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overflow: hidden; text-overflow: ellipsis; -webkit-line-clamp: 3; -webkit-box-orient: vertical; }</style><div class="col-xs-12 clearfix"><div class="u-floatLeft"><h1 class="PageHeader-title u-m0x u-fs30">ROC Curve</h1><div class="u-tcGrayDark">6,039 Followers</div><div class="u-tcGrayDark u-mt2x">Recent papers in <b>ROC Curve</b></div></div></div></div></div></div><div class="TabbedNavigation"><div class="container"><div class="row"><div class="col-xs-12 clearfix"><ul class="nav u-m0x u-p0x list-inline u-displayFlex"><li class="active"><a href="https://www.academia.edu/Documents/in/ROC_Curve">Top Papers</a></li><li><a href="https://www.academia.edu/Documents/in/ROC_Curve/MostCited">Most Cited Papers</a></li><li><a href="https://www.academia.edu/Documents/in/ROC_Curve/MostDownloaded">Most Downloaded Papers</a></li><li><a href="https://www.academia.edu/Documents/in/ROC_Curve/MostRecent">Newest Papers</a></li><li><a class="" href="https://www.academia.edu/People/ROC_Curve">People</a></li></ul></div><style type="text/css">ul.nav{flex-direction:row}@media(max-width: 567px){ul.nav{flex-direction:column}.TabbedNavigation li{max-width:100%}.TabbedNavigation li.active{background-color:var(--background-grey, #dddde2)}.TabbedNavigation li.active:before,.TabbedNavigation li.active:after{display:none}}</style></div></div></div><div class="container"><div class="row"><div class="col-xs-12"><div class="u-displayFlex"><div class="u-flexGrow1"><div class="works"><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_13025481 coauthored" data-work_id="13025481" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/13025481/An_evaluation_of_p16INK4a_expression_in_cervical_intraepithelial_neoplasia_specimens_including_women_with_HIV_1">An evaluation of p16INK4a expression in cervical intraepithelial neoplasia specimens, including women with HIV-1</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">P16 INK4a is a cyclin-dependent kinase inhibitor that regulates the transition from the G1 to S phase and negatively influences cell proliferation in conjunction with other tumour suppressor proteins, such as the retinoblastoma gene (pRb)... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_13025481" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">P16 INK4a is a cyclin-dependent kinase inhibitor that regulates the transition from the G1 to S phase and negatively influences cell proliferation in conjunction with other tumour suppressor proteins, such as the retinoblastoma gene (pRb) ). As pRb is functionally inactivated by the high-risk human papillo-human papilloma virus (HPV) oncoprotein E7, there is a concomitant overexpression of p16 INK4a . New data suggest that p16 overexpression in E7-expressing cells does not appear to result from pRB degradation, but from the induction of histone demethylases by HPV E7 . Although p16 INK4a immunostaining has been correlated with the severity of cytological and histological abnormalities in cervical lesions, variations in interpretation and a lack of standardised methodologies has resulted in uncertainty regarding the most appropriate cut-offs for the analysis of P16 INK4a levels ). This dilemma is underscored by the fact that P16 INK4a expression can be upregulated in non-dysplastic cervical lesions, including common squamous metaplasia. Moreover, published studies for the diagnostic performance of P16 INK4a in human immunodeficiency virus (HIV)infected patients remain limited ). In the present study, we assessed the expression of p16 INK4a in normal and abnormal cervical epithelium in HIV-positive and negative women and determined the diagnostic performance [receiving operating characteristics curve (ROC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)] of P16 INK4a for detecting cervical intraepithelial neoplasia (CIN) and invasive cervical cancer in tissue microarray (TMA) samples in each group.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/13025481" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="e370889ba7cfc49fbe746e9fc8d673f0" rel="nofollow" data-download="{"attachment_id":45764322,"asset_id":13025481,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/45764322/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="40647878" href="https://independent.academia.edu/Jos%C3%A9LapaESilva">José Lapa E Silva</a><script data-card-contents-for-user="40647878" type="text/json">{"id":40647878,"first_name":"José Lapa E","last_name":"Silva","domain_name":"independent","page_name":"JoséLapaESilva","display_name":"José Lapa E Silva","profile_url":"https://independent.academia.edu/Jos%C3%A9LapaESilva?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-13025481">+3</span><div class="hidden js-additional-users-13025481"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://fiocruz.academia.edu/FabioRussomano">Fabio Russomano</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/AndreaPires3">Andrea Pires</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/JonathanGolub">Jonathan Golub</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-13025481'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-13025481').html(); 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As pRb is functionally inactivated by the high-risk human papillo-human papilloma virus (HPV) oncoprotein E7, there is a concomitant overexpression of p16 INK4a . New data suggest that p16 overexpression in E7-expressing cells does not appear to result from pRB degradation, but from the induction of histone demethylases by HPV E7 . Although p16 INK4a immunostaining has been correlated with the severity of cytological and histological abnormalities in cervical lesions, variations in interpretation and a lack of standardised methodologies has resulted in uncertainty regarding the most appropriate cut-offs for the analysis of P16 INK4a levels ). This dilemma is underscored by the fact that P16 INK4a expression can be upregulated in non-dysplastic cervical lesions, including common squamous metaplasia. Moreover, published studies for the diagnostic performance of P16 INK4a in human immunodeficiency virus (HIV)infected patients remain limited ). In the present study, we assessed the expression of p16 INK4a in normal and abnormal cervical epithelium in HIV-positive and negative women and determined the diagnostic performance [receiving operating characteristics curve (ROC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)] of P16 INK4a for detecting cervical intraepithelial neoplasia (CIN) and invasive cervical cancer in tissue microarray (TMA) samples in each group.","downloadable_attachments":[{"id":45764322,"asset_id":13025481,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":40647878,"first_name":"José Lapa E","last_name":"Silva","domain_name":"independent","page_name":"JoséLapaESilva","display_name":"José Lapa E Silva","profile_url":"https://independent.academia.edu/Jos%C3%A9LapaESilva?f_ri=194916","photo":"/images/s65_no_pic.png"},{"id":32544145,"first_name":"Fabio","last_name":"Russomano","domain_name":"fiocruz","page_name":"FabioRussomano","display_name":"Fabio Russomano","profile_url":"https://fiocruz.academia.edu/FabioRussomano?f_ri=194916","photo":"/images/s65_no_pic.png"},{"id":32318295,"first_name":"Andrea","last_name":"Pires","domain_name":"independent","page_name":"AndreaPires3","display_name":"Andrea Pires","profile_url":"https://independent.academia.edu/AndreaPires3?f_ri=194916","photo":"/images/s65_no_pic.png"},{"id":32256050,"first_name":"Jonathan","last_name":"Golub","domain_name":"independent","page_name":"JonathanGolub","display_name":"Jonathan Golub","profile_url":"https://independent.academia.edu/JonathanGolub?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":6947,"name":"Medical Microbiology","url":"https://www.academia.edu/Documents/in/Medical_Microbiology?f_ri=194916","nofollow":true},{"id":12071,"name":"Immunohistochemistry","url":"https://www.academia.edu/Documents/in/Immunohistochemistry?f_ri=194916","nofollow":true},{"id":39978,"name":"HIV","url":"https://www.academia.edu/Documents/in/HIV?f_ri=194916","nofollow":true},{"id":118339,"name":"Polymerase Chain Reaction","url":"https://www.academia.edu/Documents/in/Polymerase_Chain_Reaction?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916"},{"id":1199592,"name":"Cervical Intraepithelial Neoplasia","url":"https://www.academia.edu/Documents/in/Cervical_Intraepithelial_Neoplasia?f_ri=194916"},{"id":1318932,"name":"Predictive value of tests","url":"https://www.academia.edu/Documents/in/Predictive_value_of_tests?f_ri=194916"},{"id":1819399,"name":"Case Control Studies","url":"https://www.academia.edu/Documents/in/Case_Control_Studies?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_23281770" data-work_id="23281770" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/23281770/Emerging_markers_of_cachexia_predict_survival_in_cancer_patients">Emerging markers of cachexia predict survival in cancer patients</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Background: Cachexia may occur in 40% of cancer patients, representing the major cause of death in more than 20% of them. The aim of this study was to investigate the role of leptin, ghrelin and obestatin as diagnostic and predictive... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_23281770" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Background: Cachexia may occur in 40% of cancer patients, representing the major cause of death in more than 20% of them. The aim of this study was to investigate the role of leptin, ghrelin and obestatin as diagnostic and predictive markers of cachexia in oncologic patients. Their impact on patient survival was also evaluated. Methods: 140 adults with different cancer diagnoses were recruited. Thirty healthy volunteers served as control. Serum ghrelin, obestatin and leptin were tested at baseline and after a follow-up period of 18 months. Results: Ghrelin levels were significantly higher in cancer patients than in healthy subjects (573.31 ± 130 vs 320.20 ± 66.48 ng/ml, p < 0.0001), while obestatin (17.42 ± 7.12 vs 24.89 ± 5.54 ng/ml, p < 0.0001) and leptin (38.4 ± 21.2 vs 76.28 ± 17.48 ng/ml, p < 0.0001) values were lower. At ROC analyses the diagnostic profile of ghrelin (AUC 0.962; sensitivity 83%; specificity 98%), obestatin (AUC 0.798; sensitivity 74.5%; specificity 81.5%) and leptin (AUC 0.828; sensitivity 79%; specificity 73%) was superior to that of albumin (AUC 0.547; sensitivity 63%, specificity 69.4%) for detecting cachexia among cancer patients. On Cox multivariate analyses ghrelin (HR 1.02; 95% CI 1.01 -1.03; p < 0.0001) and leptin (HR 0.94; 95% CI 0.92 -0.96; p < 0.0001) were significant predictors of death even after correction for other known risk factors such as presence of metastasis and chronic kidney disease. Conclusion: Ghrelin and leptin are promising biomarkers to diagnose cachexia and to predict survival in cancer patients.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/23281770" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="2dac5caa56e082f2fa21c253fbb3aad9" rel="nofollow" data-download="{"attachment_id":43751435,"asset_id":23281770,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/43751435/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="45162731" href="https://unime.academia.edu/SMondello">Stefania Mondello</a><script data-card-contents-for-user="45162731" type="text/json">{"id":45162731,"first_name":"Stefania","last_name":"Mondello","domain_name":"unime","page_name":"SMondello","display_name":"Stefania Mondello","profile_url":"https://unime.academia.edu/SMondello?f_ri=194916","photo":"https://0.academia-photos.com/45162731/28977264/27032638/s65_stefania.mondello.jpg"}</script></span></span></li><li class="js-paper-rank-work_23281770 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="23281770"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 23281770, container: ".js-paper-rank-work_23281770", }); 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$(".js-view-count[data-work-id=23281770]").text(description); $(".js-view-count-work_23281770").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_23281770").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="23281770"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">18</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="41783" rel="nofollow" href="https://www.academia.edu/Documents/in/Ghrelin">Ghrelin</a>, <script data-card-contents-for-ri="41783" type="text/json">{"id":41783,"name":"Ghrelin","url":"https://www.academia.edu/Documents/in/Ghrelin?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="49633" rel="nofollow" href="https://www.academia.edu/Documents/in/Heart_Failure">Heart Failure</a>, <script data-card-contents-for-ri="49633" type="text/json">{"id":49633,"name":"Heart Failure","url":"https://www.academia.edu/Documents/in/Heart_Failure?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="71511" rel="nofollow" href="https://www.academia.edu/Documents/in/Diabetes_mellitus">Diabetes mellitus</a>, <script data-card-contents-for-ri="71511" type="text/json">{"id":71511,"name":"Diabetes mellitus","url":"https://www.academia.edu/Documents/in/Diabetes_mellitus?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="90514" rel="nofollow" href="https://www.academia.edu/Documents/in/Cholesterol">Cholesterol</a><script data-card-contents-for-ri="90514" type="text/json">{"id":90514,"name":"Cholesterol","url":"https://www.academia.edu/Documents/in/Cholesterol?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=23281770]'), work: {"id":23281770,"title":"Emerging markers of cachexia predict survival in cancer patients","created_at":"2016-03-15T08:26:18.887-07:00","url":"https://www.academia.edu/23281770/Emerging_markers_of_cachexia_predict_survival_in_cancer_patients?f_ri=194916","dom_id":"work_23281770","summary":"Background: Cachexia may occur in 40% of cancer patients, representing the major cause of death in more than 20% of them. The aim of this study was to investigate the role of leptin, ghrelin and obestatin as diagnostic and predictive markers of cachexia in oncologic patients. Their impact on patient survival was also evaluated. Methods: 140 adults with different cancer diagnoses were recruited. Thirty healthy volunteers served as control. Serum ghrelin, obestatin and leptin were tested at baseline and after a follow-up period of 18 months. Results: Ghrelin levels were significantly higher in cancer patients than in healthy subjects (573.31 ± 130 vs 320.20 ± 66.48 ng/ml, p \u003c 0.0001), while obestatin (17.42 ± 7.12 vs 24.89 ± 5.54 ng/ml, p \u003c 0.0001) and leptin (38.4 ± 21.2 vs 76.28 ± 17.48 ng/ml, p \u003c 0.0001) values were lower. At ROC analyses the diagnostic profile of ghrelin (AUC 0.962; sensitivity 83%; specificity 98%), obestatin (AUC 0.798; sensitivity 74.5%; specificity 81.5%) and leptin (AUC 0.828; sensitivity 79%; specificity 73%) was superior to that of albumin (AUC 0.547; sensitivity 63%, specificity 69.4%) for detecting cachexia among cancer patients. On Cox multivariate analyses ghrelin (HR 1.02; 95% CI 1.01 -1.03; p \u003c 0.0001) and leptin (HR 0.94; 95% CI 0.92 -0.96; p \u003c 0.0001) were significant predictors of death even after correction for other known risk factors such as presence of metastasis and chronic kidney disease. Conclusion: Ghrelin and leptin are promising biomarkers to diagnose cachexia and to predict survival in cancer patients.","downloadable_attachments":[{"id":43751435,"asset_id":23281770,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":45162731,"first_name":"Stefania","last_name":"Mondello","domain_name":"unime","page_name":"SMondello","display_name":"Stefania Mondello","profile_url":"https://unime.academia.edu/SMondello?f_ri=194916","photo":"https://0.academia-photos.com/45162731/28977264/27032638/s65_stefania.mondello.jpg"}],"research_interests":[{"id":41783,"name":"Ghrelin","url":"https://www.academia.edu/Documents/in/Ghrelin?f_ri=194916","nofollow":true},{"id":49633,"name":"Heart Failure","url":"https://www.academia.edu/Documents/in/Heart_Failure?f_ri=194916","nofollow":true},{"id":71511,"name":"Diabetes mellitus","url":"https://www.academia.edu/Documents/in/Diabetes_mellitus?f_ri=194916","nofollow":true},{"id":90514,"name":"Cholesterol","url":"https://www.academia.edu/Documents/in/Cholesterol?f_ri=194916","nofollow":true},{"id":135357,"name":"Leptin","url":"https://www.academia.edu/Documents/in/Leptin?f_ri=194916"},{"id":137516,"name":"Follow-up studies","url":"https://www.academia.edu/Documents/in/Follow-up_studies?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916"},{"id":424295,"name":"Survival Rate","url":"https://www.academia.edu/Documents/in/Survival_Rate?f_ri=194916"},{"id":469018,"name":"Neoplasms","url":"https://www.academia.edu/Documents/in/Neoplasms?f_ri=194916"},{"id":540859,"name":"Cachexia","url":"https://www.academia.edu/Documents/in/Cachexia?f_ri=194916"},{"id":568482,"name":"Biological markers","url":"https://www.academia.edu/Documents/in/Biological_markers?f_ri=194916"},{"id":881608,"name":"Bovine Serum Albumin","url":"https://www.academia.edu/Documents/in/Bovine_Serum_Albumin?f_ri=194916"},{"id":1272981,"name":"Proportional Hazards Models","url":"https://www.academia.edu/Documents/in/Proportional_Hazards_Models?f_ri=194916"},{"id":1309706,"name":"Area Under Curve","url":"https://www.academia.edu/Documents/in/Area_Under_Curve?f_ri=194916"},{"id":1318932,"name":"Predictive value of tests","url":"https://www.academia.edu/Documents/in/Predictive_value_of_tests?f_ri=194916"},{"id":1819399,"name":"Case Control Studies","url":"https://www.academia.edu/Documents/in/Case_Control_Studies?f_ri=194916"},{"id":2349258,"name":"Serum albumin","url":"https://www.academia.edu/Documents/in/Serum_albumin?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3891898" data-work_id="3891898" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3891898/Brief_DISCERN_six_questions_for_the_evaluation_of_evidence_based_content_of_health_related_websites">Brief DISCERN, six questions for the evaluation of evidence-based content of health-related websites</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Objective: To extract and to validate a brief version of the DISCERN which could identify mental healthrelated websites with good content quality. Method: The present study is based on the analysis of data issued from six previous studies... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3891898" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Objective: To extract and to validate a brief version of the DISCERN which could identify mental healthrelated websites with good content quality. Method: The present study is based on the analysis of data issued from six previous studies which used DISCERN and a standardized tool for the evaluation of content quality (evidence-based health information) of 388 mental health-related websites.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3891898" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c6f9a939f7847b081f547da65128f740" rel="nofollow" data-download="{"attachment_id":50105425,"asset_id":3891898,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50105425/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="4776887" href="https://ehl.academia.edu/S%C3%A9bastienFernandez">Sébastien Fernandez</a><script data-card-contents-for-user="4776887" type="text/json">{"id":4776887,"first_name":"Sébastien","last_name":"Fernandez","domain_name":"ehl","page_name":"SébastienFernandez","display_name":"Sébastien Fernandez","profile_url":"https://ehl.academia.edu/S%C3%A9bastienFernandez?f_ri=194916","photo":"https://0.academia-photos.com/4776887/2031107/2394114/s65_s_bastien.fernandez.jpg"}</script></span></span></li><li class="js-paper-rank-work_3891898 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="3891898"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 3891898, container: ".js-paper-rank-work_3891898", }); 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$(".js-view-count[data-work-id=3891898]").text(description); $(".js-view-count-work_3891898").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_3891898").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="3891898"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">15</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2599" rel="nofollow" href="https://www.academia.edu/Documents/in/Psychometrics">Psychometrics</a>, <script data-card-contents-for-ri="2599" type="text/json">{"id":2599,"name":"Psychometrics","url":"https://www.academia.edu/Documents/in/Psychometrics?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="2827" rel="nofollow" href="https://www.academia.edu/Documents/in/Mental_Health">Mental Health</a>, <script data-card-contents-for-ri="2827" type="text/json">{"id":2827,"name":"Mental Health","url":"https://www.academia.edu/Documents/in/Mental_Health?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="3645" rel="nofollow" href="https://www.academia.edu/Documents/in/Evidence_Based_Medicine">Evidence Based Medicine</a>, <script data-card-contents-for-ri="3645" type="text/json">{"id":3645,"name":"Evidence Based Medicine","url":"https://www.academia.edu/Documents/in/Evidence_Based_Medicine?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="4441" rel="nofollow" href="https://www.academia.edu/Documents/in/Health_Care">Health Care</a><script data-card-contents-for-ri="4441" type="text/json">{"id":4441,"name":"Health Care","url":"https://www.academia.edu/Documents/in/Health_Care?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=3891898]'), work: {"id":3891898,"title":"Brief DISCERN, six questions for the evaluation of evidence-based content of health-related websites","created_at":"2013-07-08T01:05:35.793-07:00","url":"https://www.academia.edu/3891898/Brief_DISCERN_six_questions_for_the_evaluation_of_evidence_based_content_of_health_related_websites?f_ri=194916","dom_id":"work_3891898","summary":"Objective: To extract and to validate a brief version of the DISCERN which could identify mental healthrelated websites with good content quality. Method: The present study is based on the analysis of data issued from six previous studies which used DISCERN and a standardized tool for the evaluation of content quality (evidence-based health information) of 388 mental health-related websites.","downloadable_attachments":[{"id":50105425,"asset_id":3891898,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":4776887,"first_name":"Sébastien","last_name":"Fernandez","domain_name":"ehl","page_name":"SébastienFernandez","display_name":"Sébastien Fernandez","profile_url":"https://ehl.academia.edu/S%C3%A9bastienFernandez?f_ri=194916","photo":"https://0.academia-photos.com/4776887/2031107/2394114/s65_s_bastien.fernandez.jpg"}],"research_interests":[{"id":2599,"name":"Psychometrics","url":"https://www.academia.edu/Documents/in/Psychometrics?f_ri=194916","nofollow":true},{"id":2827,"name":"Mental Health","url":"https://www.academia.edu/Documents/in/Mental_Health?f_ri=194916","nofollow":true},{"id":3645,"name":"Evidence Based Medicine","url":"https://www.academia.edu/Documents/in/Evidence_Based_Medicine?f_ri=194916","nofollow":true},{"id":4441,"name":"Health Care","url":"https://www.academia.edu/Documents/in/Health_Care?f_ri=194916","nofollow":true},{"id":7428,"name":"Health Education","url":"https://www.academia.edu/Documents/in/Health_Education?f_ri=194916"},{"id":15015,"name":"Access To Information","url":"https://www.academia.edu/Documents/in/Access_To_Information?f_ri=194916"},{"id":28850,"name":"Linear models","url":"https://www.academia.edu/Documents/in/Linear_models?f_ri=194916"},{"id":53776,"name":"Factorial Analysis","url":"https://www.academia.edu/Documents/in/Factorial_Analysis?f_ri=194916"},{"id":62928,"name":"Consumer","url":"https://www.academia.edu/Documents/in/Consumer?f_ri=194916"},{"id":171144,"name":"Mental Disorders","url":"https://www.academia.edu/Documents/in/Mental_Disorders?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":327850,"name":"Questionnaires","url":"https://www.academia.edu/Documents/in/Questionnaires?f_ri=194916"},{"id":549280,"name":"Reproducibility of Results","url":"https://www.academia.edu/Documents/in/Reproducibility_of_Results?f_ri=194916"},{"id":1191356,"name":"Internet","url":"https://www.academia.edu/Documents/in/Internet?f_ri=194916"},{"id":2463496,"name":"Statistics as Topic","url":"https://www.academia.edu/Documents/in/Statistics_as_Topic?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_29097862" data-work_id="29097862" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/29097862/Thermographic_and_clinical_correlation_of_myofascial_trigger_points_in_the_masticatory_muscles">Thermographic and clinical correlation of myofascial trigger points in the masticatory muscles</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Objectives: The aim of the study was to identify and correlate myofascial trigger points (MTPs) in the masticatory muscles, using thermography and algometry. Methods: 26 female volunteers were recruited. The surface facial area over the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_29097862" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Objectives: The aim of the study was to identify and correlate myofascial trigger points (MTPs) in the masticatory muscles, using thermography and algometry. Methods: 26 female volunteers were recruited. The surface facial area over the masseter and anterior temporalis muscles was divided into 15 subareas on each side (n 5 780). This investigation consisted of three steps. The first step involved thermographic facial examination, using lateral views. The second step involved the pressure pain threshold (PPT), marking the MTP pattern areas for referred pain (n 5 131) and local pain (n 5 282) with a coloured pencil, and a photograph of the lateral face with the head in the same position as the infrared imaging. The last step was the fusion of these two images, using dedicated software (ReporterH 8.5-SP3 Professional Edition and QuickReportH 1.2, FLIR Systems, Wilsonville, OR); and the calculation of the temperature of each point. Results: PPT levels measured at the points of referred pain in MTPs (1.28 ¡ 0.45 kgf) were significantly lower than the points of local pain in MTPs (1.73 ¡ 0.59 kgf; p , 0.05). Infrared imaging indicated differences between referred and local pain in MTPs of 0.5 u C (p , 0.05). Analysis of the correlation between the PPT and infrared imaging was done using the Spearman non-parametric method, in which the correlations were positive and moderate (0.4 # r , 0.7). The sensitivity and specificity in MTPs were 62.5% and 71.3%, respectively, for referred pain, and 43.6% and 60.6%, respectively, for local pain. Conclusion: Infrared imaging measurements can provide a useful, non-invasive and nonionizing examination for diagnosis of MTPs in masticatory muscles.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/29097862" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c2cdd16d836d86877e1e7272ccafee79" rel="nofollow" data-download="{"attachment_id":49545819,"asset_id":29097862,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/49545819/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="54896964" href="https://independent.academia.edu/DeniseHaddad1">Denise Haddad</a><script data-card-contents-for-user="54896964" type="text/json">{"id":54896964,"first_name":"Denise","last_name":"Haddad","domain_name":"independent","page_name":"DeniseHaddad1","display_name":"Denise Haddad","profile_url":"https://independent.academia.edu/DeniseHaddad1?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_29097862 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="29097862"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 29097862, container: ".js-paper-rank-work_29097862", }); 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$(".js-view-count[data-work-id=29097862]").text(description); $(".js-view-count-work_29097862").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_29097862").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="29097862"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">16</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="596" rel="nofollow" href="https://www.academia.edu/Documents/in/Dentistry">Dentistry</a>, <script data-card-contents-for-ri="596" type="text/json">{"id":596,"name":"Dentistry","url":"https://www.academia.edu/Documents/in/Dentistry?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="1589" rel="nofollow" href="https://www.academia.edu/Documents/in/Photography">Photography</a>, <script data-card-contents-for-ri="1589" type="text/json">{"id":1589,"name":"Photography","url":"https://www.academia.edu/Documents/in/Photography?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="15635" rel="nofollow" href="https://www.academia.edu/Documents/in/Thermography">Thermography</a>, <script data-card-contents-for-ri="15635" type="text/json">{"id":15635,"name":"Thermography","url":"https://www.academia.edu/Documents/in/Thermography?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="133057" rel="nofollow" href="https://www.academia.edu/Documents/in/Young_Adult">Young Adult</a><script data-card-contents-for-ri="133057" type="text/json">{"id":133057,"name":"Young Adult","url":"https://www.academia.edu/Documents/in/Young_Adult?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=29097862]'), work: {"id":29097862,"title":"Thermographic and clinical correlation of myofascial trigger points in the masticatory muscles","created_at":"2016-10-12T05:44:30.802-07:00","url":"https://www.academia.edu/29097862/Thermographic_and_clinical_correlation_of_myofascial_trigger_points_in_the_masticatory_muscles?f_ri=194916","dom_id":"work_29097862","summary":"Objectives: The aim of the study was to identify and correlate myofascial trigger points (MTPs) in the masticatory muscles, using thermography and algometry. Methods: 26 female volunteers were recruited. The surface facial area over the masseter and anterior temporalis muscles was divided into 15 subareas on each side (n 5 780). This investigation consisted of three steps. The first step involved thermographic facial examination, using lateral views. The second step involved the pressure pain threshold (PPT), marking the MTP pattern areas for referred pain (n 5 131) and local pain (n 5 282) with a coloured pencil, and a photograph of the lateral face with the head in the same position as the infrared imaging. The last step was the fusion of these two images, using dedicated software (ReporterH 8.5-SP3 Professional Edition and QuickReportH 1.2, FLIR Systems, Wilsonville, OR); and the calculation of the temperature of each point. Results: PPT levels measured at the points of referred pain in MTPs (1.28 ¡ 0.45 kgf) were significantly lower than the points of local pain in MTPs (1.73 ¡ 0.59 kgf; p , 0.05). Infrared imaging indicated differences between referred and local pain in MTPs of 0.5 u C (p , 0.05). Analysis of the correlation between the PPT and infrared imaging was done using the Spearman non-parametric method, in which the correlations were positive and moderate (0.4 # r , 0.7). The sensitivity and specificity in MTPs were 62.5% and 71.3%, respectively, for referred pain, and 43.6% and 60.6%, respectively, for local pain. Conclusion: Infrared imaging measurements can provide a useful, non-invasive and nonionizing examination for diagnosis of MTPs in masticatory muscles.","downloadable_attachments":[{"id":49545819,"asset_id":29097862,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":54896964,"first_name":"Denise","last_name":"Haddad","domain_name":"independent","page_name":"DeniseHaddad1","display_name":"Denise Haddad","profile_url":"https://independent.academia.edu/DeniseHaddad1?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":596,"name":"Dentistry","url":"https://www.academia.edu/Documents/in/Dentistry?f_ri=194916","nofollow":true},{"id":1589,"name":"Photography","url":"https://www.academia.edu/Documents/in/Photography?f_ri=194916","nofollow":true},{"id":15635,"name":"Thermography","url":"https://www.academia.edu/Documents/in/Thermography?f_ri=194916","nofollow":true},{"id":133057,"name":"Young Adult","url":"https://www.academia.edu/Documents/in/Young_Adult?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916"},{"id":291038,"name":"Pressure","url":"https://www.academia.edu/Documents/in/Pressure?f_ri=194916"},{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916"},{"id":976256,"name":"Skin Temperature","url":"https://www.academia.edu/Documents/in/Skin_Temperature?f_ri=194916"},{"id":1155236,"name":"Trigger Points","url":"https://www.academia.edu/Documents/in/Trigger_Points?f_ri=194916"},{"id":1237674,"name":"Dentomaxillofacial Radiology","url":"https://www.academia.edu/Documents/in/Dentomaxillofacial_Radiology?f_ri=194916"},{"id":1262481,"name":"Pain Measurement","url":"https://www.academia.edu/Documents/in/Pain_Measurement?f_ri=194916"},{"id":1296162,"name":"Infrared Rays","url":"https://www.academia.edu/Documents/in/Infrared_Rays?f_ri=194916"},{"id":1309706,"name":"Area Under Curve","url":"https://www.academia.edu/Documents/in/Area_Under_Curve?f_ri=194916"},{"id":1484871,"name":"Pain Threshold","url":"https://www.academia.edu/Documents/in/Pain_Threshold?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_36903295" data-work_id="36903295" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/36903295/Prognostic_factors_of_acute_cholangitis_in_cases_managed_using_the_Tokyo_Guidelines">Prognostic factors of acute cholangitis in cases managed using the Tokyo Guidelines</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Background/purpose In 2007, the Tokyo Guidelines (TG07) working group established diagnostic criteria for assessment of the severity of acute cholangitis. This study aimed to analyze outcomes and identify predictors of mortality in... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_36903295" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Background/purpose In 2007, the Tokyo Guidelines (TG07) working group established diagnostic criteria for assessment of the severity of acute cholangitis. This study aimed to analyze outcomes and identify predictors of mortality in patients with acute cholangitis managed according to the TG07. Methods In this study, 215 consecutive cases of acute cholangitis were reviewed. Risk factors associated with mortality or refractory cholangitis, which is defined on the basis of prolonged hospitalization ([28 days) or disease resulting in fatality, were examined using multivariate logistic regression analysis. Results There were 52, 133, and 30 cases of mild, moderate, and severe cholangitis, respectively. The overall mortality rate was 4.2 % (9/215). Mortality rates in patients with mild, moderate, and severe cholangitis were 0, 2.3, and 20.0 %, respectively (moderate vs. severe, p = 0.001). Multivariate analysis showed that serum albumin levels B2.8 g/dl and PT-INR [1.5 were significant predictors of mortality. There were 57 patients (26.5 %) with refractory cholangitis. Multivariate analysis showed that serum albumin level B2.8 g/dl, PT-INR [1.5, etiology and inpatient status were significant predictors of refractory cholangitis. Conclusions The TG07 severity assessment criteria for acute cholangitis were significantly predictive of mortality. Hypoalbuminemia is an important risk factor in addition to organ dysfunction.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/36903295" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="9bb891eff5625e0cb957461b0603feaa" rel="nofollow" data-download="{"attachment_id":56854993,"asset_id":36903295,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/56854993/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="83400444" href="https://independent.academia.edu/HarutoshiSugiyama">Harutoshi Sugiyama</a><script data-card-contents-for-user="83400444" type="text/json">{"id":83400444,"first_name":"Harutoshi","last_name":"Sugiyama","domain_name":"independent","page_name":"HarutoshiSugiyama","display_name":"Harutoshi Sugiyama","profile_url":"https://independent.academia.edu/HarutoshiSugiyama?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_36903295 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="36903295"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 36903295, container: ".js-paper-rank-work_36903295", }); 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$(".js-view-count[data-work-id=36903295]").text(description); $(".js-view-count-work_36903295").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_36903295").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="36903295"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a>, <script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="289271" rel="nofollow" href="https://www.academia.edu/Documents/in/Aged">Aged</a>, <script data-card-contents-for-ri="289271" type="text/json">{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="489727" rel="nofollow" href="https://www.academia.edu/Documents/in/Prognosis">Prognosis</a>, <script data-card-contents-for-ri="489727" type="text/json">{"id":489727,"name":"Prognosis","url":"https://www.academia.edu/Documents/in/Prognosis?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="2460570" rel="nofollow" href="https://www.academia.edu/Documents/in/Cholangitis">Cholangitis</a><script data-card-contents-for-ri="2460570" type="text/json">{"id":2460570,"name":"Cholangitis","url":"https://www.academia.edu/Documents/in/Cholangitis?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=36903295]'), work: {"id":36903295,"title":"Prognostic factors of acute cholangitis in cases managed using the Tokyo Guidelines","created_at":"2018-06-23T11:55:15.381-07:00","url":"https://www.academia.edu/36903295/Prognostic_factors_of_acute_cholangitis_in_cases_managed_using_the_Tokyo_Guidelines?f_ri=194916","dom_id":"work_36903295","summary":"Background/purpose In 2007, the Tokyo Guidelines (TG07) working group established diagnostic criteria for assessment of the severity of acute cholangitis. This study aimed to analyze outcomes and identify predictors of mortality in patients with acute cholangitis managed according to the TG07. Methods In this study, 215 consecutive cases of acute cholangitis were reviewed. Risk factors associated with mortality or refractory cholangitis, which is defined on the basis of prolonged hospitalization ([28 days) or disease resulting in fatality, were examined using multivariate logistic regression analysis. Results There were 52, 133, and 30 cases of mild, moderate, and severe cholangitis, respectively. The overall mortality rate was 4.2 % (9/215). Mortality rates in patients with mild, moderate, and severe cholangitis were 0, 2.3, and 20.0 %, respectively (moderate vs. severe, p = 0.001). Multivariate analysis showed that serum albumin levels B2.8 g/dl and PT-INR [1.5 were significant predictors of mortality. There were 57 patients (26.5 %) with refractory cholangitis. Multivariate analysis showed that serum albumin level B2.8 g/dl, PT-INR [1.5, etiology and inpatient status were significant predictors of refractory cholangitis. Conclusions The TG07 severity assessment criteria for acute cholangitis were significantly predictive of mortality. Hypoalbuminemia is an important risk factor in addition to organ dysfunction.","downloadable_attachments":[{"id":56854993,"asset_id":36903295,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":83400444,"first_name":"Harutoshi","last_name":"Sugiyama","domain_name":"independent","page_name":"HarutoshiSugiyama","display_name":"Harutoshi Sugiyama","profile_url":"https://independent.academia.edu/HarutoshiSugiyama?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916","nofollow":true},{"id":489727,"name":"Prognosis","url":"https://www.academia.edu/Documents/in/Prognosis?f_ri=194916","nofollow":true},{"id":2460570,"name":"Cholangitis","url":"https://www.academia.edu/Documents/in/Cholangitis?f_ri=194916","nofollow":true},{"id":2463800,"name":"Severity of Illness Index","url":"https://www.academia.edu/Documents/in/Severity_of_Illness_Index?f_ri=194916"},{"id":2471455,"name":"Acute Disease","url":"https://www.academia.edu/Documents/in/Acute_Disease?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_73284651" data-work_id="73284651" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/73284651/A_risk_score_to_predict_need_for_treatment_for_uppergastrointestinal_haemorrhage">A risk score to predict need for treatment for uppergastrointestinal haemorrhage</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Background Current risk-stratification systems for patients with acute upper-gastrointestinal bleeding discriminate between patients at high or low risks of dying or rebleeding. We therefore developed and prospectively validated a risk... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_73284651" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Background Current risk-stratification systems for patients with acute upper-gastrointestinal bleeding discriminate between patients at high or low risks of dying or rebleeding. We therefore developed and prospectively validated a risk score to identify a patient's need for treatment. Methods Our first study used data from 1748 patients admitted for upper-gastrointestinal haemorrhage. By logistic regression, we derived a risk score that predicts patients' risks of needing blood transfusion or intervention to control bleeding, rebleeding, or dying. From this score, we developed a simplified fast-track screen for use at initial presentation. In a second study, we prospectively validated this score using receiver operating characteristic (ROC) curves-a measure of the validity of a scoring system-and 2 goodness-of-fit testing with data from 197 patients. We also validated the quicker screening tool. Findings We calculated risk scores from patients' admission haemoglobin, blood urea, pulse, and systolic blood pressure, as well as presentation with syncope or melaena, and evidence of hepatic disease or cardiac failure. The score discriminated well with a ROC curve area of 0•92 (95% CI 0•88-0•95). The score was well calibrated for patients needing treatment (p=0•84). Interpretation Our score identified patients at low or high risk of needing treatment to manage their bleeding. This score should assist the clinical management of patients presenting with upper-gastrointestinal haemorrhage, but requires external validation.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/73284651" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="4c6c5accb527e184cb485d864052b0d7" rel="nofollow" data-download="{"attachment_id":81864035,"asset_id":73284651,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/81864035/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="205758329" href="https://independent.academia.edu/NgaHo%C3%A0ng127">Nga Hoàng</a><script data-card-contents-for-user="205758329" type="text/json">{"id":205758329,"first_name":"Nga","last_name":"Hoàng","domain_name":"independent","page_name":"NgaHoàng127","display_name":"Nga Hoàng","profile_url":"https://independent.academia.edu/NgaHo%C3%A0ng127?f_ri=194916","photo":"https://0.academia-photos.com/205758329/66290123/54639534/s65_nga.ho_ng.png"}</script></span></span></li><li class="js-paper-rank-work_73284651 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="73284651"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 73284651, container: ".js-paper-rank-work_73284651", }); 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$(".js-view-count[data-work-id=73284651]").text(description); $(".js-view-count-work_73284651").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_73284651").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="73284651"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">15</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="26327" rel="nofollow" href="https://www.academia.edu/Documents/in/Medicine">Medicine</a>, <script data-card-contents-for-ri="26327" type="text/json">{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="62112" rel="nofollow" href="https://www.academia.edu/Documents/in/Prospective_studies">Prospective studies</a>, <script data-card-contents-for-ri="62112" type="text/json">{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="81559" rel="nofollow" href="https://www.academia.edu/Documents/in/Scotland">Scotland</a>, <script data-card-contents-for-ri="81559" type="text/json">{"id":81559,"name":"Scotland","url":"https://www.academia.edu/Documents/in/Scotland?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="88321" rel="nofollow" href="https://www.academia.edu/Documents/in/Blood_Pressure">Blood Pressure</a><script data-card-contents-for-ri="88321" type="text/json">{"id":88321,"name":"Blood Pressure","url":"https://www.academia.edu/Documents/in/Blood_Pressure?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=73284651]'), work: {"id":73284651,"title":"A risk score to predict need for treatment for uppergastrointestinal haemorrhage","created_at":"2022-03-07T20:22:30.022-08:00","url":"https://www.academia.edu/73284651/A_risk_score_to_predict_need_for_treatment_for_uppergastrointestinal_haemorrhage?f_ri=194916","dom_id":"work_73284651","summary":"Background Current risk-stratification systems for patients with acute upper-gastrointestinal bleeding discriminate between patients at high or low risks of dying or rebleeding. We therefore developed and prospectively validated a risk score to identify a patient's need for treatment. Methods Our first study used data from 1748 patients admitted for upper-gastrointestinal haemorrhage. By logistic regression, we derived a risk score that predicts patients' risks of needing blood transfusion or intervention to control bleeding, rebleeding, or dying. From this score, we developed a simplified fast-track screen for use at initial presentation. In a second study, we prospectively validated this score using receiver operating characteristic (ROC) curves-a measure of the validity of a scoring system-and 2 goodness-of-fit testing with data from 197 patients. We also validated the quicker screening tool. Findings We calculated risk scores from patients' admission haemoglobin, blood urea, pulse, and systolic blood pressure, as well as presentation with syncope or melaena, and evidence of hepatic disease or cardiac failure. The score discriminated well with a ROC curve area of 0•92 (95% CI 0•88-0•95). The score was well calibrated for patients needing treatment (p=0•84). Interpretation Our score identified patients at low or high risk of needing treatment to manage their bleeding. This score should assist the clinical management of patients presenting with upper-gastrointestinal haemorrhage, but requires external validation.","downloadable_attachments":[{"id":81864035,"asset_id":73284651,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":205758329,"first_name":"Nga","last_name":"Hoàng","domain_name":"independent","page_name":"NgaHoàng127","display_name":"Nga Hoàng","profile_url":"https://independent.academia.edu/NgaHo%C3%A0ng127?f_ri=194916","photo":"https://0.academia-photos.com/205758329/66290123/54639534/s65_nga.ho_ng.png"}],"research_interests":[{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine?f_ri=194916","nofollow":true},{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true},{"id":81559,"name":"Scotland","url":"https://www.academia.edu/Documents/in/Scotland?f_ri=194916","nofollow":true},{"id":88321,"name":"Blood Pressure","url":"https://www.academia.edu/Documents/in/Blood_Pressure?f_ri=194916","nofollow":true},{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":243629,"name":"Lancet","url":"https://www.academia.edu/Documents/in/Lancet?f_ri=194916"},{"id":620049,"name":"Risk Factors","url":"https://www.academia.edu/Documents/in/Risk_Factors-1?f_ri=194916"},{"id":627890,"name":"Blood Transfusion","url":"https://www.academia.edu/Documents/in/Blood_Transfusion?f_ri=194916"},{"id":1311261,"name":"Hemoglobins","url":"https://www.academia.edu/Documents/in/Hemoglobins?f_ri=194916"},{"id":1318932,"name":"Predictive value of tests","url":"https://www.academia.edu/Documents/in/Predictive_value_of_tests?f_ri=194916"},{"id":1937356,"name":"Risk Score","url":"https://www.academia.edu/Documents/in/Risk_Score?f_ri=194916"},{"id":2463800,"name":"Severity of Illness Index","url":"https://www.academia.edu/Documents/in/Severity_of_Illness_Index?f_ri=194916"},{"id":3094070,"name":"The Lancet","url":"https://www.academia.edu/Documents/in/The_Lancet?f_ri=194916"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_73257120" data-work_id="73257120" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/73257120/Analysis_of_blood_based_gene_expression_in_idiopathic_Parkinson_disease">Analysis of blood-based gene expression in idiopathic Parkinson disease</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Objective:To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_73257120" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Objective:To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples).Methods:Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks.Results:A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was ident...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/73257120" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="3dd637c0b29f9e418782ce9b75814b8d" rel="nofollow" data-download="{"attachment_id":81847780,"asset_id":73257120,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/81847780/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="159390476" href="https://independent.academia.edu/ROnShamir">ROn Shamir</a><script data-card-contents-for-user="159390476" type="text/json">{"id":159390476,"first_name":"ROn","last_name":"Shamir","domain_name":"independent","page_name":"ROnShamir","display_name":"ROn Shamir","profile_url":"https://independent.academia.edu/ROnShamir?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_73257120 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="73257120"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 73257120, container: ".js-paper-rank-work_73257120", }); 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After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks.Results:A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was ident...","downloadable_attachments":[{"id":81847780,"asset_id":73257120,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":159390476,"first_name":"ROn","last_name":"Shamir","domain_name":"independent","page_name":"ROnShamir","display_name":"ROn Shamir","profile_url":"https://independent.academia.edu/ROnShamir?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":237,"name":"Cognitive Science","url":"https://www.academia.edu/Documents/in/Cognitive_Science?f_ri=194916","nofollow":true},{"id":623,"name":"Neurology","url":"https://www.academia.edu/Documents/in/Neurology?f_ri=194916","nofollow":true},{"id":6970,"name":"Biomarkers","url":"https://www.academia.edu/Documents/in/Biomarkers?f_ri=194916","nofollow":true},{"id":7710,"name":"Biology","url":"https://www.academia.edu/Documents/in/Biology?f_ri=194916","nofollow":true},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine?f_ri=194916"},{"id":37848,"name":"Neurodegenerative Diseases","url":"https://www.academia.edu/Documents/in/Neurodegenerative_Diseases?f_ri=194916"},{"id":43761,"name":"Transcriptome","url":"https://www.academia.edu/Documents/in/Transcriptome?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":210852,"name":"Gene Regulatory Networks","url":"https://www.academia.edu/Documents/in/Gene_Regulatory_Networks?f_ri=194916"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":375301,"name":"Microarray Analysis","url":"https://www.academia.edu/Documents/in/Microarray_Analysis?f_ri=194916"},{"id":549280,"name":"Reproducibility of Results","url":"https://www.academia.edu/Documents/in/Reproducibility_of_Results?f_ri=194916"},{"id":1239755,"name":"Neurosciences","url":"https://www.academia.edu/Documents/in/Neurosciences?f_ri=194916"},{"id":1541077,"name":"Parkinson Disease","url":"https://www.academia.edu/Documents/in/Parkinson_Disease?f_ri=194916"},{"id":1810445,"name":"Gene expression profiling","url":"https://www.academia.edu/Documents/in/Gene_expression_profiling?f_ri=194916"},{"id":1819400,"name":"Cohort Studies","url":"https://www.academia.edu/Documents/in/Cohort_Studies?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_68682203" data-work_id="68682203" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/68682203/Iris_localization_via_intensity_gradient_and_recognition_through_bit_planes">Iris localization via intensity gradient and recognition through bit planes</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Iris recognition is very hot topic in both research and practical applications. In this paper, a robust algorithm is proposed for iris localization and a very simple method is employed for feature extraction. Iris localization is the key... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_68682203" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Iris recognition is very hot topic in both research and practical applications. In this paper, a robust algorithm is proposed for iris localization and a very simple method is employed for feature extraction. Iris localization is the key step in iris recognition systems because all subsequent steps depend highly on its accuracy. The proposed algorithm utilizes important property of gradient of intensity level in the greyscale images (after converting the images into greyscale if not). Then iris is normalized into a dimensionless rectangular strip of size 128*512 pixels and different features are extracted based upon bit plane slicing of the strip to get binary iris code. ROC curves are also drawn for different features. Matching decision is based on accumulative sum of bitwise XOR of different iris codes. Experiments show that proposed localization algorithm is very effective. Results have been tabulated by evaluating the developed algorithm with 1000 eye images and recognition accuracy has reached up to 99.6%.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/68682203" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="caf54ec7d5f9b131846d15969f5ba004" rel="nofollow" data-download="{"attachment_id":79077751,"asset_id":68682203,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/79077751/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="96108414" href="https://independent.academia.edu/abdulBasit741">abdul Basit</a><script data-card-contents-for-user="96108414" type="text/json">{"id":96108414,"first_name":"abdul","last_name":"Basit","domain_name":"independent","page_name":"abdulBasit741","display_name":"abdul Basit","profile_url":"https://independent.academia.edu/abdulBasit741?f_ri=194916","photo":"https://0.academia-photos.com/96108414/21118066/20589589/s65_abdul.basit.jpg"}</script></span></span></li><li class="js-paper-rank-work_68682203 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="68682203"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 68682203, container: ".js-paper-rank-work_68682203", }); 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$(".js-view-count[data-work-id=68682203]").text(description); $(".js-view-count-work_68682203").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_68682203").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="68682203"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="79384" rel="nofollow" href="https://www.academia.edu/Documents/in/Feature_matching">Feature matching</a>, <script data-card-contents-for-ri="79384" type="text/json">{"id":79384,"name":"Feature matching","url":"https://www.academia.edu/Documents/in/Feature_matching?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="160144" rel="nofollow" href="https://www.academia.edu/Documents/in/Feature_Extraction">Feature Extraction</a>, <script data-card-contents-for-ri="160144" type="text/json">{"id":160144,"name":"Feature Extraction","url":"https://www.academia.edu/Documents/in/Feature_Extraction?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="167397" rel="nofollow" href="https://www.academia.edu/Documents/in/Image_recognition">Image recognition</a>, <script data-card-contents-for-ri="167397" type="text/json">{"id":167397,"name":"Image recognition","url":"https://www.academia.edu/Documents/in/Image_recognition?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a><script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=68682203]'), work: {"id":68682203,"title":"Iris localization via intensity gradient and recognition through bit planes","created_at":"2022-01-19T05:47:24.781-08:00","url":"https://www.academia.edu/68682203/Iris_localization_via_intensity_gradient_and_recognition_through_bit_planes?f_ri=194916","dom_id":"work_68682203","summary":"Iris recognition is very hot topic in both research and practical applications. In this paper, a robust algorithm is proposed for iris localization and a very simple method is employed for feature extraction. Iris localization is the key step in iris recognition systems because all subsequent steps depend highly on its accuracy. The proposed algorithm utilizes important property of gradient of intensity level in the greyscale images (after converting the images into greyscale if not). Then iris is normalized into a dimensionless rectangular strip of size 128*512 pixels and different features are extracted based upon bit plane slicing of the strip to get binary iris code. ROC curves are also drawn for different features. Matching decision is based on accumulative sum of bitwise XOR of different iris codes. Experiments show that proposed localization algorithm is very effective. Results have been tabulated by evaluating the developed algorithm with 1000 eye images and recognition accuracy has reached up to 99.6%.","downloadable_attachments":[{"id":79077751,"asset_id":68682203,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":96108414,"first_name":"abdul","last_name":"Basit","domain_name":"independent","page_name":"abdulBasit741","display_name":"abdul Basit","profile_url":"https://independent.academia.edu/abdulBasit741?f_ri=194916","photo":"https://0.academia-photos.com/96108414/21118066/20589589/s65_abdul.basit.jpg"}],"research_interests":[{"id":79384,"name":"Feature matching","url":"https://www.academia.edu/Documents/in/Feature_matching?f_ri=194916","nofollow":true},{"id":160144,"name":"Feature Extraction","url":"https://www.academia.edu/Documents/in/Feature_Extraction?f_ri=194916","nofollow":true},{"id":167397,"name":"Image recognition","url":"https://www.academia.edu/Documents/in/Image_recognition?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":871638,"name":"IRIS RECOGNITION","url":"https://www.academia.edu/Documents/in/IRIS_RECOGNITION?f_ri=194916"},{"id":2217833,"name":"Gradient methods","url":"https://www.academia.edu/Documents/in/Gradient_methods?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_63952242" data-work_id="63952242" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/63952242/Presentation_of_receiver_operating_characteristics_ROC_plots">Presentation of receiver-operating characteristics (ROC) plots</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest">characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine [Reviewl. Clin</div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/63952242" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="6ee3f1628e0637ca24d8a3aaafe42197" rel="nofollow" data-download="{"attachment_id":76205316,"asset_id":63952242,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/76205316/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="204618906" href="https://independent.academia.edu/ChristopheDepuydt">Christophe Depuydt</a><script data-card-contents-for-user="204618906" type="text/json">{"id":204618906,"first_name":"Christophe","last_name":"Depuydt","domain_name":"independent","page_name":"ChristopheDepuydt","display_name":"Christophe Depuydt","profile_url":"https://independent.academia.edu/ChristopheDepuydt?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_63952242 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="63952242"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 63952242, container: ".js-paper-rank-work_63952242", }); });</script></li><li class="js-percentile-work_63952242 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 63952242; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_63952242"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_63952242 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="63952242"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 63952242; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=63952242]").text(description); $(".js-view-count-work_63952242").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_63952242").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="63952242"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="41839" rel="nofollow" href="https://www.academia.edu/Documents/in/Clinical_Chemistry">Clinical Chemistry</a>, <script data-card-contents-for-ri="41839" type="text/json">{"id":41839,"name":"Clinical Chemistry","url":"https://www.academia.edu/Documents/in/Clinical_Chemistry?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="82978" rel="nofollow" href="https://www.academia.edu/Documents/in/Reactive_Oxygen_Species">Reactive Oxygen Species</a>, <script data-card-contents-for-ri="82978" type="text/json">{"id":82978,"name":"Reactive Oxygen Species","url":"https://www.academia.edu/Documents/in/Reactive_Oxygen_Species?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="84243" rel="nofollow" href="https://www.academia.edu/Documents/in/Medical_Biotechnology">Medical Biotechnology</a>, <script data-card-contents-for-ri="84243" type="text/json">{"id":84243,"name":"Medical Biotechnology","url":"https://www.academia.edu/Documents/in/Medical_Biotechnology?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a><script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=63952242]'), work: {"id":63952242,"title":"Presentation of receiver-operating characteristics (ROC) plots","created_at":"2021-12-13T01:25:51.246-08:00","url":"https://www.academia.edu/63952242/Presentation_of_receiver_operating_characteristics_ROC_plots?f_ri=194916","dom_id":"work_63952242","summary":"characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine [Reviewl. Clin","downloadable_attachments":[{"id":76205316,"asset_id":63952242,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":204618906,"first_name":"Christophe","last_name":"Depuydt","domain_name":"independent","page_name":"ChristopheDepuydt","display_name":"Christophe Depuydt","profile_url":"https://independent.academia.edu/ChristopheDepuydt?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":41839,"name":"Clinical Chemistry","url":"https://www.academia.edu/Documents/in/Clinical_Chemistry?f_ri=194916","nofollow":true},{"id":82978,"name":"Reactive Oxygen Species","url":"https://www.academia.edu/Documents/in/Reactive_Oxygen_Species?f_ri=194916","nofollow":true},{"id":84243,"name":"Medical Biotechnology","url":"https://www.academia.edu/Documents/in/Medical_Biotechnology?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916"},{"id":1924712,"name":"Interleukin","url":"https://www.academia.edu/Documents/in/Interleukin?f_ri=194916"},{"id":3789880,"name":"Medical biochemistry and metabolomics","url":"https://www.academia.edu/Documents/in/Medical_biochemistry_and_metabolomics?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_58636583" data-work_id="58636583" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/58636583/New_Measure_of_Insulin_Sensitivity_Predicts_Cardiovascular_Disease_Better_than_HOMA_Estimated_Insulin_Resistance">New Measure of Insulin Sensitivity Predicts Cardiovascular Disease Better than HOMA Estimated Insulin Resistance</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Context: Accurate assessment of insulin sensitivity may better identify individuals at increased risk of cardio-metabolic diseases. Objectives: To examine whether a combination of anthropometric, biochemical and imaging measures can... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_58636583" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Context: Accurate assessment of insulin sensitivity may better identify individuals at increased risk of cardio-metabolic diseases. Objectives: To examine whether a combination of anthropometric, biochemical and imaging measures can better estimate insulin sensitivity index (ISI) and provide improved prediction of cardio-metabolic risk, in comparison to HOMA-IR. Design and participants: Healthy male volunteers (96 Chinese, 80 Malay, 77 Indian), 21 to 40 years, body mass index 18230 kg/m 2. Predicted ISI (ISI-cal) was generated using 45 randomly selected Chinese through stepwise multiple linear regression, and validated in the rest using non-parametric correlation (Kendall's tau t). In an independent longitudinal cohort, ISI-cal and HOMA-IR were compared for prediction of diabetes and cardiovascular disease (CVD), using ROC curves. Setting: The study was conducted in a university academic medical centre. Outcome measures: ISI measured by hyperinsulinemic euglycemic glucose clamp, along with anthropometric measurements, biochemical assessment and imaging; incident diabetes and CVD. Results: A combination of fasting insulin, serum triglycerides and waist-to-hip ratio (WHR) provided the best estimate of clamp-derived ISI (adjusted R 2 0.58 versus 0.32 HOMA-IR). In an independent cohort, ROC areas under the curve were 0.7760.02 ISI-cal versus 0.7660.02 HOMA-IR (p.0.05) for incident diabetes, and 0.7460.03 ISI-cal versus 0.6160.03 HOMA-IR (p,0.001) for incident CVD. ISI-cal also had greater sensitivity than defined metabolic syndrome in predicting CVD, with a four-fold increase in the risk of CVD independent of metabolic syndrome. Conclusions: Triglycerides and WHR, combined with fasting insulin levels, provide a better estimate of current insulin resistance state and improved identification of individuals with future risk of CVD, compared to HOMA-IR. This may be useful for estimating insulin sensitivity and cardio-metabolic risk in clinical and epidemiological settings.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/58636583" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ed4cc1f3c6d68868c5e8b2392ea31368" rel="nofollow" data-download="{"attachment_id":72950756,"asset_id":58636583,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/72950756/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="830600" href="https://nanyang.academia.edu/VitaliZagorodnov">Vitali Zagorodnov</a><script data-card-contents-for-user="830600" type="text/json">{"id":830600,"first_name":"Vitali","last_name":"Zagorodnov","domain_name":"nanyang","page_name":"VitaliZagorodnov","display_name":"Vitali Zagorodnov","profile_url":"https://nanyang.academia.edu/VitaliZagorodnov?f_ri=194916","photo":"https://0.academia-photos.com/830600/290395/343534/s65_vitali.zagorodnov.jpg"}</script></span></span></li><li class="js-paper-rank-work_58636583 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="58636583"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 58636583, container: ".js-paper-rank-work_58636583", }); 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$(".js-view-count[data-work-id=58636583]").text(description); $(".js-view-count-work_58636583").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_58636583").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="58636583"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">11</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="5018" rel="nofollow" href="https://www.academia.edu/Documents/in/Anthropometry">Anthropometry</a>, <script data-card-contents-for-ri="5018" type="text/json">{"id":5018,"name":"Anthropometry","url":"https://www.academia.edu/Documents/in/Anthropometry?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="16664" rel="nofollow" href="https://www.academia.edu/Documents/in/Risk_assessment">Risk assessment</a>, <script data-card-contents-for-ri="16664" type="text/json">{"id":16664,"name":"Risk assessment","url":"https://www.academia.edu/Documents/in/Risk_assessment?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="28235" rel="nofollow" href="https://www.academia.edu/Documents/in/Multidisciplinary">Multidisciplinary</a>, <script data-card-contents-for-ri="28235" type="text/json">{"id":28235,"name":"Multidisciplinary","url":"https://www.academia.edu/Documents/in/Multidisciplinary?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="28850" rel="nofollow" href="https://www.academia.edu/Documents/in/Linear_models">Linear models</a><script data-card-contents-for-ri="28850" type="text/json">{"id":28850,"name":"Linear models","url":"https://www.academia.edu/Documents/in/Linear_models?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=58636583]'), work: {"id":58636583,"title":"New Measure of Insulin Sensitivity Predicts Cardiovascular Disease Better than HOMA Estimated Insulin Resistance","created_at":"2021-10-17T11:21:28.583-07:00","url":"https://www.academia.edu/58636583/New_Measure_of_Insulin_Sensitivity_Predicts_Cardiovascular_Disease_Better_than_HOMA_Estimated_Insulin_Resistance?f_ri=194916","dom_id":"work_58636583","summary":"Context: Accurate assessment of insulin sensitivity may better identify individuals at increased risk of cardio-metabolic diseases. Objectives: To examine whether a combination of anthropometric, biochemical and imaging measures can better estimate insulin sensitivity index (ISI) and provide improved prediction of cardio-metabolic risk, in comparison to HOMA-IR. Design and participants: Healthy male volunteers (96 Chinese, 80 Malay, 77 Indian), 21 to 40 years, body mass index 18230 kg/m 2. Predicted ISI (ISI-cal) was generated using 45 randomly selected Chinese through stepwise multiple linear regression, and validated in the rest using non-parametric correlation (Kendall's tau t). In an independent longitudinal cohort, ISI-cal and HOMA-IR were compared for prediction of diabetes and cardiovascular disease (CVD), using ROC curves. Setting: The study was conducted in a university academic medical centre. Outcome measures: ISI measured by hyperinsulinemic euglycemic glucose clamp, along with anthropometric measurements, biochemical assessment and imaging; incident diabetes and CVD. Results: A combination of fasting insulin, serum triglycerides and waist-to-hip ratio (WHR) provided the best estimate of clamp-derived ISI (adjusted R 2 0.58 versus 0.32 HOMA-IR). In an independent cohort, ROC areas under the curve were 0.7760.02 ISI-cal versus 0.7660.02 HOMA-IR (p.0.05) for incident diabetes, and 0.7460.03 ISI-cal versus 0.6160.03 HOMA-IR (p,0.001) for incident CVD. ISI-cal also had greater sensitivity than defined metabolic syndrome in predicting CVD, with a four-fold increase in the risk of CVD independent of metabolic syndrome. Conclusions: Triglycerides and WHR, combined with fasting insulin levels, provide a better estimate of current insulin resistance state and improved identification of individuals with future risk of CVD, compared to HOMA-IR. This may be useful for estimating insulin sensitivity and cardio-metabolic risk in clinical and epidemiological settings.","downloadable_attachments":[{"id":72950756,"asset_id":58636583,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":830600,"first_name":"Vitali","last_name":"Zagorodnov","domain_name":"nanyang","page_name":"VitaliZagorodnov","display_name":"Vitali Zagorodnov","profile_url":"https://nanyang.academia.edu/VitaliZagorodnov?f_ri=194916","photo":"https://0.academia-photos.com/830600/290395/343534/s65_vitali.zagorodnov.jpg"}],"research_interests":[{"id":5018,"name":"Anthropometry","url":"https://www.academia.edu/Documents/in/Anthropometry?f_ri=194916","nofollow":true},{"id":16664,"name":"Risk assessment","url":"https://www.academia.edu/Documents/in/Risk_assessment?f_ri=194916","nofollow":true},{"id":28235,"name":"Multidisciplinary","url":"https://www.academia.edu/Documents/in/Multidisciplinary?f_ri=194916","nofollow":true},{"id":28850,"name":"Linear models","url":"https://www.academia.edu/Documents/in/Linear_models?f_ri=194916","nofollow":true},{"id":51373,"name":"Insulin Resistance","url":"https://www.academia.edu/Documents/in/Insulin_Resistance?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":220780,"name":"PLoS one","url":"https://www.academia.edu/Documents/in/PLoS_one?f_ri=194916"},{"id":330953,"name":"Longitudinal Studies","url":"https://www.academia.edu/Documents/in/Longitudinal_Studies?f_ri=194916"},{"id":559242,"name":"Cardiovascular Diseases","url":"https://www.academia.edu/Documents/in/Cardiovascular_Diseases?f_ri=194916"},{"id":622589,"name":"Risk Assessment","url":"https://www.academia.edu/Documents/in/Risk_Assessment-2?f_ri=194916"},{"id":1819400,"name":"Cohort Studies","url":"https://www.academia.edu/Documents/in/Cohort_Studies?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_8370438" data-work_id="8370438" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/8370438/Objective_Quantification_of_Posterior_Capsule_Opacification_after_Cataract_Surgery_with_Optical_Coherence_Tomography">Objective Quantification of Posterior Capsule Opacification after Cataract Surgery, with Optical Coherence Tomography</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">To evaluate posterior capsule opacification (PCO) in humans after cataract surgery with intraocular lens (IOL) implantation, by using optical coherence tomography (OCT-1). METHODS. Sixty-six eyes with PCO and 20 eyes with a normal... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_8370438" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">To evaluate posterior capsule opacification (PCO) in humans after cataract surgery with intraocular lens (IOL) implantation, by using optical coherence tomography (OCT-1). METHODS. Sixty-six eyes with PCO and 20 eyes with a normal posterior capsule were analyzed. A 3-mm-long horizontal scan of the posterior capsule was obtained. Measurements at three points and their average were recorded. Intraoperator and interoperator reliabilities were assessed. Investigated was peak intensity (PI) and posterior capsule thickening (PCT), with PCT indicating the distance between two reflectivity spikes, with an approximate axial resolution of 10 m. Results were compared with visual acuity (VA) and PCO type. RESULTS. Intraoperator reliability was 0.59 and 0.97 for average PI and PCT, respectively. The interoperator concordance correlation coefficient was 0.70 and 0.82 for average PI and PCT, respectively. Median (interquartile range) intensities of the reflectivity spike were 16.88 (dB) (range, 12.88 -20.41) and 11.9 (8.58 -14.28), respectively, in the PCO and control eyes (P ϭ 0.001). PCT was found in PCO eyes (median: 86.13 m; range, 46.33-115.33), whereas no second spike appeared in control eyes (P ϭ 0.001). The area under the receiver operating characteristic curve of the average PCT for differentiating pearl-type from fibrosis-type PCO was 0.87 (P ϭ 0.001). For a cutoff point of 55.3 m, the sensitivity was 97.5%, and the specificity was 69%. Worse VA correlated significantly only with larger PCT (r o ϭ 0.66; P ϭ 0.01).</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/8370438" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="e24af85e937d53e1952ab251746a16e9" rel="nofollow" data-download="{"attachment_id":34770274,"asset_id":8370438,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/34770274/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="16830125" href="https://independent.academia.edu/AuroraAlvarez3">Aurora Alvarez</a><script data-card-contents-for-user="16830125" type="text/json">{"id":16830125,"first_name":"Aurora","last_name":"Alvarez","domain_name":"independent","page_name":"AuroraAlvarez3","display_name":"Aurora Alvarez","profile_url":"https://independent.academia.edu/AuroraAlvarez3?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_8370438 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="8370438"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 8370438, container: ".js-paper-rank-work_8370438", }); 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METHODS. Sixty-six eyes with PCO and 20 eyes with a normal posterior capsule were analyzed. A 3-mm-long horizontal scan of the posterior capsule was obtained. Measurements at three points and their average were recorded. Intraoperator and interoperator reliabilities were assessed. Investigated was peak intensity (PI) and posterior capsule thickening (PCT), with PCT indicating the distance between two reflectivity spikes, with an approximate axial resolution of 10 m. Results were compared with visual acuity (VA) and PCO type. RESULTS. Intraoperator reliability was 0.59 and 0.97 for average PI and PCT, respectively. The interoperator concordance correlation coefficient was 0.70 and 0.82 for average PI and PCT, respectively. Median (interquartile range) intensities of the reflectivity spike were 16.88 (dB) (range, 12.88 -20.41) and 11.9 (8.58 -14.28), respectively, in the PCO and control eyes (P ϭ 0.001). PCT was found in PCO eyes (median: 86.13 m; range, 46.33-115.33), whereas no second spike appeared in control eyes (P ϭ 0.001). The area under the receiver operating characteristic curve of the average PCT for differentiating pearl-type from fibrosis-type PCO was 0.87 (P ϭ 0.001). For a cutoff point of 55.3 m, the sensitivity was 97.5%, and the specificity was 69%. Worse VA correlated significantly only with larger PCT (r o ϭ 0.66; P ϭ 0.01).","downloadable_attachments":[{"id":34770274,"asset_id":8370438,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":16830125,"first_name":"Aurora","last_name":"Alvarez","domain_name":"independent","page_name":"AuroraAlvarez3","display_name":"Aurora Alvarez","profile_url":"https://independent.academia.edu/AuroraAlvarez3?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":17302,"name":"Optical coherence tomography","url":"https://www.academia.edu/Documents/in/Optical_coherence_tomography?f_ri=194916","nofollow":true},{"id":22506,"name":"Adolescent","url":"https://www.academia.edu/Documents/in/Adolescent?f_ri=194916","nofollow":true},{"id":40271,"name":"Visual acuity","url":"https://www.academia.edu/Documents/in/Visual_acuity?f_ri=194916","nofollow":true},{"id":47884,"name":"Biological 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ipsilateral breast tumor recurrence (IBTR) after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The aim of our study was to evaluate a published nomogram from... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_21723252" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Prediction of patients at highest risk for ipsilateral breast tumor recurrence (IBTR) after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The aim of our study was to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center to predict for risk of IBTR in patients with DCIS from our institution.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/21723252" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="b76f951a039d62488b1575699f9ad0d9" rel="nofollow" data-download="{"attachment_id":42485732,"asset_id":21723252,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/42485732/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="42911540" href="https://independent.academia.edu/HughCarmalt">Hugh Carmalt</a><script data-card-contents-for-user="42911540" type="text/json">{"id":42911540,"first_name":"Hugh","last_name":"Carmalt","domain_name":"independent","page_name":"HughCarmalt","display_name":"Hugh Carmalt","profile_url":"https://independent.academia.edu/HughCarmalt?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_21723252 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="21723252"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 21723252, container: ".js-paper-rank-work_21723252", }); });</script></li><li class="js-percentile-work_21723252 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 21723252; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_21723252"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_21723252 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="21723252"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 21723252; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=21723252]").text(description); $(".js-view-count-work_21723252").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_21723252").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="21723252"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">16</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="6802" rel="nofollow" href="https://www.academia.edu/Documents/in/Breast_Cancer">Breast Cancer</a>, <script data-card-contents-for-ri="6802" type="text/json">{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="16664" rel="nofollow" href="https://www.academia.edu/Documents/in/Risk_assessment">Risk assessment</a>, <script data-card-contents-for-ri="16664" type="text/json">{"id":16664,"name":"Risk assessment","url":"https://www.academia.edu/Documents/in/Risk_assessment?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="33069" rel="nofollow" href="https://www.academia.edu/Documents/in/Probability">Probability</a>, <script data-card-contents-for-ri="33069" type="text/json">{"id":33069,"name":"Probability","url":"https://www.academia.edu/Documents/in/Probability?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="115895" rel="nofollow" href="https://www.academia.edu/Documents/in/Clinical_oncology">Clinical oncology</a><script data-card-contents-for-ri="115895" type="text/json">{"id":115895,"name":"Clinical oncology","url":"https://www.academia.edu/Documents/in/Clinical_oncology?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=21723252]'), work: {"id":21723252,"title":"Evaluation of a breast cancer nomogram for prediction of non-sentinel lymph node positivity","created_at":"2016-02-09T03:10:14.118-08:00","url":"https://www.academia.edu/21723252/Evaluation_of_a_breast_cancer_nomogram_for_prediction_of_non_sentinel_lymph_node_positivity?f_ri=194916","dom_id":"work_21723252","summary":"Prediction of patients at highest risk for ipsilateral breast tumor recurrence (IBTR) after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The aim of our study was to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center to predict for risk of IBTR in patients with DCIS from our institution.","downloadable_attachments":[{"id":42485732,"asset_id":21723252,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":42911540,"first_name":"Hugh","last_name":"Carmalt","domain_name":"independent","page_name":"HughCarmalt","display_name":"Hugh Carmalt","profile_url":"https://independent.academia.edu/HughCarmalt?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer?f_ri=194916","nofollow":true},{"id":16664,"name":"Risk assessment","url":"https://www.academia.edu/Documents/in/Risk_assessment?f_ri=194916","nofollow":true},{"id":33069,"name":"Probability","url":"https://www.academia.edu/Documents/in/Probability?f_ri=194916","nofollow":true},{"id":115895,"name":"Clinical oncology","url":"https://www.academia.edu/Documents/in/Clinical_oncology?f_ri=194916","nofollow":true},{"id":133057,"name":"Young Adult","url":"https://www.academia.edu/Documents/in/Young_Adult?f_ri=194916"},{"id":137516,"name":"Follow-up studies","url":"https://www.academia.edu/Documents/in/Follow-up_studies?f_ri=194916"},{"id":174502,"name":"Incidence","url":"https://www.academia.edu/Documents/in/Incidence?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916"},{"id":448603,"name":"Necrosis","url":"https://www.academia.edu/Documents/in/Necrosis?f_ri=194916"},{"id":469105,"name":"Retrospective Studies","url":"https://www.academia.edu/Documents/in/Retrospective_Studies?f_ri=194916"},{"id":622589,"name":"Risk Assessment","url":"https://www.academia.edu/Documents/in/Risk_Assessment-2?f_ri=194916"},{"id":884014,"name":"Chemoradiotherapy","url":"https://www.academia.edu/Documents/in/Chemoradiotherapy?f_ri=194916"},{"id":1309706,"name":"Area Under Curve","url":"https://www.academia.edu/Documents/in/Area_Under_Curve?f_ri=194916"},{"id":1363315,"name":"Axilla","url":"https://www.academia.edu/Documents/in/Axilla?f_ri=194916"},{"id":1730405,"name":"Nomogram","url":"https://www.academia.edu/Documents/in/Nomogram?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_18902508" data-work_id="18902508" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/18902508/Recognition_of_goblet_cells_upon_endocytoscopy_indicates_the_presence_of_gastric_intestinal_metaplasia">Recognition of goblet cells upon endocytoscopy indicates the presence of gastric intestinal metaplasia</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Background: Gastric intestinal metaplasia (IM) is considered precancerous and is difficult to differentiate upon endoscopy. Endocytoscopy enables observation at a cellular level for focused biopsy. The present study examined the use of... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_18902508" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Background: Gastric intestinal metaplasia (IM) is considered precancerous and is difficult to differentiate upon endoscopy. Endocytoscopy enables observation at a cellular level for focused biopsy. The present study examined the use of endocytoscopy for recognition of gastric IM.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/18902508" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8a3d5927e276bf3d161a0ec07ed52962" rel="nofollow" data-download="{"attachment_id":40319798,"asset_id":18902508,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/40319798/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="39027201" href="https://cuhk.academia.edu/AnthonyTeoh">Anthony Teoh</a><script data-card-contents-for-user="39027201" type="text/json">{"id":39027201,"first_name":"Anthony","last_name":"Teoh","domain_name":"cuhk","page_name":"AnthonyTeoh","display_name":"Anthony Teoh","profile_url":"https://cuhk.academia.edu/AnthonyTeoh?f_ri=194916","photo":"https://0.academia-photos.com/39027201/17783796/17808546/s65_anthony.teoh.jpg"}</script></span></span></li><li class="js-paper-rank-work_18902508 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="18902508"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 18902508, container: ".js-paper-rank-work_18902508", }); });</script></li><li class="js-percentile-work_18902508 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 18902508; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_18902508"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_18902508 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="18902508"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 18902508; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=18902508]").text(description); $(".js-view-count-work_18902508").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_18902508").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="18902508"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">9</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="62112" rel="nofollow" href="https://www.academia.edu/Documents/in/Prospective_studies">Prospective studies</a>, <script data-card-contents-for-ri="62112" type="text/json">{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="71471" rel="nofollow" href="https://www.academia.edu/Documents/in/Intestinal_Mucosa">Intestinal Mucosa</a>, <script data-card-contents-for-ri="71471" type="text/json">{"id":71471,"name":"Intestinal Mucosa","url":"https://www.academia.edu/Documents/in/Intestinal_Mucosa?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a>, <script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="244814" rel="nofollow" href="https://www.academia.edu/Documents/in/Clinical_Sciences">Clinical Sciences</a><script data-card-contents-for-ri="244814" type="text/json">{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=18902508]'), work: {"id":18902508,"title":"Recognition of goblet cells upon endocytoscopy indicates the presence of gastric intestinal metaplasia","created_at":"2015-11-23T23:25:58.042-08:00","url":"https://www.academia.edu/18902508/Recognition_of_goblet_cells_upon_endocytoscopy_indicates_the_presence_of_gastric_intestinal_metaplasia?f_ri=194916","dom_id":"work_18902508","summary":"Background: Gastric intestinal metaplasia (IM) is considered precancerous and is difficult to differentiate upon endoscopy. Endocytoscopy enables observation at a cellular level for focused biopsy. The present study examined the use of endocytoscopy for recognition of gastric IM.","downloadable_attachments":[{"id":40319798,"asset_id":18902508,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":39027201,"first_name":"Anthony","last_name":"Teoh","domain_name":"cuhk","page_name":"AnthonyTeoh","display_name":"Anthony Teoh","profile_url":"https://cuhk.academia.edu/AnthonyTeoh?f_ri=194916","photo":"https://0.academia-photos.com/39027201/17783796/17808546/s65_anthony.teoh.jpg"}],"research_interests":[{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true},{"id":71471,"name":"Intestinal Mucosa","url":"https://www.academia.edu/Documents/in/Intestinal_Mucosa?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916","nofollow":true},{"id":343756,"name":"Gastrointestinal Endoscopy","url":"https://www.academia.edu/Documents/in/Gastrointestinal_Endoscopy?f_ri=194916"},{"id":375142,"name":"Precancerous Conditions","url":"https://www.academia.edu/Documents/in/Precancerous_Conditions?f_ri=194916"},{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916"},{"id":987927,"name":"Goblet Cells","url":"https://www.academia.edu/Documents/in/Goblet_Cells?f_ri=194916"},{"id":1757408,"name":"Digestive Endoscopy","url":"https://www.academia.edu/Documents/in/Digestive_Endoscopy?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_18267748 coauthored" data-work_id="18267748" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/18267748/A_cascade_classifier_applied_in_pedestrian_detection_using_laser_and_image_based_features">A cascade classifier applied in pedestrian detection using laser and image-based features</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this paper we present a multistage method applied in pedestrian detection using information from a LIDAR and a monocular-camera mounted on an electric vehicle driving in urban scenarios. The proposed method is a cascade of classifiers... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_18267748" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this paper we present a multistage method applied in pedestrian detection using information from a LIDAR and a monocular-camera mounted on an electric vehicle driving in urban scenarios. The proposed method is a cascade of classifiers trained in two subsets of features, one with laserbased features and the other with a set of image-based features. A specific training approach was developed to adjust the cascade stages in order to enhance the classification performance. The proposed method differs from the conventional cascade regarding the way the selected samples are propagated through the cascade. Thus, the subsequent stages of the proposed cascade receive both negatives and positives from previous ones, relying on a decision margin process. Experiments were conducted in off-line mode, for a set of single component classifiers and for the proposed cascade technique. The results are compared in terms of classification performance metrics and ROC curves.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/18267748" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="7c9887530018ba6bea6c07782af6e0fb" rel="nofollow" data-download="{"attachment_id":39964176,"asset_id":18267748,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/39964176/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="38250234" href="https://independent.academia.edu/UrbanoNunes">Urbano Nunes</a><script data-card-contents-for-user="38250234" type="text/json">{"id":38250234,"first_name":"Urbano","last_name":"Nunes","domain_name":"independent","page_name":"UrbanoNunes","display_name":"Urbano Nunes","profile_url":"https://independent.academia.edu/UrbanoNunes?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-18267748">+2</span><div class="hidden js-additional-users-18267748"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://kuleuven.academia.edu/OswaldoLudwig">Oswaldo Ludwig</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://uc-pt.academia.edu/CristianoPremebida">Cristiano Premebida</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-18267748'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-18267748').html(); 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container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_18267748 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="18267748"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 18267748; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=18267748]").text(description); $(".js-view-count-work_18267748").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_18267748").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="18267748"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a>, <script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="257081" rel="nofollow" href="https://www.academia.edu/Documents/in/Electric_Vehicle">Electric Vehicle</a>, <script data-card-contents-for-ri="257081" type="text/json">{"id":257081,"name":"Electric Vehicle","url":"https://www.academia.edu/Documents/in/Electric_Vehicle?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="904133" rel="nofollow" href="https://www.academia.edu/Documents/in/Pedestrian_Detection">Pedestrian Detection</a><script data-card-contents-for-ri="904133" type="text/json">{"id":904133,"name":"Pedestrian Detection","url":"https://www.academia.edu/Documents/in/Pedestrian_Detection?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=18267748]'), work: {"id":18267748,"title":"A cascade classifier applied in pedestrian detection using laser and image-based features","created_at":"2015-11-13T02:23:00.230-08:00","url":"https://www.academia.edu/18267748/A_cascade_classifier_applied_in_pedestrian_detection_using_laser_and_image_based_features?f_ri=194916","dom_id":"work_18267748","summary":"In this paper we present a multistage method applied in pedestrian detection using information from a LIDAR and a monocular-camera mounted on an electric vehicle driving in urban scenarios. The proposed method is a cascade of classifiers trained in two subsets of features, one with laserbased features and the other with a set of image-based features. A specific training approach was developed to adjust the cascade stages in order to enhance the classification performance. The proposed method differs from the conventional cascade regarding the way the selected samples are propagated through the cascade. Thus, the subsequent stages of the proposed cascade receive both negatives and positives from previous ones, relying on a decision margin process. Experiments were conducted in off-line mode, for a set of single component classifiers and for the proposed cascade technique. The results are compared in terms of classification performance metrics and ROC curves.","downloadable_attachments":[{"id":39964176,"asset_id":18267748,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":38250234,"first_name":"Urbano","last_name":"Nunes","domain_name":"independent","page_name":"UrbanoNunes","display_name":"Urbano Nunes","profile_url":"https://independent.academia.edu/UrbanoNunes?f_ri=194916","photo":"/images/s65_no_pic.png"},{"id":34525508,"first_name":"Oswaldo","last_name":"Ludwig","domain_name":"kuleuven","page_name":"OswaldoLudwig","display_name":"Oswaldo Ludwig","profile_url":"https://kuleuven.academia.edu/OswaldoLudwig?f_ri=194916","photo":"https://0.academia-photos.com/34525508/10092602/164003807/s65_oswaldo.ludwig.jpg"},{"id":34532219,"first_name":"Cristiano","last_name":"Premebida","domain_name":"uc-pt","page_name":"CristianoPremebida","display_name":"Cristiano Premebida","profile_url":"https://uc-pt.academia.edu/CristianoPremebida?f_ri=194916","photo":"https://0.academia-photos.com/34532219/12722414/14150574/s65_cristiano.premebida.png"}],"research_interests":[{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":257081,"name":"Electric Vehicle","url":"https://www.academia.edu/Documents/in/Electric_Vehicle?f_ri=194916","nofollow":true},{"id":904133,"name":"Pedestrian Detection","url":"https://www.academia.edu/Documents/in/Pedestrian_Detection?f_ri=194916","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_32366719" data-work_id="32366719" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/32366719/Evaluation_of_diagnostic_scales_for_appendicitis_in_patients_with_abdominal_pain">Evaluation of diagnostic scales for appendicitis in patients with abdominal pain</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Introducción. El diagnóstico de apendicitis es difícil y existen algunas escalas que pretenden mejorar la exactitud diagnóstica. Objetivo. Determinar las características operativas de las escalas de Alvarado y Fenyö, comparándolas con la... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_32366719" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Introducción. El diagnóstico de apendicitis es difícil y existen algunas escalas que pretenden mejorar la exactitud diagnóstica. Objetivo. Determinar las características operativas de las escalas de Alvarado y Fenyö, comparándolas con la impresión diagnóstica del cirujano y la patología en el dolor abdominal sugestivo de apendicitis. Materiales y métodos. Se trata de un estudio prospectivo de evaluación de pruebas diagnósticas. Se registraron los signos, síntomas y resultados de exámenes de laboratorio incluidos en las escalas. Se registró de manera ciega el diagnóstico del cirujano y su conducta. Se determinó la sensibilidad, especificidad, valores diagnósticos positivos y negativos, y likelihood ratio (índice de verosimilitud) de cada escala y del cirujano, discriminado por sexo. Resultados. Se analizaron 374 sujetos, sin diferencias estadísticamente significativas de variables entre sexos. Se operaron 269 pacientes. El 16,9% de los hombres y el 31,4% de las mujeres no tuvieron apendicitis. Para los hombres, la sensibilidad del diagnóstico por el cirujano fue mayor que las escalas (86,2% Vs. 73% en Alvarado Vs. 67,2% en Fenyö) con una especificidad similar. Para las mujeres la sensibilidad del cirujano y la escala de Alvarado fueron similares y superiores a la de Fenyö (77,1% Vs. 79,5% en Alvarado y 47% en Fenyö) pero la especificidad fue superior para Fenyö (92,9% Vs. 71,4% en Alvarado y 75,9% en cirujano). La frecuencia de apendicitis crece de manera proporcional al puntaje de Alvarado. Conclusión. Para hombres con dolor en la fosa iliaca derecha, el diagnóstico hecho por el cirujano es mejor que las escalas diagnósticas. Para el caso de las mujeres, la escala de Fenyö ofrece una mejor sensibilidad. La escala de Alvarado puede facilitar la conducta en pacientes con dolor en fosa iliaca derecha.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/32366719" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="521c7cb0aa31f6545aacb4d4e7579109" rel="nofollow" data-download="{"attachment_id":52571388,"asset_id":32366719,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/52571388/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="33204076" href="https://antioquia.academia.edu/AlvaroSanabria">Alvaro Sanabria</a><script data-card-contents-for-user="33204076" type="text/json">{"id":33204076,"first_name":"Alvaro","last_name":"Sanabria","domain_name":"antioquia","page_name":"AlvaroSanabria","display_name":"Alvaro Sanabria","profile_url":"https://antioquia.academia.edu/AlvaroSanabria?f_ri=194916","photo":"https://0.academia-photos.com/33204076/114643036/103923277/s65_alvaro.sanabria.jpeg"}</script></span></span></li><li class="js-paper-rank-work_32366719 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="32366719"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 32366719, container: ".js-paper-rank-work_32366719", }); });</script></li><li class="js-percentile-work_32366719 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 32366719; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_32366719"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_32366719 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="32366719"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 32366719; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=32366719]").text(description); $(".js-view-count-work_32366719").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_32366719").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="32366719"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="62112" rel="nofollow" href="https://www.academia.edu/Documents/in/Prospective_studies">Prospective studies</a>, <script data-card-contents-for-ri="62112" type="text/json">{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a>, <script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="549280" rel="nofollow" href="https://www.academia.edu/Documents/in/Reproducibility_of_Results">Reproducibility of Results</a>, <script data-card-contents-for-ri="549280" type="text/json">{"id":549280,"name":"Reproducibility of Results","url":"https://www.academia.edu/Documents/in/Reproducibility_of_Results?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="901876" rel="nofollow" href="https://www.academia.edu/Documents/in/Sensitivity_and_Specificity">Sensitivity and Specificity</a><script data-card-contents-for-ri="901876" type="text/json">{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=32366719]'), work: {"id":32366719,"title":"Evaluation of diagnostic scales for appendicitis in patients with abdominal pain","created_at":"2017-04-10T09:50:40.005-07:00","url":"https://www.academia.edu/32366719/Evaluation_of_diagnostic_scales_for_appendicitis_in_patients_with_abdominal_pain?f_ri=194916","dom_id":"work_32366719","summary":"Introducción. El diagnóstico de apendicitis es difícil y existen algunas escalas que pretenden mejorar la exactitud diagnóstica. Objetivo. Determinar las características operativas de las escalas de Alvarado y Fenyö, comparándolas con la impresión diagnóstica del cirujano y la patología en el dolor abdominal sugestivo de apendicitis. Materiales y métodos. Se trata de un estudio prospectivo de evaluación de pruebas diagnósticas. Se registraron los signos, síntomas y resultados de exámenes de laboratorio incluidos en las escalas. Se registró de manera ciega el diagnóstico del cirujano y su conducta. Se determinó la sensibilidad, especificidad, valores diagnósticos positivos y negativos, y likelihood ratio (índice de verosimilitud) de cada escala y del cirujano, discriminado por sexo. Resultados. Se analizaron 374 sujetos, sin diferencias estadísticamente significativas de variables entre sexos. Se operaron 269 pacientes. El 16,9% de los hombres y el 31,4% de las mujeres no tuvieron apendicitis. Para los hombres, la sensibilidad del diagnóstico por el cirujano fue mayor que las escalas (86,2% Vs. 73% en Alvarado Vs. 67,2% en Fenyö) con una especificidad similar. Para las mujeres la sensibilidad del cirujano y la escala de Alvarado fueron similares y superiores a la de Fenyö (77,1% Vs. 79,5% en Alvarado y 47% en Fenyö) pero la especificidad fue superior para Fenyö (92,9% Vs. 71,4% en Alvarado y 75,9% en cirujano). La frecuencia de apendicitis crece de manera proporcional al puntaje de Alvarado. Conclusión. Para hombres con dolor en la fosa iliaca derecha, el diagnóstico hecho por el cirujano es mejor que las escalas diagnósticas. Para el caso de las mujeres, la escala de Fenyö ofrece una mejor sensibilidad. La escala de Alvarado puede facilitar la conducta en pacientes con dolor en fosa iliaca derecha.","downloadable_attachments":[{"id":52571388,"asset_id":32366719,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33204076,"first_name":"Alvaro","last_name":"Sanabria","domain_name":"antioquia","page_name":"AlvaroSanabria","display_name":"Alvaro Sanabria","profile_url":"https://antioquia.academia.edu/AlvaroSanabria?f_ri=194916","photo":"https://0.academia-photos.com/33204076/114643036/103923277/s65_alvaro.sanabria.jpeg"}],"research_interests":[{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":549280,"name":"Reproducibility of Results","url":"https://www.academia.edu/Documents/in/Reproducibility_of_Results?f_ri=194916","nofollow":true},{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916","nofollow":true},{"id":1180715,"name":"Abdominal Pain","url":"https://www.academia.edu/Documents/in/Abdominal_Pain?f_ri=194916"},{"id":1259531,"name":"Acute Appendicitis","url":"https://www.academia.edu/Documents/in/Acute_Appendicitis?f_ri=194916"},{"id":1318932,"name":"Predictive value of tests","url":"https://www.academia.edu/Documents/in/Predictive_value_of_tests?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_47609884" data-work_id="47609884" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/47609884/Quantification_of_peripapillary_total_retinal_volume_in_pseudopapilledema_and_mild_papilledema_using_spectral_domain_optical_coherence_tomography">Quantification of peripapillary total retinal volume in pseudopapilledema and mild papilledema using spectral-domain optical coherence tomography</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest">PURPOSE: To distinguish differences in retinal nerve fiber layer (RNFL) thickness and peripapillary total retinal volume between eyes with papilledema, pseudopapilledema, and normal findings.</div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/47609884" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa 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itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="35512408" href="https://independent.academia.edu/PremSubramanian">Prem Subramanian</a><script data-card-contents-for-user="35512408" type="text/json">{"id":35512408,"first_name":"Prem","last_name":"Subramanian","domain_name":"independent","page_name":"PremSubramanian","display_name":"Prem Subramanian","profile_url":"https://independent.academia.edu/PremSubramanian?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_47609884 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="47609884"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 47609884, container: ".js-paper-rank-work_47609884", }); });</script></li><li class="js-percentile-work_47609884 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 47609884; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_47609884"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_47609884 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="47609884"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47609884; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=47609884]").text(description); $(".js-view-count-work_47609884").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_47609884").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="47609884"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">14</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="17302" rel="nofollow" href="https://www.academia.edu/Documents/in/Optical_coherence_tomography">Optical coherence tomography</a>, <script data-card-contents-for-ri="17302" type="text/json">{"id":17302,"name":"Optical coherence tomography","url":"https://www.academia.edu/Documents/in/Optical_coherence_tomography?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="40271" rel="nofollow" href="https://www.academia.edu/Documents/in/Visual_acuity">Visual acuity</a>, <script data-card-contents-for-ri="40271" type="text/json">{"id":40271,"name":"Visual acuity","url":"https://www.academia.edu/Documents/in/Visual_acuity?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="117200" rel="nofollow" href="https://www.academia.edu/Documents/in/Retina">Retina</a>, <script data-card-contents-for-ri="117200" type="text/json">{"id":117200,"name":"Retina","url":"https://www.academia.edu/Documents/in/Retina?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="121320" rel="nofollow" href="https://www.academia.edu/Documents/in/Intraocular_Pressure">Intraocular Pressure</a><script data-card-contents-for-ri="121320" type="text/json">{"id":121320,"name":"Intraocular Pressure","url":"https://www.academia.edu/Documents/in/Intraocular_Pressure?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=47609884]'), work: {"id":47609884,"title":"Quantification of peripapillary total retinal volume in pseudopapilledema and mild papilledema using spectral-domain optical coherence tomography","created_at":"2021-04-23T08:50:49.374-07:00","url":"https://www.academia.edu/47609884/Quantification_of_peripapillary_total_retinal_volume_in_pseudopapilledema_and_mild_papilledema_using_spectral_domain_optical_coherence_tomography?f_ri=194916","dom_id":"work_47609884","summary":"PURPOSE: To distinguish differences in retinal nerve fiber layer (RNFL) thickness and peripapillary total retinal volume between eyes with papilledema, pseudopapilledema, and normal findings.","downloadable_attachments":[{"id":66614677,"asset_id":47609884,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":35512408,"first_name":"Prem","last_name":"Subramanian","domain_name":"independent","page_name":"PremSubramanian","display_name":"Prem Subramanian","profile_url":"https://independent.academia.edu/PremSubramanian?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":17302,"name":"Optical coherence tomography","url":"https://www.academia.edu/Documents/in/Optical_coherence_tomography?f_ri=194916","nofollow":true},{"id":40271,"name":"Visual acuity","url":"https://www.academia.edu/Documents/in/Visual_acuity?f_ri=194916","nofollow":true},{"id":117200,"name":"Retina","url":"https://www.academia.edu/Documents/in/Retina?f_ri=194916","nofollow":true},{"id":121320,"name":"Intraocular Pressure","url":"https://www.academia.edu/Documents/in/Intraocular_Pressure?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":359001,"name":"Optometry and Ophthalmology","url":"https://www.academia.edu/Documents/in/Optometry_and_Ophthalmology?f_ri=194916"},{"id":410370,"name":"Public health systems and services research","url":"https://www.academia.edu/Documents/in/Public_health_systems_and_services_research-1?f_ri=194916"},{"id":513105,"name":"Retinal Ganglion Cells","url":"https://www.academia.edu/Documents/in/Retinal_Ganglion_Cells?f_ri=194916"},{"id":557542,"name":"Optic Disk","url":"https://www.academia.edu/Documents/in/Optic_Disk?f_ri=194916"},{"id":563992,"name":"Visual Fields","url":"https://www.academia.edu/Documents/in/Visual_Fields?f_ri=194916"},{"id":1309706,"name":"Area Under Curve","url":"https://www.academia.edu/Documents/in/Area_Under_Curve?f_ri=194916"},{"id":1434562,"name":"Papilledema","url":"https://www.academia.edu/Documents/in/Papilledema?f_ri=194916"},{"id":1819400,"name":"Cohort Studies","url":"https://www.academia.edu/Documents/in/Cohort_Studies?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_34274506" data-work_id="34274506" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/34274506/Serum_Magnesium_Levels_and_Acute_Exacerbation_of_Chronic_Obstructive_Pulmonary_Disease_A_Retrospective_Study">Serum Magnesium Levels and Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Retrospective Study</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">A decrease in serum Mg +2 is associated with airway hyper-reactivity and impaired pulmonary function. The purpose of this study was to determine if decreased serum Mg +2 levels in patients with chronic obstructive pulmonary disease (COPD)... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_34274506" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">A decrease in serum Mg +2 is associated with airway hyper-reactivity and impaired pulmonary function. The purpose of this study was to determine if decreased serum Mg +2 levels in patients with chronic obstructive pulmonary disease (COPD) are associated with acute exacerbations. In a retrospective study, the charted serum Mg +2 levels in 100 COPD patients were examined. These included 50 patients who presented with an acute exacerbation of COPD and 50 stable patients. Chart review was sequential within both groups. Serum Mg 2+ levels in the stable COPD patients averaged 0.91 ± 0.10 mmol/L (mean ± SD) with a 95% CI of 0.88 -0.94 mmol/L. Patients undergoing an exacerbation had significantly lower serum Mg +2 levels (0.77 ± 0.10 mmol/L; CI, 0.74 -0.79; p <0.0001). Logistic regression of the dichotomous outcomes as a function of serum Mg +2 concentration demonstrated a highly significant association (c 2 = 41.26; p <10 -5 ). These data were subjected to receiver-operator characteristic (ROC) analysis for decision levels (DL) and the area under the ROC curve was determined to be 0.85 ± 0.04 (CI, 0.78 -0.93). The optimum DL was determined to lie between 0.80 mmol/L (OR = 14.33; sensitivity 70%; specificity 86%) and 0.84 mmol/L (OR = 11.16; sensitivity 84%; specificity 68%). These data suggest that at the lower range of the reference interval, serum Mg +2 levels are associated with an increased risk of exacerbation of symptoms in COPD patients. Furthermore, they suggest a DL that is useful for predicting clinical outcomes in these patients and serving as a target value for therapy.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/34274506" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="0b9c9d3009eaea46f00f0602034621bd" rel="nofollow" data-download="{"attachment_id":54181667,"asset_id":34274506,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/54181667/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="67404381" href="https://independent.academia.edu/VincentDebari">Vincent Debari</a><script data-card-contents-for-user="67404381" type="text/json">{"id":67404381,"first_name":"Vincent","last_name":"Debari","domain_name":"independent","page_name":"VincentDebari","display_name":"Vincent Debari","profile_url":"https://independent.academia.edu/VincentDebari?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_34274506 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="34274506"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 34274506, container: ".js-paper-rank-work_34274506", }); });</script></li><li class="js-percentile-work_34274506 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 34274506; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_34274506"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_34274506 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="34274506"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 34274506; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=34274506]").text(description); $(".js-view-count-work_34274506").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_34274506").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="34274506"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">15</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="32433" rel="nofollow" href="https://www.academia.edu/Documents/in/Logistic_Regression">Logistic Regression</a>, <script data-card-contents-for-ri="32433" type="text/json">{"id":32433,"name":"Logistic Regression","url":"https://www.academia.edu/Documents/in/Logistic_Regression?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="70902" rel="nofollow" href="https://www.academia.edu/Documents/in/Magnesium">Magnesium</a>, <script data-card-contents-for-ri="70902" type="text/json">{"id":70902,"name":"Magnesium","url":"https://www.academia.edu/Documents/in/Magnesium?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="164831" rel="nofollow" href="https://www.academia.edu/Documents/in/Dyspnea">Dyspnea</a>, <script data-card-contents-for-ri="164831" type="text/json">{"id":164831,"name":"Dyspnea","url":"https://www.academia.edu/Documents/in/Dyspnea?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a><script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=34274506]'), work: {"id":34274506,"title":"Serum Magnesium Levels and Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Retrospective Study","created_at":"2017-08-19T05:12:22.322-07:00","url":"https://www.academia.edu/34274506/Serum_Magnesium_Levels_and_Acute_Exacerbation_of_Chronic_Obstructive_Pulmonary_Disease_A_Retrospective_Study?f_ri=194916","dom_id":"work_34274506","summary":"A decrease in serum Mg +2 is associated with airway hyper-reactivity and impaired pulmonary function. The purpose of this study was to determine if decreased serum Mg +2 levels in patients with chronic obstructive pulmonary disease (COPD) are associated with acute exacerbations. In a retrospective study, the charted serum Mg +2 levels in 100 COPD patients were examined. These included 50 patients who presented with an acute exacerbation of COPD and 50 stable patients. Chart review was sequential within both groups. Serum Mg 2+ levels in the stable COPD patients averaged 0.91 ± 0.10 mmol/L (mean ± SD) with a 95% CI of 0.88 -0.94 mmol/L. Patients undergoing an exacerbation had significantly lower serum Mg +2 levels (0.77 ± 0.10 mmol/L; CI, 0.74 -0.79; p \u003c0.0001). Logistic regression of the dichotomous outcomes as a function of serum Mg +2 concentration demonstrated a highly significant association (c 2 = 41.26; p \u003c10 -5 ). These data were subjected to receiver-operator characteristic (ROC) analysis for decision levels (DL) and the area under the ROC curve was determined to be 0.85 ± 0.04 (CI, 0.78 -0.93). The optimum DL was determined to lie between 0.80 mmol/L (OR = 14.33; sensitivity 70%; specificity 86%) and 0.84 mmol/L (OR = 11.16; sensitivity 84%; specificity 68%). These data suggest that at the lower range of the reference interval, serum Mg +2 levels are associated with an increased risk of exacerbation of symptoms in COPD patients. Furthermore, they suggest a DL that is useful for predicting clinical outcomes in these patients and serving as a target value for therapy.","downloadable_attachments":[{"id":54181667,"asset_id":34274506,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":67404381,"first_name":"Vincent","last_name":"Debari","domain_name":"independent","page_name":"VincentDebari","display_name":"Vincent Debari","profile_url":"https://independent.academia.edu/VincentDebari?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":32433,"name":"Logistic Regression","url":"https://www.academia.edu/Documents/in/Logistic_Regression?f_ri=194916","nofollow":true},{"id":70902,"name":"Magnesium","url":"https://www.academia.edu/Documents/in/Magnesium?f_ri=194916","nofollow":true},{"id":164831,"name":"Dyspnea","url":"https://www.academia.edu/Documents/in/Dyspnea?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916"},{"id":469105,"name":"Retrospective Studies","url":"https://www.academia.edu/Documents/in/Retrospective_Studies?f_ri=194916"},{"id":556576,"name":"Chronic obstructive pulmonary disease","url":"https://www.academia.edu/Documents/in/Chronic_obstructive_pulmonary_disease?f_ri=194916"},{"id":677189,"name":"Pulmonary Function","url":"https://www.academia.edu/Documents/in/Pulmonary_Function?f_ri=194916"},{"id":990198,"name":"Retrospective Study","url":"https://www.academia.edu/Documents/in/Retrospective_Study?f_ri=194916"},{"id":1000427,"name":"Reference Values","url":"https://www.academia.edu/Documents/in/Reference_Values?f_ri=194916"},{"id":1107101,"name":"Cough","url":"https://www.academia.edu/Documents/in/Cough?f_ri=194916"},{"id":1294607,"name":"Logistic Models","url":"https://www.academia.edu/Documents/in/Logistic_Models?f_ri=194916"},{"id":1309706,"name":"Area Under Curve","url":"https://www.academia.edu/Documents/in/Area_Under_Curve?f_ri=194916"},{"id":2651394,"name":"roc analysis","url":"https://www.academia.edu/Documents/in/roc_analysis?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_1405676" data-work_id="1405676" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/1405676/Prediction_of_Protein_Protein_Interactions_Using_Pairwise_Alignment_and_Inter_Domain_Linker_Region">Prediction of Protein-Protein Interactions Using Pairwise Alignment and Inter-Domain Linker Region</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">One of the central problems in modern biology is to identify the complete set of interactions among the proteins in a cell. The structural interaction of proteins and their domains in networks is one of the most basic molecular mechanisms... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_1405676" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">One of the central problems in modern biology is to identify the complete set of interactions among the proteins in a cell. The structural interaction of proteins and their domains in networks is one of the most basic molecular mechanisms for biological cells. Structural evidence indicates that, interacting pairs of close homologs usually interact in the same way. In this article, we make use of both homology and inter-domain linker region knowledge to predict interaction between protein pairs solely by amino acid sequence information. High quality core set of 150 yeast proteins obtained from the Database of Interacting Proteins (DIP) was considered to test the accuracy of the proposed method. The strongest prediction of the method reached over 70% accuracy. These results show great potential for the proposed method.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/1405676" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="26aff04c8fe989c3f819ea1947f7fec3" rel="nofollow" data-download="{"attachment_id":9403056,"asset_id":1405676,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/9403056/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="632008" href="https://uaeu.academia.edu/NazarZaki">Nazar Zaki</a><script data-card-contents-for-user="632008" type="text/json">{"id":632008,"first_name":"Nazar","last_name":"Zaki","domain_name":"uaeu","page_name":"NazarZaki","display_name":"Nazar Zaki","profile_url":"https://uaeu.academia.edu/NazarZaki?f_ri=194916","photo":"https://0.academia-photos.com/632008/218143/254830/s65_nazar.zaki.jpg"}</script></span></span></li><li class="js-paper-rank-work_1405676 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="1405676"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 1405676, container: ".js-paper-rank-work_1405676", }); 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The structural interaction of proteins and their domains in networks is one of the most basic molecular mechanisms for biological cells. Structural evidence indicates that, interacting pairs of close homologs usually interact in the same way. In this article, we make use of both homology and inter-domain linker region knowledge to predict interaction between protein pairs solely by amino acid sequence information. High quality core set of 150 yeast proteins obtained from the Database of Interacting Proteins (DIP) was considered to test the accuracy of the proposed method. The strongest prediction of the method reached over 70% accuracy. 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})();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_1586397" data-work_id="1586397" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/1586397/Comparison_of_Scoring_Systems_for_Invasive_Pests_Using_ROC_Analysis_and_Monte_Carlo_Simulations_Comparison_of_Scoring_Systems_for_Invasive_Pests_Using_ROC_Analysis_and_Monte_Carlo_Simulations">Comparison of Scoring Systems for Invasive Pests Using ROC Analysis and Monte Carlo Simulations: Comparison of Scoring Systems for Invasive Pests Using ROC Analysis and Monte Carlo Simulations</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Different international plant protection organisations advocate different schemes for conducting pest risk assessments. Most of these schemes use structured questionnaire in which experts are asked to score several items using an ordinal... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_1586397" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Different international plant protection organisations advocate different schemes for conducting pest risk assessments. Most of these schemes use structured questionnaire in which experts are asked to score several items using an ordinal scale. The scores are then combined using a range of procedures, such as simple arithmetic mean, weighted averages, multiplication of scores, and cumulative sums. The most useful schemes will correctly identify harmful pests and identify ones that are not. As the quality of a pest risk assessment can depend on the characteristics of the scoring system used by the risk assessors (i.e., on the number of points of the scale and on the method used for combining the component scores), it is important to assess and compare the performance of different scoring systems. In this article, we proposed a new method for assessing scoring systems. Its principle is to simulate virtual data using a stochastic model and, then, to estimate sensitivity and specificity values from these data for different scoring systems. The interest of our approach was illustrated in a case study where several scoring systems were compared. Data for this analysis were generated using a probabilistic model describing the pest introduction process. The generated data were then used to simulate the outcome of scoring systems and to assess the accuracy of the decisions about positive and negative introduction. The results showed that ordinal scales with at most 5 or 6 points were sufficient and that the multiplication-based scoring systems performed better than their sum-based counterparts. The proposed method could be used in the future to assess a great diversity of scoring systems.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/1586397" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="9512089e53c0fbd0a547f43a5c579f73" rel="nofollow" data-download="{"attachment_id":50918336,"asset_id":1586397,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50918336/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="1808855" href="https://independent.academia.edu/MittintyMurthy">Mittinty Murthy</a><script data-card-contents-for-user="1808855" type="text/json">{"id":1808855,"first_name":"Mittinty","last_name":"Murthy","domain_name":"independent","page_name":"MittintyMurthy","display_name":"Mittinty Murthy","profile_url":"https://independent.academia.edu/MittintyMurthy?f_ri=194916","photo":"https://0.academia-photos.com/1808855/617561/766576/s65_mittinty.murthy.jpg"}</script></span></span></li><li class="js-paper-rank-work_1586397 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="1586397"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 1586397, container: ".js-paper-rank-work_1586397", }); 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$(".js-view-count[data-work-id=1586397]").text(description); $(".js-view-count-work_1586397").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_1586397").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="1586397"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="4392" rel="nofollow" href="https://www.academia.edu/Documents/in/Monte_Carlo_Simulation">Monte Carlo Simulation</a>, <script data-card-contents-for-ri="4392" type="text/json">{"id":4392,"name":"Monte Carlo Simulation","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Simulation?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="11870" rel="nofollow" href="https://www.academia.edu/Documents/in/Invasive_Species">Invasive Species</a>, <script data-card-contents-for-ri="11870" type="text/json">{"id":11870,"name":"Invasive Species","url":"https://www.academia.edu/Documents/in/Invasive_Species?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="28235" rel="nofollow" href="https://www.academia.edu/Documents/in/Multidisciplinary">Multidisciplinary</a>, <script data-card-contents-for-ri="28235" type="text/json">{"id":28235,"name":"Multidisciplinary","url":"https://www.academia.edu/Documents/in/Multidisciplinary?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="50711" rel="nofollow" href="https://www.academia.edu/Documents/in/Risk_Analysis">Risk Analysis</a><script data-card-contents-for-ri="50711" type="text/json">{"id":50711,"name":"Risk Analysis","url":"https://www.academia.edu/Documents/in/Risk_Analysis?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=1586397]'), work: {"id":1586397,"title":"Comparison of Scoring Systems for Invasive Pests Using ROC Analysis and Monte Carlo Simulations: Comparison of Scoring Systems for Invasive Pests Using ROC Analysis and Monte Carlo Simulations","created_at":"2012-05-23T18:14:44.468-07:00","url":"https://www.academia.edu/1586397/Comparison_of_Scoring_Systems_for_Invasive_Pests_Using_ROC_Analysis_and_Monte_Carlo_Simulations_Comparison_of_Scoring_Systems_for_Invasive_Pests_Using_ROC_Analysis_and_Monte_Carlo_Simulations?f_ri=194916","dom_id":"work_1586397","summary":"Different international plant protection organisations advocate different schemes for conducting pest risk assessments. Most of these schemes use structured questionnaire in which experts are asked to score several items using an ordinal scale. The scores are then combined using a range of procedures, such as simple arithmetic mean, weighted averages, multiplication of scores, and cumulative sums. The most useful schemes will correctly identify harmful pests and identify ones that are not. As the quality of a pest risk assessment can depend on the characteristics of the scoring system used by the risk assessors (i.e., on the number of points of the scale and on the method used for combining the component scores), it is important to assess and compare the performance of different scoring systems. In this article, we proposed a new method for assessing scoring systems. Its principle is to simulate virtual data using a stochastic model and, then, to estimate sensitivity and specificity values from these data for different scoring systems. The interest of our approach was illustrated in a case study where several scoring systems were compared. Data for this analysis were generated using a probabilistic model describing the pest introduction process. The generated data were then used to simulate the outcome of scoring systems and to assess the accuracy of the decisions about positive and negative introduction. The results showed that ordinal scales with at most 5 or 6 points were sufficient and that the multiplication-based scoring systems performed better than their sum-based counterparts. The proposed method could be used in the future to assess a great diversity of scoring systems.","downloadable_attachments":[{"id":50918336,"asset_id":1586397,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":1808855,"first_name":"Mittinty","last_name":"Murthy","domain_name":"independent","page_name":"MittintyMurthy","display_name":"Mittinty Murthy","profile_url":"https://independent.academia.edu/MittintyMurthy?f_ri=194916","photo":"https://0.academia-photos.com/1808855/617561/766576/s65_mittinty.murthy.jpg"}],"research_interests":[{"id":4392,"name":"Monte Carlo Simulation","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Simulation?f_ri=194916","nofollow":true},{"id":11870,"name":"Invasive Species","url":"https://www.academia.edu/Documents/in/Invasive_Species?f_ri=194916","nofollow":true},{"id":28235,"name":"Multidisciplinary","url":"https://www.academia.edu/Documents/in/Multidisciplinary?f_ri=194916","nofollow":true},{"id":50711,"name":"Risk Analysis","url":"https://www.academia.edu/Documents/in/Risk_Analysis?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":401947,"name":"Sensitivity","url":"https://www.academia.edu/Documents/in/Sensitivity?f_ri=194916"},{"id":871199,"name":"Stochastic Model","url":"https://www.academia.edu/Documents/in/Stochastic_Model?f_ri=194916"},{"id":1333436,"name":"Monte Carlo Method","url":"https://www.academia.edu/Documents/in/Monte_Carlo_Method?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3710239" data-work_id="3710239" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3710239/Reliability_of_indicators_of_decline_in_abundance">Reliability of indicators of decline in abundance</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Abstract: Although there are many indicators of endangerment (i.e., whether populations or species meet criteria that justify conservation action), their reliability has rarely been tested. Such indicators may fail to identify that a... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3710239" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Abstract: Although there are many indicators of endangerment (i.e., whether populations or species meet criteria that justify conservation action), their reliability has rarely been tested. Such indicators may fail to identify that a population or species meets criteria for conservation action (false negative) or may incorrectly show that such criteria have been met (false positive). To quantify the rate of both types of error for 20 commonly used indicators of declining abundance (threat indicators), we used receiver operating characteristic curves derived from historical (1938–2007) data for 18 sockeye salmon (Oncorhynchus nerka) populations in the Fraser River, British Columbia, Canada. We retrospectively determined each population's yearly status (reflected by change in abundance over time) on the basis of each indicator. We then compared that population's status in a given year with the status in subsequent years (determined by the magnitude of decline in abundance across those years). For each sockeye population, we calculated how often each indicator of past status matched subsequent status. No single threat indicator provided error-free estimates of status, but indicators that reflected the extent (i.e., magnitude) of past decline in abundance (through comparison of current abundance with some historical baseline abundance) tended to better reflect status in subsequent years than the rate of decline over the previous 3 generations (a widely used indicator). We recommend that when possible, the reliability of various threat indicators be evaluated with empirical analyses before such indicators are used to determine the need for conservation action. These indicators should include estimates from the entire data set to take into account a historical baseline.Resumen: Aunque existen muchos indicadores de riesgo (i.e., sí las poblaciones o especies cumplen con criterios para justificar acciones de conservación), su confiabilidad ha sido probada pocas veces. Dichos indicadores pueden fallar al identificar que una población o especie cumple con criterios para acciones de conservación (negativo falso) o pueden mostrar incorrectamente que tales criterios se han cumplido (positivo falso). Para cuantificar la tasa de ambos tipos de error para 20 indicadores de declinación de abundancia (indicadores de amenaza) utilizados comúnmente, utilizamos curvas de características de operación de receptores derivadas de datos históricos (1937–2008) de 18 poblaciones de salmón (Oncorhynchus nerka) en el Río Fraser, Columbia Británica, Canadá. Retrospectivamente determinamos el estatus anual de cada población (reflejado en cambios en la abundancia en el tiempo) con base en cada indicador. Posteriormente comparamos el estatus de la población en un año determinado con el estatus de años subsecuentes (determinado por la magnitud de la declinación en abundancia en esos años). Para cada población de salmón, calculamos la frecuencia en que cada indicador de estatus pasado era igual al estatus subsecuente. Ningún indicador de amenaza proporcionó estimaciones de estatus libres de error, pero los indicadores que reflejaron la extensión (i.e., magnitud) de la declinación en abundancia pasada (mediante comparación de la abundancia actual con la abundancia histórica de referencia) tendieron a reflejar de mejor manera el estatus en años anteriores que la tasa de declinación en las 3 generaciones previas (un indicador ampliamente utilizado). Recomendamos que, cuando sea posible, se evalúe la confiabilidad de varios indicadores de amenaza con análisis empíricos antes de que esos indicadores sean utilizados para determinar la necesidad de acciones de conservación. Estos indicadores deben incluir estimaciones a partir del total de datos para considerar una referencia histórica.Resumen: Aunque existen muchos indicadores de riesgo (i.e., sí las poblaciones o especies cumplen con criterios para justificar acciones de conservación), su confiabilidad ha sido probada pocas veces. Dichos indicadores pueden fallar al identificar que una población o especie cumple con criterios para acciones de conservación (negativo falso) o pueden mostrar incorrectamente que tales criterios se han cumplido (positivo falso). Para cuantificar la tasa de ambos tipos de error para 20 indicadores de declinación de abundancia (indicadores de amenaza) utilizados comúnmente, utilizamos curvas de características de operación de receptores derivadas de datos históricos (1937–2008) de 18 poblaciones de salmón (Oncorhynchus nerka) en el Río Fraser, Columbia Británica, Canadá. Retrospectivamente determinamos el estatus anual de cada población (reflejado en cambios en la abundancia en el tiempo) con base en cada indicador. Posteriormente comparamos el estatus de la población en un año determinado con el estatus de años subsecuentes (determinado por la magnitud de la declinación en abundancia en esos años). Para cada población de salmón, calculamos la frecuencia en que cada indicador de estatus pasado era igual al estatus subsecuente. Ningún indicador de amenaza proporcionó estimaciones de estatus libres de error, pero los indicadores que reflejaron la extensión (i.e., magnitud) de la declinación en abundancia pasada (mediante comparación de la abundancia actual con la abundancia histórica de referencia) tendieron a reflejar de mejor manera el estatus en años anteriores que la tasa de declinación en las 3 generaciones previas (un indicador ampliamente utilizado). Recomendamos que, cuando sea posible, se evalúe la confiabilidad de varios indicadores de amenaza con análisis empíricos antes de que esos indicadores sean utilizados para determinar la necesidad de acciones de conservación. Estos indicadores deben incluir estimaciones a partir del total de datos para considerar una referencia histórica.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3710239" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="e12a7edfe2cf9dd22024f9b9ce8da770" rel="nofollow" data-download="{"attachment_id":50168151,"asset_id":3710239,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50168151/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="828742" href="https://sfu.academia.edu/NickDulvy">Nick Dulvy</a><script data-card-contents-for-user="828742" type="text/json">{"id":828742,"first_name":"Nick","last_name":"Dulvy","domain_name":"sfu","page_name":"NickDulvy","display_name":"Nick Dulvy","profile_url":"https://sfu.academia.edu/NickDulvy?f_ri=194916","photo":"https://0.academia-photos.com/828742/289235/14813720/s65_nick.dulvy.jpg"}</script></span></span></li><li class="js-paper-rank-work_3710239 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="3710239"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 3710239, container: ".js-paper-rank-work_3710239", }); 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$(".js-view-count[data-work-id=3710239]").text(description); $(".js-view-count-work_3710239").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_3710239").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="3710239"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">13</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="2467" rel="nofollow" href="https://www.academia.edu/Documents/in/Conservation_Biology">Conservation Biology</a>, <script data-card-contents-for-ri="2467" type="text/json">{"id":2467,"name":"Conservation Biology","url":"https://www.academia.edu/Documents/in/Conservation_Biology?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="4559" rel="nofollow" href="https://www.academia.edu/Documents/in/Reproduction">Reproduction</a>, <script data-card-contents-for-ri="4559" type="text/json">{"id":4559,"name":"Reproduction","url":"https://www.academia.edu/Documents/in/Reproduction?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="47884" rel="nofollow" href="https://www.academia.edu/Documents/in/Biological_Sciences">Biological Sciences</a>, <script data-card-contents-for-ri="47884" type="text/json">{"id":47884,"name":"Biological Sciences","url":"https://www.academia.edu/Documents/in/Biological_Sciences?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="58054" rel="nofollow" href="https://www.academia.edu/Documents/in/Environmental_Sciences">Environmental Sciences</a><script data-card-contents-for-ri="58054" type="text/json">{"id":58054,"name":"Environmental Sciences","url":"https://www.academia.edu/Documents/in/Environmental_Sciences?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=3710239]'), work: {"id":3710239,"title":"Reliability of indicators of decline in abundance","created_at":"2013-06-14T03:21:15.793-07:00","url":"https://www.academia.edu/3710239/Reliability_of_indicators_of_decline_in_abundance?f_ri=194916","dom_id":"work_3710239","summary":"Abstract: Although there are many indicators of endangerment (i.e., whether populations or species meet criteria that justify conservation action), their reliability has rarely been tested. Such indicators may fail to identify that a population or species meets criteria for conservation action (false negative) or may incorrectly show that such criteria have been met (false positive). To quantify the rate of both types of error for 20 commonly used indicators of declining abundance (threat indicators), we used receiver operating characteristic curves derived from historical (1938–2007) data for 18 sockeye salmon (Oncorhynchus nerka) populations in the Fraser River, British Columbia, Canada. We retrospectively determined each population's yearly status (reflected by change in abundance over time) on the basis of each indicator. We then compared that population's status in a given year with the status in subsequent years (determined by the magnitude of decline in abundance across those years). For each sockeye population, we calculated how often each indicator of past status matched subsequent status. No single threat indicator provided error-free estimates of status, but indicators that reflected the extent (i.e., magnitude) of past decline in abundance (through comparison of current abundance with some historical baseline abundance) tended to better reflect status in subsequent years than the rate of decline over the previous 3 generations (a widely used indicator). We recommend that when possible, the reliability of various threat indicators be evaluated with empirical analyses before such indicators are used to determine the need for conservation action. These indicators should include estimates from the entire data set to take into account a historical baseline.Resumen: Aunque existen muchos indicadores de riesgo (i.e., sí las poblaciones o especies cumplen con criterios para justificar acciones de conservación), su confiabilidad ha sido probada pocas veces. Dichos indicadores pueden fallar al identificar que una población o especie cumple con criterios para acciones de conservación (negativo falso) o pueden mostrar incorrectamente que tales criterios se han cumplido (positivo falso). Para cuantificar la tasa de ambos tipos de error para 20 indicadores de declinación de abundancia (indicadores de amenaza) utilizados comúnmente, utilizamos curvas de características de operación de receptores derivadas de datos históricos (1937–2008) de 18 poblaciones de salmón (Oncorhynchus nerka) en el Río Fraser, Columbia Británica, Canadá. Retrospectivamente determinamos el estatus anual de cada población (reflejado en cambios en la abundancia en el tiempo) con base en cada indicador. Posteriormente comparamos el estatus de la población en un año determinado con el estatus de años subsecuentes (determinado por la magnitud de la declinación en abundancia en esos años). Para cada población de salmón, calculamos la frecuencia en que cada indicador de estatus pasado era igual al estatus subsecuente. Ningún indicador de amenaza proporcionó estimaciones de estatus libres de error, pero los indicadores que reflejaron la extensión (i.e., magnitud) de la declinación en abundancia pasada (mediante comparación de la abundancia actual con la abundancia histórica de referencia) tendieron a reflejar de mejor manera el estatus en años anteriores que la tasa de declinación en las 3 generaciones previas (un indicador ampliamente utilizado). Recomendamos que, cuando sea posible, se evalúe la confiabilidad de varios indicadores de amenaza con análisis empíricos antes de que esos indicadores sean utilizados para determinar la necesidad de acciones de conservación. Estos indicadores deben incluir estimaciones a partir del total de datos para considerar una referencia histórica.Resumen: Aunque existen muchos indicadores de riesgo (i.e., sí las poblaciones o especies cumplen con criterios para justificar acciones de conservación), su confiabilidad ha sido probada pocas veces. Dichos indicadores pueden fallar al identificar que una población o especie cumple con criterios para acciones de conservación (negativo falso) o pueden mostrar incorrectamente que tales criterios se han cumplido (positivo falso). Para cuantificar la tasa de ambos tipos de error para 20 indicadores de declinación de abundancia (indicadores de amenaza) utilizados comúnmente, utilizamos curvas de características de operación de receptores derivadas de datos históricos (1937–2008) de 18 poblaciones de salmón (Oncorhynchus nerka) en el Río Fraser, Columbia Británica, Canadá. Retrospectivamente determinamos el estatus anual de cada población (reflejado en cambios en la abundancia en el tiempo) con base en cada indicador. Posteriormente comparamos el estatus de la población en un año determinado con el estatus de años subsecuentes (determinado por la magnitud de la declinación en abundancia en esos años). Para cada población de salmón, calculamos la frecuencia en que cada indicador de estatus pasado era igual al estatus subsecuente. Ningún indicador de amenaza proporcionó estimaciones de estatus libres de error, pero los indicadores que reflejaron la extensión (i.e., magnitud) de la declinación en abundancia pasada (mediante comparación de la abundancia actual con la abundancia histórica de referencia) tendieron a reflejar de mejor manera el estatus en años anteriores que la tasa de declinación en las 3 generaciones previas (un indicador ampliamente utilizado). Recomendamos que, cuando sea posible, se evalúe la confiabilidad de varios indicadores de amenaza con análisis empíricos antes de que esos indicadores sean utilizados para determinar la necesidad de acciones de conservación. Estos indicadores deben incluir estimaciones a partir del total de datos para considerar una referencia histórica.","downloadable_attachments":[{"id":50168151,"asset_id":3710239,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":828742,"first_name":"Nick","last_name":"Dulvy","domain_name":"sfu","page_name":"NickDulvy","display_name":"Nick Dulvy","profile_url":"https://sfu.academia.edu/NickDulvy?f_ri=194916","photo":"https://0.academia-photos.com/828742/289235/14813720/s65_nick.dulvy.jpg"}],"research_interests":[{"id":2467,"name":"Conservation Biology","url":"https://www.academia.edu/Documents/in/Conservation_Biology?f_ri=194916","nofollow":true},{"id":4559,"name":"Reproduction","url":"https://www.academia.edu/Documents/in/Reproduction?f_ri=194916","nofollow":true},{"id":47884,"name":"Biological Sciences","url":"https://www.academia.edu/Documents/in/Biological_Sciences?f_ri=194916","nofollow":true},{"id":58054,"name":"Environmental Sciences","url":"https://www.academia.edu/Documents/in/Environmental_Sciences?f_ri=194916","nofollow":true},{"id":117886,"name":"Animal migration","url":"https://www.academia.edu/Documents/in/Animal_migration?f_ri=194916"},{"id":162645,"name":"Population Density","url":"https://www.academia.edu/Documents/in/Population_Density?f_ri=194916"},{"id":164918,"name":"Salmon","url":"https://www.academia.edu/Documents/in/Salmon?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":198379,"name":"British Columbia","url":"https://www.academia.edu/Documents/in/British_Columbia?f_ri=194916"},{"id":469105,"name":"Retrospective Studies","url":"https://www.academia.edu/Documents/in/Retrospective_Studies?f_ri=194916"},{"id":649451,"name":"Seasons","url":"https://www.academia.edu/Documents/in/Seasons?f_ri=194916"},{"id":719974,"name":"Conservation of Natural Resources","url":"https://www.academia.edu/Documents/in/Conservation_of_Natural_Resources?f_ri=194916"},{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_7157827" data-work_id="7157827" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/7157827/Overexpression_of_11%CE%B2_Hydroxysteroid_Dehydrogenase_Type_1_in_Hepatic_and_Visceral_Adipose_Tissue_is_Associated_with_Metabolic_Disorders_in_Morbidly_Obese_Patients">Overexpression of 11β-Hydroxysteroid Dehydrogenase Type 1 in Hepatic and Visceral Adipose Tissue is Associated with Metabolic Disorders in Morbidly Obese Patients</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Background The enzyme 11-β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) catalyzes intracellular glucocorticoid reactivation by conversion of cortisone to cortisol in different tissues and have been implicated in several metabolic... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_7157827" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Background The enzyme 11-β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) catalyzes intracellular glucocorticoid reactivation by conversion of cortisone to cortisol in different tissues and have been implicated in several metabolic disorders associated with obesity. The aim of this study was to evaluate the 11β-HSD1 expression in liver, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) in morbidly obese patients undergoing bariatric surgery and its correlations with clinical, anthropometric, and biochemical variables. Methods A prospective study was conducted over a 27-month period. Hepatic, VAT, and SAT samples were obtained at the time of surgery. 11β-HSD1 and 18S gene expression was measured using real-time quantitative reverse transcriptase-polymerase chain reaction. Results Forty nine patients met the inclusion criteria [mean age: 42.2 ± 10 years, body mass index (BMI): 42 ± 6 kg/m2, 71% women and 63% with metabolic syndrome (MS)]. 11β-HSD1 mRNA levels were higher in liver than fat tissue (p < 0.001), being higher in SAT than in VAT (p < 0.001) without gender-specific differences. Hepatic expression of 11β-HSD1 correlated positively with SAT and VAT, alanine aminotransferase (ALT), and serum glucose and was inversely associated with BMI. 11β-HSD1 mRNA in VAT correlated positively with insulinemia, ALT, and LDL cholesterol. There were no associations between 11β-HSD1 mRNA in SAT and the variables analyzed. Conclusions 11β-HSD1 expression is higher in liver in comparison to adipose tissue in obese patients. The observed correlations between hepatic and VAT 11β-HSD1 expression with dyslipidemia and insulin resistance suggest that this enzyme might have a pathogenic role in obesity and related metabolic disorders.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/7157827" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="88e06a31d9d4d64df7a25a3ec3db028d" rel="nofollow" data-download="{"attachment_id":48577516,"asset_id":7157827,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/48577516/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="12366896" href="https://independent.academia.edu/MauricioMorales9">Mauricio Morales</a><script data-card-contents-for-user="12366896" type="text/json">{"id":12366896,"first_name":"Mauricio","last_name":"Morales","domain_name":"independent","page_name":"MauricioMorales9","display_name":"Mauricio Morales","profile_url":"https://independent.academia.edu/MauricioMorales9?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_7157827 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="7157827"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 7157827, container: ".js-paper-rank-work_7157827", }); 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$(".js-view-count[data-work-id=7157827]").text(description); $(".js-view-count-work_7157827").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_7157827").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="7157827"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">38</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="648" rel="nofollow" href="https://www.academia.edu/Documents/in/Bariatric_Surgery">Bariatric Surgery</a>, <script data-card-contents-for-ri="648" type="text/json">{"id":648,"name":"Bariatric Surgery","url":"https://www.academia.edu/Documents/in/Bariatric_Surgery?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="3851" rel="nofollow" href="https://www.academia.edu/Documents/in/Obesity">Obesity</a>, <script data-card-contents-for-ri="3851" type="text/json">{"id":3851,"name":"Obesity","url":"https://www.academia.edu/Documents/in/Obesity?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="27784" rel="nofollow" href="https://www.academia.edu/Documents/in/Gene_expression">Gene expression</a>, <script data-card-contents-for-ri="27784" type="text/json">{"id":27784,"name":"Gene expression","url":"https://www.academia.edu/Documents/in/Gene_expression?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="37818" rel="nofollow" href="https://www.academia.edu/Documents/in/Metabolic_syndrome">Metabolic syndrome</a><script data-card-contents-for-ri="37818" type="text/json">{"id":37818,"name":"Metabolic syndrome","url":"https://www.academia.edu/Documents/in/Metabolic_syndrome?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=7157827]'), work: {"id":7157827,"title":"Overexpression of 11β-Hydroxysteroid Dehydrogenase Type 1 in Hepatic and Visceral Adipose Tissue is Associated with Metabolic Disorders in Morbidly Obese Patients","created_at":"2014-05-25T20:35:01.474-07:00","url":"https://www.academia.edu/7157827/Overexpression_of_11%CE%B2_Hydroxysteroid_Dehydrogenase_Type_1_in_Hepatic_and_Visceral_Adipose_Tissue_is_Associated_with_Metabolic_Disorders_in_Morbidly_Obese_Patients?f_ri=194916","dom_id":"work_7157827","summary":"Background The enzyme 11-β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) catalyzes intracellular glucocorticoid reactivation by conversion of cortisone to cortisol in different tissues and have been implicated in several metabolic disorders associated with obesity. The aim of this study was to evaluate the 11β-HSD1 expression in liver, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) in morbidly obese patients undergoing bariatric surgery and its correlations with clinical, anthropometric, and biochemical variables. Methods A prospective study was conducted over a 27-month period. Hepatic, VAT, and SAT samples were obtained at the time of surgery. 11β-HSD1 and 18S gene expression was measured using real-time quantitative reverse transcriptase-polymerase chain reaction. Results Forty nine patients met the inclusion criteria [mean age: 42.2 ± 10 years, body mass index (BMI): 42 ± 6 kg/m2, 71% women and 63% with metabolic syndrome (MS)]. 11β-HSD1 mRNA levels were higher in liver than fat tissue (p \u003c 0.001), being higher in SAT than in VAT (p \u003c 0.001) without gender-specific differences. Hepatic expression of 11β-HSD1 correlated positively with SAT and VAT, alanine aminotransferase (ALT), and serum glucose and was inversely associated with BMI. 11β-HSD1 mRNA in VAT correlated positively with insulinemia, ALT, and LDL cholesterol. There were no associations between 11β-HSD1 mRNA in SAT and the variables analyzed. Conclusions 11β-HSD1 expression is higher in liver in comparison to adipose tissue in obese patients. The observed correlations between hepatic and VAT 11β-HSD1 expression with dyslipidemia and insulin resistance suggest that this enzyme might have a pathogenic role in obesity and related metabolic disorders.","downloadable_attachments":[{"id":48577516,"asset_id":7157827,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":12366896,"first_name":"Mauricio","last_name":"Morales","domain_name":"independent","page_name":"MauricioMorales9","display_name":"Mauricio Morales","profile_url":"https://independent.academia.edu/MauricioMorales9?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":648,"name":"Bariatric Surgery","url":"https://www.academia.edu/Documents/in/Bariatric_Surgery?f_ri=194916","nofollow":true},{"id":3851,"name":"Obesity","url":"https://www.academia.edu/Documents/in/Obesity?f_ri=194916","nofollow":true},{"id":27784,"name":"Gene 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tissue","url":"https://www.academia.edu/Documents/in/Adipose_tissue?f_ri=194916"},{"id":58431,"name":"Cortisol","url":"https://www.academia.edu/Documents/in/Cortisol?f_ri=194916"},{"id":71437,"name":"Liver","url":"https://www.academia.edu/Documents/in/Liver?f_ri=194916"},{"id":84760,"name":"Mice","url":"https://www.academia.edu/Documents/in/Mice?f_ri=194916"},{"id":90514,"name":"Cholesterol","url":"https://www.academia.edu/Documents/in/Cholesterol?f_ri=194916"},{"id":103297,"name":"Corticosterone","url":"https://www.academia.edu/Documents/in/Corticosterone?f_ri=194916"},{"id":133057,"name":"Young Adult","url":"https://www.academia.edu/Documents/in/Young_Adult?f_ri=194916"},{"id":151036,"name":"non alcoholic fatty liver disease (NAFLD)","url":"https://www.academia.edu/Documents/in/non_alcoholic_fatty_liver_disease_NAFLD_?f_ri=194916"},{"id":192564,"name":"Body Mass Index","url":"https://www.academia.edu/Documents/in/Body_Mass_Index?f_ri=194916"},{"id":194916,"name":"ROC 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class="InlineList-item"><div class="download"><a id="249004c46c21f1e0061d4541c9e07474" rel="nofollow" data-download="{"attachment_id":48100408,"asset_id":8424924,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/48100408/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="17083658" href="https://independent.academia.edu/FrankyShah">Franky Shah</a><script data-card-contents-for-user="17083658" type="text/json">{"id":17083658,"first_name":"Franky","last_name":"Shah","domain_name":"independent","page_name":"FrankyShah","display_name":"Franky Shah","profile_url":"https://independent.academia.edu/FrankyShah?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_8424924 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="8424924"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 8424924, container: ".js-paper-rank-work_8424924", }); });</script></li><li class="js-percentile-work_8424924 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 8424924; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_8424924"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_8424924 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="8424924"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 8424924; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=8424924]").text(description); $(".js-view-count-work_8424924").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_8424924").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="8424924"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">20</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="6802" rel="nofollow" href="https://www.academia.edu/Documents/in/Breast_Cancer">Breast Cancer</a>, <script data-card-contents-for-ri="6802" type="text/json">{"id":6802,"name":"Breast Cancer","url":"https://www.academia.edu/Documents/in/Breast_Cancer?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="10610" rel="nofollow" href="https://www.academia.edu/Documents/in/Survival_Analysis">Survival Analysis</a>, <script data-card-contents-for-ri="10610" type="text/json">{"id":10610,"name":"Survival Analysis","url":"https://www.academia.edu/Documents/in/Survival_Analysis?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="12071" rel="nofollow" href="https://www.academia.edu/Documents/in/Immunohistochemistry">Immunohistochemistry</a>, <script data-card-contents-for-ri="12071" type="text/json">{"id":12071,"name":"Immunohistochemistry","url":"https://www.academia.edu/Documents/in/Immunohistochemistry?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="29149" rel="nofollow" href="https://www.academia.edu/Documents/in/Extracellular_Matrix">Extracellular Matrix</a><script data-card-contents-for-ri="29149" type="text/json">{"id":29149,"name":"Extracellular Matrix","url":"https://www.academia.edu/Documents/in/Extracellular_Matrix?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=8424924]'), work: {"id":8424924,"title":"Clinical significance of matrix metalloproteinase 2 and 9 in breast cancer","created_at":"2014-09-21T13:23:17.166-07:00","url":"https://www.academia.edu/8424924/Clinical_significance_of_matrix_metalloproteinase_2_and_9_in_breast_cancer?f_ri=194916","dom_id":"work_8424924","summary":null,"downloadable_attachments":[{"id":48100408,"asset_id":8424924,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":17083658,"first_name":"Franky","last_name":"Shah","domain_name":"independent","page_name":"FrankyShah","display_name":"Franky Shah","profile_url":"https://independent.academia.edu/FrankyShah?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":6802,"name":"Breast 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Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":203512,"name":"Cervical Cancer","url":"https://www.academia.edu/Documents/in/Cervical_Cancer?f_ri=194916"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916"},{"id":315194,"name":"Oral Squamous Cell Carcinoma (OSCC)","url":"https://www.academia.edu/Documents/in/Oral_Squamous_Cell_Carcinoma_OSCC_?f_ri=194916"},{"id":437772,"name":"Odds ratio","url":"https://www.academia.edu/Documents/in/Odds_ratio?f_ri=194916"},{"id":489727,"name":"Prognosis","url":"https://www.academia.edu/Documents/in/Prognosis?f_ri=194916"},{"id":527897,"name":"Matrix Metalloproteinases","url":"https://www.academia.edu/Documents/in/Matrix_Metalloproteinases?f_ri=194916"},{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916"},{"id":1745478,"name":"Adenocarcinoma","url":"https://www.academia.edu/Documents/in/Adenocarcinoma?f_ri=194916"},{"id":1819399,"name":"Case Control Studies","url":"https://www.academia.edu/Documents/in/Case_Control_Studies?f_ri=194916"},{"id":1920779,"name":"Matrix Metalloproteinase","url":"https://www.academia.edu/Documents/in/Matrix_Metalloproteinase?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_11013587" data-work_id="11013587" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/11013587/Early_diagnosis_of_perioperative_myocardial_infarction_after_coronary_bypass_grafting_a_study_using_biomarkers_and_cardiac_magnetic_resonance_imaging">Early diagnosis of perioperative myocardial infarction after coronary bypass grafting: a study using biomarkers and cardiac magnetic resonance imaging</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest">The Annals of Thoracic Surgery CME Program is located online at <a href="http://cme.ctsnetjournals.org" rel="nofollow">http://cme.ctsnetjournals.org</a>. To take the CME activity related to this article, you must have either an STS member or an individual non-member subscription to the journal.</div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/11013587" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="2d3e4c4801d40d555dd03d6ae1ad8a7b" rel="nofollow" data-download="{"attachment_id":46967474,"asset_id":11013587,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46967474/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="26661426" href="https://independent.academia.edu/LucaTesta">Luca Testa</a><script data-card-contents-for-user="26661426" type="text/json">{"id":26661426,"first_name":"Luca","last_name":"Testa","domain_name":"independent","page_name":"LucaTesta","display_name":"Luca Testa","profile_url":"https://independent.academia.edu/LucaTesta?f_ri=194916","photo":"https://0.academia-photos.com/26661426/7424745/8345120/s65_luca.testa.jpg"}</script></span></span></li><li class="js-paper-rank-work_11013587 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="11013587"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 11013587, container: ".js-paper-rank-work_11013587", }); });</script></li><li class="js-percentile-work_11013587 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 11013587; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_11013587"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_11013587 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="11013587"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 11013587; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=11013587]").text(description); $(".js-view-count-work_11013587").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_11013587").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="11013587"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">21</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="6200" rel="nofollow" href="https://www.academia.edu/Documents/in/Magnetic_Resonance_Imaging">Magnetic Resonance Imaging</a>, <script data-card-contents-for-ri="6200" type="text/json">{"id":6200,"name":"Magnetic Resonance Imaging","url":"https://www.academia.edu/Documents/in/Magnetic_Resonance_Imaging?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="6671" rel="nofollow" href="https://www.academia.edu/Documents/in/Syntax">Syntax</a>, <script data-card-contents-for-ri="6671" type="text/json">{"id":6671,"name":"Syntax","url":"https://www.academia.edu/Documents/in/Syntax?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="49685" rel="nofollow" href="https://www.academia.edu/Documents/in/CAD">CAD</a>, <script data-card-contents-for-ri="49685" type="text/json">{"id":49685,"name":"CAD","url":"https://www.academia.edu/Documents/in/CAD?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="62112" rel="nofollow" href="https://www.academia.edu/Documents/in/Prospective_studies">Prospective studies</a><script data-card-contents-for-ri="62112" type="text/json">{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=11013587]'), work: {"id":11013587,"title":"Early diagnosis of perioperative myocardial infarction after coronary bypass grafting: a study using biomarkers and cardiac magnetic resonance imaging","created_at":"2015-02-23T06:53:10.539-08:00","url":"https://www.academia.edu/11013587/Early_diagnosis_of_perioperative_myocardial_infarction_after_coronary_bypass_grafting_a_study_using_biomarkers_and_cardiac_magnetic_resonance_imaging?f_ri=194916","dom_id":"work_11013587","summary":"The Annals of Thoracic Surgery CME Program is located online at http://cme.ctsnetjournals.org. To take the CME activity related to this article, you must have either an STS member or an individual non-member subscription to the journal.","downloadable_attachments":[{"id":46967474,"asset_id":11013587,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":26661426,"first_name":"Luca","last_name":"Testa","domain_name":"independent","page_name":"LucaTesta","display_name":"Luca Testa","profile_url":"https://independent.academia.edu/LucaTesta?f_ri=194916","photo":"https://0.academia-photos.com/26661426/7424745/8345120/s65_luca.testa.jpg"}],"research_interests":[{"id":6200,"name":"Magnetic Resonance Imaging","url":"https://www.academia.edu/Documents/in/Magnetic_Resonance_Imaging?f_ri=194916","nofollow":true},{"id":6671,"name":"Syntax","url":"https://www.academia.edu/Documents/in/Syntax?f_ri=194916","nofollow":true},{"id":49685,"name":"CAD","url":"https://www.academia.edu/Documents/in/CAD?f_ri=194916","nofollow":true},{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true},{"id":99513,"name":"SVG","url":"https://www.academia.edu/Documents/in/SVG?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":231661,"name":"Enzyme","url":"https://www.academia.edu/Documents/in/Enzyme?f_ri=194916"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":262317,"name":"NPV","url":"https://www.academia.edu/Documents/in/NPV?f_ri=194916"},{"id":273338,"name":"IL","url":"https://www.academia.edu/Documents/in/IL?f_ri=194916"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916"},{"id":291532,"name":"PPV","url":"https://www.academia.edu/Documents/in/PPV?f_ri=194916"},{"id":375999,"name":"LM","url":"https://www.academia.edu/Documents/in/LM?f_ri=194916"},{"id":378016,"name":"Myocardial Infarction","url":"https://www.academia.edu/Documents/in/Myocardial_Infarction?f_ri=194916"},{"id":568482,"name":"Biological markers","url":"https://www.academia.edu/Documents/in/Biological_markers?f_ri=194916"},{"id":734790,"name":"Perioperative myocardial infarction","url":"https://www.academia.edu/Documents/in/Perioperative_myocardial_infarction?f_ri=194916"},{"id":906219,"name":"Coronary artery bypass surgery","url":"https://www.academia.edu/Documents/in/Coronary_artery_bypass_surgery?f_ri=194916"},{"id":1217494,"name":"Early Diagnosis","url":"https://www.academia.edu/Documents/in/Early_Diagnosis?f_ri=194916"},{"id":1309695,"name":"Troponin I","url":"https://www.academia.edu/Documents/in/Troponin_I?f_ri=194916"},{"id":1718007,"name":"Cardiac Magnetic Resonance Imaging","url":"https://www.academia.edu/Documents/in/Cardiac_Magnetic_Resonance_Imaging?f_ri=194916"},{"id":2439414,"name":"Magnetic resonance image","url":"https://www.academia.edu/Documents/in/Magnetic_resonance_image?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_26354106" data-work_id="26354106" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/26354106/Validity_of_the_motor_observation_questionnaire_for_teachers_as_a_screening_instrument_for_children_at_risk_for_developmental_coordination_disorder">Validity of the motor observation questionnaire for teachers as a screening instrument for children at risk for developmental coordination disorder</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This study investigates validity of the Motor Observation Questionnaire for Teachers (MOQ-T) in 182 children aged 5-10 years, 91 children referred for motor problems to a rehabilitation center and 91 comparison children. Performance on... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_26354106" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This study investigates validity of the Motor Observation Questionnaire for Teachers (MOQ-T) in 182 children aged 5-10 years, 91 children referred for motor problems to a rehabilitation center and 91 comparison children. Performance on the MOQ-T was compared to performance on the Movement Assessment Battery for Children (M-ABC) and the Developmental Coordination Disorder Questionnaire (DCD-Q). Significant correlations were obtained between the MOQ-T and the DCD-Q (r = À.63), and the MOQ-T and the M-ABC (r = .57). The MOQ-T discriminated between children at risk for DCD and comparison children. Sensitivity of the MOQ-T was 80.5%, specificity 62% with the M-ABC as 'gold standard'. These results support the validity of the MOQ-T as a screening instrument for identification of children at risk for DCD. address: <a href="mailto:M.M.Schoemaker@RUG.NL" rel="nofollow">M.M.Schoemaker@RUG.NL</a> (M.M. Schoemaker).</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/26354106" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="9ae6e25fe9f12a65758e211659bfc77f" rel="nofollow" data-download="{"attachment_id":46663721,"asset_id":26354106,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46663721/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="50290453" href="https://rug.academia.edu/HeleenReindersMesselink">Heleen Reinders-Messelink</a><script data-card-contents-for-user="50290453" type="text/json">{"id":50290453,"first_name":"Heleen","last_name":"Reinders-Messelink","domain_name":"rug","page_name":"HeleenReindersMesselink","display_name":"Heleen Reinders-Messelink","profile_url":"https://rug.academia.edu/HeleenReindersMesselink?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_26354106 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="26354106"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 26354106, container: ".js-paper-rank-work_26354106", }); 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Performance on the MOQ-T was compared to performance on the Movement Assessment Battery for Children (M-ABC) and the Developmental Coordination Disorder Questionnaire (DCD-Q). Significant correlations were obtained between the MOQ-T and the DCD-Q (r = À.63), and the MOQ-T and the M-ABC (r = .57). The MOQ-T discriminated between children at risk for DCD and comparison children. Sensitivity of the MOQ-T was 80.5%, specificity 62% with the M-ABC as 'gold standard'. These results support the validity of the MOQ-T as a screening instrument for identification of children at risk for DCD. address: M.M.Schoemaker@RUG.NL (M.M. Schoemaker).","downloadable_attachments":[{"id":46663721,"asset_id":26354106,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":50290453,"first_name":"Heleen","last_name":"Reinders-Messelink","domain_name":"rug","page_name":"HeleenReindersMesselink","display_name":"Heleen Reinders-Messelink","profile_url":"https://rug.academia.edu/HeleenReindersMesselink?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=194916","nofollow":true},{"id":37229,"name":"Human Movement Science","url":"https://www.academia.edu/Documents/in/Human_Movement_Science?f_ri=194916","nofollow":true},{"id":52253,"name":"Developmental Coordination Disorder","url":"https://www.academia.edu/Documents/in/Developmental_Coordination_Disorder?f_ri=194916","nofollow":true},{"id":62145,"name":"Faculty","url":"https://www.academia.edu/Documents/in/Faculty?f_ri=194916","nofollow":true},{"id":64933,"name":"Child","url":"https://www.academia.edu/Documents/in/Child?f_ri=194916"},{"id":66174,"name":"DCD","url":"https://www.academia.edu/Documents/in/DCD?f_ri=194916"},{"id":144833,"name":"Validity","url":"https://www.academia.edu/Documents/in/Validity?f_ri=194916"},{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":313752,"name":"Gold Standard","url":"https://www.academia.edu/Documents/in/Gold_Standard?f_ri=194916"},{"id":327850,"name":"Questionnaires","url":"https://www.academia.edu/Documents/in/Questionnaires?f_ri=194916"},{"id":493175,"name":"Human Movement","url":"https://www.academia.edu/Documents/in/Human_Movement?f_ri=194916"},{"id":620049,"name":"Risk Factors","url":"https://www.academia.edu/Documents/in/Risk_Factors-1?f_ri=194916"},{"id":2463800,"name":"Severity of Illness Index","url":"https://www.academia.edu/Documents/in/Severity_of_Illness_Index?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_25628705" data-work_id="25628705" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/25628705/Diagnostic_performance_of_CT_versus_MR_in_detecting_aldosterone_producing_adenoma_in_primary_hyperaldosteronism_Conn_s_syndrome_">Diagnostic performance of CT versus MR in detecting aldosterone-producing adenoma in primary hyperaldosteronism (Conn?s syndrome)</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The aim of the present study is to compare the diagnostic performance of CT and MR imaging in detecting aldosterone-producing adenoma and to compare the interobserver variability in the detection of an aldosterone-producing adenoma on CT... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_25628705" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The aim of the present study is to compare the diagnostic performance of CT and MR imaging in detecting aldosterone-producing adenoma and to compare the interobserver variability in the detection of an aldosterone-producing adenoma on CT and MR. A retrospective study of 34 patients with primary hyperaldosteronism was performed. A total of 17 cases of aldosterone-producing adenoma and 17 cases of bilateral adrenal hyperplasia were included. The final diagnosis of an adenoma was made by surgery with histological confirmation, whereas that of bilateral adrenal hyperplasia was made on adrenal venous sampling or a good biochemical and clinical response following medical treatment alone and in the absence of a unilateral radiological abnormality. The CT (n=30) and MR (n=24) scans were reviewed independently by two radiologists experienced in adrenal imaging, who were unaware of the cause of the primary hyperaldosteronism. The diagnostic performances of both observers in detecting an aldosterone-producing adenoma on CT and MR imaging were compared. The 16 adenomatous nodules that were detected on imaging ranged from 1 to 4.75 cm in diameter. The calculated sensitivity and specificity for detecting aldosterone-producing adenoma were 87 and 93% for one observer and 85 and 82% for the other observer on CT, and 83 and 83% for one observer and 92 and 92% for the other observer on MR, respectively. Receptor operating characteristics curve analysis showed similar performances of both observers in detecting an aldosterone-producing adenoma on CT and MR imaging. There was good interobserver agreement on CT (k=0.71) and on MR (k=0.67). We have demonstrated comparable diagnostic performance and good interobserver agreement on CT and MR imaging for the detection of aldosterone-producing adenoma.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/25628705" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="9dc78216542971fb053e5a92cbba49bf" rel="nofollow" data-download="{"attachment_id":46256206,"asset_id":25628705,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46256206/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="49262694" href="https://nwlh.academia.edu/RaviLingam">Ravi Lingam</a><script data-card-contents-for-user="49262694" type="text/json">{"id":49262694,"first_name":"Ravi","last_name":"Lingam","domain_name":"nwlh","page_name":"RaviLingam","display_name":"Ravi Lingam","profile_url":"https://nwlh.academia.edu/RaviLingam?f_ri=194916","photo":"https://0.academia-photos.com/49262694/13062449/14396602/s65_ravi.lingam.jpg"}</script></span></span></li><li class="js-paper-rank-work_25628705 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="25628705"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 25628705, container: ".js-paper-rank-work_25628705", }); 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$(".js-view-count[data-work-id=25628705]").text(description); $(".js-view-count-work_25628705").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_25628705").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="25628705"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">19</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="6200" rel="nofollow" href="https://www.academia.edu/Documents/in/Magnetic_Resonance_Imaging">Magnetic Resonance Imaging</a>, <script data-card-contents-for-ri="6200" type="text/json">{"id":6200,"name":"Magnetic Resonance Imaging","url":"https://www.academia.edu/Documents/in/Magnetic_Resonance_Imaging?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="89997" rel="nofollow" href="https://www.academia.edu/Documents/in/Aldosterone">Aldosterone</a>, <script data-card-contents-for-ri="89997" type="text/json">{"id":89997,"name":"Aldosterone","url":"https://www.academia.edu/Documents/in/Aldosterone?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="176968" rel="nofollow" href="https://www.academia.edu/Documents/in/Hyperplasia">Hyperplasia</a>, <script data-card-contents-for-ri="176968" type="text/json">{"id":176968,"name":"Hyperplasia","url":"https://www.academia.edu/Documents/in/Hyperplasia?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a><script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=25628705]'), work: {"id":25628705,"title":"Diagnostic performance of CT versus MR in detecting aldosterone-producing adenoma in primary hyperaldosteronism (Conn?s syndrome)","created_at":"2016-05-25T23:53:58.124-07:00","url":"https://www.academia.edu/25628705/Diagnostic_performance_of_CT_versus_MR_in_detecting_aldosterone_producing_adenoma_in_primary_hyperaldosteronism_Conn_s_syndrome_?f_ri=194916","dom_id":"work_25628705","summary":"The aim of the present study is to compare the diagnostic performance of CT and MR imaging in detecting aldosterone-producing adenoma and to compare the interobserver variability in the detection of an aldosterone-producing adenoma on CT and MR. A retrospective study of 34 patients with primary hyperaldosteronism was performed. A total of 17 cases of aldosterone-producing adenoma and 17 cases of bilateral adrenal hyperplasia were included. The final diagnosis of an adenoma was made by surgery with histological confirmation, whereas that of bilateral adrenal hyperplasia was made on adrenal venous sampling or a good biochemical and clinical response following medical treatment alone and in the absence of a unilateral radiological abnormality. The CT (n=30) and MR (n=24) scans were reviewed independently by two radiologists experienced in adrenal imaging, who were unaware of the cause of the primary hyperaldosteronism. The diagnostic performances of both observers in detecting an aldosterone-producing adenoma on CT and MR imaging were compared. The 16 adenomatous nodules that were detected on imaging ranged from 1 to 4.75 cm in diameter. The calculated sensitivity and specificity for detecting aldosterone-producing adenoma were 87 and 93% for one observer and 85 and 82% for the other observer on CT, and 83 and 83% for one observer and 92 and 92% for the other observer on MR, respectively. Receptor operating characteristics curve analysis showed similar performances of both observers in detecting an aldosterone-producing adenoma on CT and MR imaging. There was good interobserver agreement on CT (k=0.71) and on MR (k=0.67). We have demonstrated comparable diagnostic performance and good interobserver agreement on CT and MR imaging for the detection of aldosterone-producing adenoma.","downloadable_attachments":[{"id":46256206,"asset_id":25628705,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":49262694,"first_name":"Ravi","last_name":"Lingam","domain_name":"nwlh","page_name":"RaviLingam","display_name":"Ravi Lingam","profile_url":"https://nwlh.academia.edu/RaviLingam?f_ri=194916","photo":"https://0.academia-photos.com/49262694/13062449/14396602/s65_ravi.lingam.jpg"}],"research_interests":[{"id":6200,"name":"Magnetic Resonance Imaging","url":"https://www.academia.edu/Documents/in/Magnetic_Resonance_Imaging?f_ri=194916","nofollow":true},{"id":89997,"name":"Aldosterone","url":"https://www.academia.edu/Documents/in/Aldosterone?f_ri=194916","nofollow":true},{"id":176968,"name":"Hyperplasia","url":"https://www.academia.edu/Documents/in/Hyperplasia?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":279027,"name":"European","url":"https://www.academia.edu/Documents/in/European?f_ri=194916"},{"id":363788,"name":"Receiving Operating Characteristic","url":"https://www.academia.edu/Documents/in/Receiving_Operating_Characteristic?f_ri=194916"},{"id":375296,"name":"Observer Variation","url":"https://www.academia.edu/Documents/in/Observer_Variation?f_ri=194916"},{"id":438955,"name":"Sjogren´s Syndrome","url":"https://www.academia.edu/Documents/in/Sjogren_s_Syndrome?f_ri=194916"},{"id":469105,"name":"Retrospective Studies","url":"https://www.academia.edu/Documents/in/Retrospective_Studies?f_ri=194916"},{"id":589853,"name":"Adrenal Gland","url":"https://www.academia.edu/Documents/in/Adrenal_Gland?f_ri=194916"},{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916"},{"id":959921,"name":"X ray Computed Tomography","url":"https://www.academia.edu/Documents/in/X_ray_Computed_Tomography?f_ri=194916"},{"id":963748,"name":"Adenoma","url":"https://www.academia.edu/Documents/in/Adenoma?f_ri=194916"},{"id":990198,"name":"Retrospective Study","url":"https://www.academia.edu/Documents/in/Retrospective_Study?f_ri=194916"},{"id":1122411,"name":"Mr Imaging","url":"https://www.academia.edu/Documents/in/Mr_Imaging?f_ri=194916"},{"id":1318932,"name":"Predictive value of tests","url":"https://www.academia.edu/Documents/in/Predictive_value_of_tests?f_ri=194916"},{"id":1354774,"name":"Hyperaldosteronism","url":"https://www.academia.edu/Documents/in/Hyperaldosteronism?f_ri=194916"},{"id":1881146,"name":"Medical Treatment","url":"https://www.academia.edu/Documents/in/Medical_Treatment?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_13318564" data-work_id="13318564" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/13318564/Quantitative_analysis_of_CT_perfusion_parameters_in_the_evaluation_of_brain_gliomas_and_metastases">Quantitative analysis of CT-perfusion parameters in the evaluation of brain gliomas and metastases</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The paper reports a quantitative analysis of the perfusion maps of 22 patients, affected by gliomas or by metastasis, with the aim of characterizing the malignant tissue with respect to the normal tissue. The gold standard was obtained by... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_13318564" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The paper reports a quantitative analysis of the perfusion maps of 22 patients, affected by gliomas or by metastasis, with the aim of characterizing the malignant tissue with respect to the normal tissue. The gold standard was obtained by histological exam or nuclear medicine techniques. The perfusion scan provided 11 parametric maps, including Cerebral Blood Volume (CBV), Cerebral Blood Flow (CBF), Average Perfusion (P mean ) and Permeability-surface area product (PS).</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/13318564" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="46f71bf49af0ddbc0302ca7ebadc7c79" rel="nofollow" data-download="{"attachment_id":45474606,"asset_id":13318564,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/45474606/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="32564152" href="https://independent.academia.edu/AnnaDiNallo">Anna Di Nallo</a><script data-card-contents-for-user="32564152" type="text/json">{"id":32564152,"first_name":"Anna Di","last_name":"Nallo","domain_name":"independent","page_name":"AnnaDiNallo","display_name":"Anna Di Nallo","profile_url":"https://independent.academia.edu/AnnaDiNallo?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_13318564 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="13318564"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 13318564, container: ".js-paper-rank-work_13318564", }); 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When computational methods are... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_13552450" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Automated and efficient methods that map ortholog interactions from several organisms and public databases (pDB) are needed to identify new interactions in an organism of interest (interolog mapping). When computational methods are applied to predict interactions, it is important that these methods be validated and their efficiency proven. In this study, we compare six Blast+ metrics over three datasets to identify the best metric for protein-protein interaction predictions. Using Blast+ to align the protein pairs, the ortholog interactions from DIP were mapped to String, Intact and Psibase pDBs. For each interaction mapped to each pDBs, we retrieved the alignment score, e-value, bitscore, similarity, identity and coverage. We evaluated these Blast+ values, and combinations thereof, with the Receiver Operating Characteristic (ROC) curves and computed the Area Under Curve (AUC). To validate these predictions, we used a subset of the Database of Interacting Proteins (DIP) composed of ...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/13552450" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="3fbafda3bddbf2ae8f28445a220c46e2" rel="nofollow" data-download="{"attachment_id":45221473,"asset_id":13552450,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/45221473/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="32740963" href="https://independent.academia.edu/DebmalyaBarh">Debmalya Barh</a><script data-card-contents-for-user="32740963" type="text/json">{"id":32740963,"first_name":"Debmalya","last_name":"Barh","domain_name":"independent","page_name":"DebmalyaBarh","display_name":"Debmalya Barh","profile_url":"https://independent.academia.edu/DebmalyaBarh?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-13552450">+1</span><div class="hidden js-additional-users-13552450"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://cpmtc-igc-ufmg.academia.edu/EdsonFolador">Edson L Folador</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-13552450'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-13552450').html(); 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When computational methods are applied to predict interactions, it is important that these methods be validated and their efficiency proven. In this study, we compare six Blast+ metrics over three datasets to identify the best metric for protein-protein interaction predictions. Using Blast+ to align the protein pairs, the ortholog interactions from DIP were mapped to String, Intact and Psibase pDBs. For each interaction mapped to each pDBs, we retrieved the alignment score, e-value, bitscore, similarity, identity and coverage. We evaluated these Blast+ values, and combinations thereof, with the Receiver Operating Characteristic (ROC) curves and computed the Area Under Curve (AUC). To validate these predictions, we used a subset of the Database of Interacting Proteins (DIP) composed of ...","downloadable_attachments":[{"id":45221473,"asset_id":13552450,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":32740963,"first_name":"Debmalya","last_name":"Barh","domain_name":"independent","page_name":"DebmalyaBarh","display_name":"Debmalya Barh","profile_url":"https://independent.academia.edu/DebmalyaBarh?f_ri=194916","photo":"/images/s65_no_pic.png"},{"id":32785739,"first_name":"Edson","last_name":"Folador","domain_name":"cpmtc-igc-ufmg","page_name":"EdsonFolador","display_name":"Edson L Folador","profile_url":"https://cpmtc-igc-ufmg.academia.edu/EdsonFolador?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":4233,"name":"Computational Biology","url":"https://www.academia.edu/Documents/in/Computational_Biology?f_ri=194916","nofollow":true},{"id":37871,"name":"Integrative Biology","url":"https://www.academia.edu/Documents/in/Integrative_Biology?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":1309706,"name":"Area Under Curve","url":"https://www.academia.edu/Documents/in/Area_Under_Curve?f_ri=194916","nofollow":true}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_13996013" data-work_id="13996013" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/13996013/A_web_based_pilot_study_of_inter_pathologist_reproducibility_using_the_ISHLT_2004_working_formulation_for_biopsy_diagnosis_of_cardiac_allograft_rejection_The_European_experience">A web-based pilot study of inter-pathologist reproducibility using the ISHLT 2004 working formulation for biopsy diagnosis of cardiac allograft rejection: The European experience</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The aim of this study was to assess, at the European level and using digital technology, the inter-pathologist reproducibility of the ISHLT 2004 system and to compare it with the 1990 system We also assessed the reproducibility of the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_13996013" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The aim of this study was to assess, at the European level and using digital technology, the inter-pathologist reproducibility of the ISHLT 2004 system and to compare it with the 1990 system We also assessed the reproducibility of the morphologic criteria for diagnosis of antibodymediated rejection detailed in the 2004 grading system.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/13996013" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ce17ae999abc9ffb73813c97b72391b9" rel="nofollow" data-download="{"attachment_id":44720699,"asset_id":13996013,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" 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Fries","profile_url":"https://uni-koln.academia.edu/JochenFries?f_ri=194916","photo":"https://0.academia-photos.com/33033348/18525201/18491768/s65_jochen.fries.jpg"}</script></span></span></li><li class="js-paper-rank-work_13996013 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="13996013"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 13996013, container: ".js-paper-rank-work_13996013", }); });</script></li><li class="js-percentile-work_13996013 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 13996013; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = 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style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="13996013"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">15</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="37826" rel="nofollow" href="https://www.academia.edu/Documents/in/Biopsy">Biopsy</a>, <script data-card-contents-for-ri="37826" type="text/json">{"id":37826,"name":"Biopsy","url":"https://www.academia.edu/Documents/in/Biopsy?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="75826" rel="nofollow" href="https://www.academia.edu/Documents/in/Europe">Europe</a>, <script data-card-contents-for-ri="75826" type="text/json">{"id":75826,"name":"Europe","url":"https://www.academia.edu/Documents/in/Europe?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="162159" rel="nofollow" href="https://www.academia.edu/Documents/in/Differential_Diagnosis">Differential Diagnosis</a>, <script data-card-contents-for-ri="162159" type="text/json">{"id":162159,"name":"Differential Diagnosis","url":"https://www.academia.edu/Documents/in/Differential_Diagnosis?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a><script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=13996013]'), work: {"id":13996013,"title":"A web-based pilot study of inter-pathologist reproducibility using the ISHLT 2004 working formulation for biopsy diagnosis of cardiac allograft rejection: The European 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Fries","profile_url":"https://uni-koln.academia.edu/JochenFries?f_ri=194916","photo":"https://0.academia-photos.com/33033348/18525201/18491768/s65_jochen.fries.jpg"}],"research_interests":[{"id":37826,"name":"Biopsy","url":"https://www.academia.edu/Documents/in/Biopsy?f_ri=194916","nofollow":true},{"id":75826,"name":"Europe","url":"https://www.academia.edu/Documents/in/Europe?f_ri=194916","nofollow":true},{"id":162159,"name":"Differential Diagnosis","url":"https://www.academia.edu/Documents/in/Differential_Diagnosis?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":308908,"name":"Pilot study","url":"https://www.academia.edu/Documents/in/Pilot_study?f_ri=194916"},{"id":392828,"name":"Myocardium","url":"https://www.academia.edu/Documents/in/Myocardium?f_ri=194916"},{"id":469105,"name":"Retrospective Studies","url":"https://www.academia.edu/Documents/in/Retrospective_Studies?f_ri=194916"},{"id":549280,"name":"Reproducibility of Results","url":"https://www.academia.edu/Documents/in/Reproducibility_of_Results?f_ri=194916"},{"id":893785,"name":"Graft Rejection","url":"https://www.academia.edu/Documents/in/Graft_Rejection?f_ri=194916"},{"id":945595,"name":"Pilot Projects","url":"https://www.academia.edu/Documents/in/Pilot_Projects?f_ri=194916"},{"id":987931,"name":"Heart Transplantation","url":"https://www.academia.edu/Documents/in/Heart_Transplantation?f_ri=194916"},{"id":1036494,"name":"Heart and Lung Transplantation","url":"https://www.academia.edu/Documents/in/Heart_and_Lung_Transplantation?f_ri=194916"},{"id":1191356,"name":"Internet","url":"https://www.academia.edu/Documents/in/Internet?f_ri=194916"},{"id":2027622,"name":"The Heart","url":"https://www.academia.edu/Documents/in/The_Heart?f_ri=194916"},{"id":2207328,"name":"Heart Diseases","url":"https://www.academia.edu/Documents/in/Heart_Diseases?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_24163160" data-work_id="24163160" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/24163160/Efficient_Source_Separation_Algorithms_for_Acoustic_Fall_Detection_Using_a_Microsoft_Kinect">Efficient Source Separation Algorithms for Acoustic Fall Detection Using a Microsoft Kinect</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Falls have become a common health problem among older adults. In previous study, we proposed an acoustic fall detection system (acoustic FADE) that employed a microphone array and beamforming to provide automatic fall detection. However,... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_24163160" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Falls have become a common health problem among older adults. In previous study, we proposed an acoustic fall detection system (acoustic FADE) that employed a microphone array and beamforming to provide automatic fall detection. However, the previous acoustic FADE had difficulties in detecting the fall signal in environments where interference comes from the fall direction, the number of interferences exceeds FADE's ability to handle or a fall is occluded. To address these issues, in this paper, we propose two blind source separation (BSS) methods for extracting the fall signal out of the interferences to improve the fall classification task. We first propose the single-channel BSS by using nonnegative matrix factorization (NMF) to automatically decompose the mixture into a linear combination of several basis components. Based on the distinct patterns of the bases of falls, we identify them efficiently and then construct the interference free fall signal. Next, we extend the single-channel BSS to the multichannel case through a joint NMF over all channels followed by a delay-and-sum beamformer for additional ambient noise reduction. In our experiments, we used the Microsoft Kinect to collect the acoustic data in realhome environments. The results show that in environments with high interference and background noise levels, the fall detection performance is significantly improved using the proposed BSS approaches.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/24163160" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="52ccfda16aa1e2a88c876722ab8b773d" rel="nofollow" data-download="{"attachment_id":44509310,"asset_id":24163160,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/44509310/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="46589618" href="https://independent.academia.edu/MihailPopescu">Mihail Popescu</a><script data-card-contents-for-user="46589618" type="text/json">{"id":46589618,"first_name":"Mihail","last_name":"Popescu","domain_name":"independent","page_name":"MihailPopescu","display_name":"Mihail Popescu","profile_url":"https://independent.academia.edu/MihailPopescu?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_24163160 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="24163160"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 24163160, container: ".js-paper-rank-work_24163160", }); 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$(".js-view-count[data-work-id=24163160]").text(description); $(".js-view-count-work_24163160").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_24163160").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="24163160"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="428" rel="nofollow" href="https://www.academia.edu/Documents/in/Algorithms">Algorithms</a>, <script data-card-contents-for-ri="428" type="text/json">{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="499" rel="nofollow" href="https://www.academia.edu/Documents/in/Acoustics">Acoustics</a>, <script data-card-contents-for-ri="499" type="text/json">{"id":499,"name":"Acoustics","url":"https://www.academia.edu/Documents/in/Acoustics?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="1131" rel="nofollow" href="https://www.academia.edu/Documents/in/Biomedical_Engineering">Biomedical Engineering</a>, <script data-card-contents-for-ri="1131" type="text/json">{"id":1131,"name":"Biomedical Engineering","url":"https://www.academia.edu/Documents/in/Biomedical_Engineering?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="69542" rel="nofollow" href="https://www.academia.edu/Documents/in/Computer_Simulation">Computer Simulation</a><script data-card-contents-for-ri="69542" type="text/json">{"id":69542,"name":"Computer Simulation","url":"https://www.academia.edu/Documents/in/Computer_Simulation?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=24163160]'), work: {"id":24163160,"title":"Efficient Source Separation Algorithms for Acoustic Fall Detection Using a Microsoft Kinect","created_at":"2016-04-07T06:46:48.058-07:00","url":"https://www.academia.edu/24163160/Efficient_Source_Separation_Algorithms_for_Acoustic_Fall_Detection_Using_a_Microsoft_Kinect?f_ri=194916","dom_id":"work_24163160","summary":"Falls have become a common health problem among older adults. In previous study, we proposed an acoustic fall detection system (acoustic FADE) that employed a microphone array and beamforming to provide automatic fall detection. However, the previous acoustic FADE had difficulties in detecting the fall signal in environments where interference comes from the fall direction, the number of interferences exceeds FADE's ability to handle or a fall is occluded. To address these issues, in this paper, we propose two blind source separation (BSS) methods for extracting the fall signal out of the interferences to improve the fall classification task. We first propose the single-channel BSS by using nonnegative matrix factorization (NMF) to automatically decompose the mixture into a linear combination of several basis components. Based on the distinct patterns of the bases of falls, we identify them efficiently and then construct the interference free fall signal. Next, we extend the single-channel BSS to the multichannel case through a joint NMF over all channels followed by a delay-and-sum beamformer for additional ambient noise reduction. In our experiments, we used the Microsoft Kinect to collect the acoustic data in realhome environments. The results show that in environments with high interference and background noise levels, the fall detection performance is significantly improved using the proposed BSS approaches.","downloadable_attachments":[{"id":44509310,"asset_id":24163160,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":46589618,"first_name":"Mihail","last_name":"Popescu","domain_name":"independent","page_name":"MihailPopescu","display_name":"Mihail Popescu","profile_url":"https://independent.academia.edu/MihailPopescu?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms?f_ri=194916","nofollow":true},{"id":499,"name":"Acoustics","url":"https://www.academia.edu/Documents/in/Acoustics?f_ri=194916","nofollow":true},{"id":1131,"name":"Biomedical Engineering","url":"https://www.academia.edu/Documents/in/Biomedical_Engineering?f_ri=194916","nofollow":true},{"id":69542,"name":"Computer Simulation","url":"https://www.academia.edu/Documents/in/Computer_Simulation?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":991311,"name":"Signal to Noise Ratio","url":"https://www.academia.edu/Documents/in/Signal_to_Noise_Ratio?f_ri=194916"},{"id":1237788,"name":"Electrical And Electronic Engineering","url":"https://www.academia.edu/Documents/in/Electrical_And_Electronic_Engineering?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_23826751" data-work_id="23826751" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/23826751/A_Comparison_Study_of_Multiple_Measures_of_Adherence_to_HIV_Protease_Inhibitors">A Comparison Study of Multiple Measures of Adherence to HIV Protease Inhibitors</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest">Background: Poor adherence to HIV protease inhibitors may compromise the effectiveness of treatment. Few studies have compared methods for measuring adherence or have related adherence measures to a clinical outcome.</div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/23826751" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="3fb3c6929477d768b9bcdd9112c62d33" rel="nofollow" data-download="{"attachment_id":44234249,"asset_id":23826751,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/44234249/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="32848327" href="https://independent.academia.edu/LorenMiller1">Loren Miller</a><script data-card-contents-for-user="32848327" type="text/json">{"id":32848327,"first_name":"Loren","last_name":"Miller","domain_name":"independent","page_name":"LorenMiller1","display_name":"Loren Miller","profile_url":"https://independent.academia.edu/LorenMiller1?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_23826751 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="23826751"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 23826751, container: ".js-paper-rank-work_23826751", }); });</script></li><li class="js-percentile-work_23826751 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 23826751; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_23826751"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_23826751 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="23826751"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 23826751; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=23826751]").text(description); $(".js-view-count-work_23826751").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_23826751").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="23826751"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">15</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="428" rel="nofollow" href="https://www.academia.edu/Documents/in/Algorithms">Algorithms</a>, <script data-card-contents-for-ri="428" type="text/json">{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="8819" rel="nofollow" href="https://www.academia.edu/Documents/in/Medication_Adherence">Medication Adherence</a>, <script data-card-contents-for-ri="8819" type="text/json">{"id":8819,"name":"Medication Adherence","url":"https://www.academia.edu/Documents/in/Medication_Adherence?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="12426" rel="nofollow" href="https://www.academia.edu/Documents/in/Treatment_Outcome">Treatment Outcome</a>, <script data-card-contents-for-ri="12426" type="text/json">{"id":12426,"name":"Treatment Outcome","url":"https://www.academia.edu/Documents/in/Treatment_Outcome?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="99708" rel="nofollow" href="https://www.academia.edu/Documents/in/Clinical">Clinical</a><script data-card-contents-for-ri="99708" type="text/json">{"id":99708,"name":"Clinical","url":"https://www.academia.edu/Documents/in/Clinical?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=23826751]'), work: {"id":23826751,"title":"A Comparison Study of Multiple Measures of Adherence to HIV Protease Inhibitors","created_at":"2016-03-30T08:12:37.620-07:00","url":"https://www.academia.edu/23826751/A_Comparison_Study_of_Multiple_Measures_of_Adherence_to_HIV_Protease_Inhibitors?f_ri=194916","dom_id":"work_23826751","summary":"Background: Poor adherence to HIV protease inhibitors may compromise the effectiveness of treatment. Few studies have compared methods for measuring adherence or have related adherence measures to a clinical outcome.","downloadable_attachments":[{"id":44234249,"asset_id":23826751,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":32848327,"first_name":"Loren","last_name":"Miller","domain_name":"independent","page_name":"LorenMiller1","display_name":"Loren Miller","profile_url":"https://independent.academia.edu/LorenMiller1?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms?f_ri=194916","nofollow":true},{"id":8819,"name":"Medication Adherence","url":"https://www.academia.edu/Documents/in/Medication_Adherence?f_ri=194916","nofollow":true},{"id":12426,"name":"Treatment Outcome","url":"https://www.academia.edu/Documents/in/Treatment_Outcome?f_ri=194916","nofollow":true},{"id":99708,"name":"Clinical","url":"https://www.academia.edu/Documents/in/Clinical?f_ri=194916","nofollow":true},{"id":131185,"name":"Cohort Study","url":"https://www.academia.edu/Documents/in/Cohort_Study?f_ri=194916"},{"id":135005,"name":"Patient Compliance","url":"https://www.academia.edu/Documents/in/Patient_Compliance?f_ri=194916"},{"id":160242,"name":"Hiv Infection","url":"https://www.academia.edu/Documents/in/Hiv_Infection?f_ri=194916"},{"id":177235,"name":"Self-administration","url":"https://www.academia.edu/Documents/in/Self-administration?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":330953,"name":"Longitudinal Studies","url":"https://www.academia.edu/Documents/in/Longitudinal_Studies?f_ri=194916"},{"id":507661,"name":"Medical Electronics","url":"https://www.academia.edu/Documents/in/Medical_Electronics?f_ri=194916"},{"id":549280,"name":"Reproducibility of Results","url":"https://www.academia.edu/Documents/in/Reproducibility_of_Results?f_ri=194916"},{"id":612870,"name":"Psychotic Disorders","url":"https://www.academia.edu/Documents/in/Psychotic_Disorders?f_ri=194916"},{"id":1386625,"name":"Clinical Psychopharmacology","url":"https://www.academia.edu/Documents/in/Clinical_Psychopharmacology?f_ri=194916"},{"id":2249317,"name":"Viral Load","url":"https://www.academia.edu/Documents/in/Viral_Load?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_23061941" data-work_id="23061941" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/23061941/Abnormal_human_behavioral_pattern_detection_in_assisted_living_environments">Abnormal human behavioral pattern detection in assisted living environments</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In recent years, there is a growing interest about assisted living environments especially for the elderly who live alone, due to the increasing number of aged people. In order for them to live safe and healthy, we need to detect abnormal... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_23061941" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In recent years, there is a growing interest about assisted living environments especially for the elderly who live alone, due to the increasing number of aged people. In order for them to live safe and healthy, we need to detect abnormal behavior that may cause severe and emergent situations for the elderly. In this work, we suggest a method that detects abnormal behavior using wireless sensor networks. We model an episode that is a series of events, which includes spatial and temporal information about the subject being monitored. We define a similarity scoring function that compares two episodes taking into consideration temporal aspects. We propose a way to determine a threshold to divide episodes into two groups that reduces wrong classification. Weights on individual functions that consist the similarity function are determined experimentally so that they can produce the good results in terms of area under curve in receiver operating characteristic (ROC) curve.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/23061941" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="6066cbbbd2b203fbdd16f6faf27c88b8" rel="nofollow" data-download="{"attachment_id":43564539,"asset_id":23061941,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/43564539/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="33586977" href="https://independent.academia.edu/VangelisMetsis">Vangelis Metsis</a><script data-card-contents-for-user="33586977" type="text/json">{"id":33586977,"first_name":"Vangelis","last_name":"Metsis","domain_name":"independent","page_name":"VangelisMetsis","display_name":"Vangelis Metsis","profile_url":"https://independent.academia.edu/VangelisMetsis?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_23061941 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="23061941"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 23061941, container: ".js-paper-rank-work_23061941", }); });</script></li><li class="js-percentile-work_23061941 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 23061941; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_23061941"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_23061941 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="23061941"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 23061941; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=23061941]").text(description); $(".js-view-count-work_23061941").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_23061941").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="23061941"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="87818" rel="nofollow" href="https://www.academia.edu/Documents/in/Human_behavior">Human behavior</a>, <script data-card-contents-for-ri="87818" type="text/json">{"id":87818,"name":"Human behavior","url":"https://www.academia.edu/Documents/in/Human_behavior?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="106145" rel="nofollow" href="https://www.academia.edu/Documents/in/Classification">Classification</a>, <script data-card-contents-for-ri="106145" type="text/json">{"id":106145,"name":"Classification","url":"https://www.academia.edu/Documents/in/Classification?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a>, <script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="1211847" rel="nofollow" href="https://www.academia.edu/Documents/in/Wireless_Sensor_Network">Wireless Sensor Network</a><script data-card-contents-for-ri="1211847" type="text/json">{"id":1211847,"name":"Wireless Sensor Network","url":"https://www.academia.edu/Documents/in/Wireless_Sensor_Network?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=23061941]'), work: {"id":23061941,"title":"Abnormal human behavioral pattern detection in assisted living environments","created_at":"2016-03-09T16:33:25.528-08:00","url":"https://www.academia.edu/23061941/Abnormal_human_behavioral_pattern_detection_in_assisted_living_environments?f_ri=194916","dom_id":"work_23061941","summary":"In recent years, there is a growing interest about assisted living environments especially for the elderly who live alone, due to the increasing number of aged people. In order for them to live safe and healthy, we need to detect abnormal behavior that may cause severe and emergent situations for the elderly. In this work, we suggest a method that detects abnormal behavior using wireless sensor networks. We model an episode that is a series of events, which includes spatial and temporal information about the subject being monitored. We define a similarity scoring function that compares two episodes taking into consideration temporal aspects. We propose a way to determine a threshold to divide episodes into two groups that reduces wrong classification. Weights on individual functions that consist the similarity function are determined experimentally so that they can produce the good results in terms of area under curve in receiver operating characteristic (ROC) curve.","downloadable_attachments":[{"id":43564539,"asset_id":23061941,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33586977,"first_name":"Vangelis","last_name":"Metsis","domain_name":"independent","page_name":"VangelisMetsis","display_name":"Vangelis Metsis","profile_url":"https://independent.academia.edu/VangelisMetsis?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":87818,"name":"Human behavior","url":"https://www.academia.edu/Documents/in/Human_behavior?f_ri=194916","nofollow":true},{"id":106145,"name":"Classification","url":"https://www.academia.edu/Documents/in/Classification?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":1211847,"name":"Wireless Sensor Network","url":"https://www.academia.edu/Documents/in/Wireless_Sensor_Network?f_ri=194916","nofollow":true},{"id":1309706,"name":"Area Under Curve","url":"https://www.academia.edu/Documents/in/Area_Under_Curve?f_ri=194916"},{"id":1359009,"name":"Score Function","url":"https://www.academia.edu/Documents/in/Score_Function?f_ri=194916"},{"id":1914590,"name":"Threshold Value","url":"https://www.academia.edu/Documents/in/Threshold_Value?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_23000954" data-work_id="23000954" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/23000954/Comparison_of_diagnostic_accuracy_of_digital_imaging_by_using_CCD_and_CMOS_APS_sensors_with_E_speed_film_in_the_detection_of_periapical_bony_lesions">Comparison of diagnostic accuracy of digital imaging by using CCD and CMOS-APS sensors with E-speed film in the detection of periapical bony lesions</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The identification and interpretation of periapical bony lesions is important for accurate diagnosis and treatment. Diagnostic accuracy may depend on the extent of bony involvement of the lesion as well as on the type of diagnostic... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_23000954" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The identification and interpretation of periapical bony lesions is important for accurate diagnosis and treatment. Diagnostic accuracy may depend on the extent of bony involvement of the lesion as well as on the type of diagnostic imaging system used. A recent advance in imaging technology is direct digital imaging (DDI). The standard DDI system uses a sensor containing a charge-coupled device (CCD) that produces an image as an array of pixels displayed on a computer monitor. The computerized image can be manipulated and enhanced with computer software. Advantages of DDI include a 50% reduction in radiation exposure, 1 immediate image generation, image manipulation, elimination of chemical processing of radiographs, and enhancement of one's ability to educate patients.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/23000954" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="eedd3aa78ae984429a1d3d8a0eda1c4f" rel="nofollow" data-download="{"attachment_id":43514536,"asset_id":23000954,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/43514536/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="44615002" href="https://independent.academia.edu/JamesGeist">James Geist</a><script data-card-contents-for-user="44615002" type="text/json">{"id":44615002,"first_name":"James","last_name":"Geist","domain_name":"independent","page_name":"JamesGeist","display_name":"James Geist","profile_url":"https://independent.academia.edu/JamesGeist?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_23000954 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="23000954"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 23000954, container: ".js-paper-rank-work_23000954", }); 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$(".js-view-count[data-work-id=23000954]").text(description); $(".js-view-count-work_23000954").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_23000954").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="23000954"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">16</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="596" rel="nofollow" href="https://www.academia.edu/Documents/in/Dentistry">Dentistry</a>, <script data-card-contents-for-ri="596" type="text/json">{"id":596,"name":"Dentistry","url":"https://www.academia.edu/Documents/in/Dentistry?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="640" rel="nofollow" href="https://www.academia.edu/Documents/in/Radiology">Radiology</a>, <script data-card-contents-for-ri="640" type="text/json">{"id":640,"name":"Radiology","url":"https://www.academia.edu/Documents/in/Radiology?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="5187" rel="nofollow" href="https://www.academia.edu/Documents/in/Statistical_Analysis">Statistical Analysis</a>, <script data-card-contents-for-ri="5187" type="text/json">{"id":5187,"name":"Statistical Analysis","url":"https://www.academia.edu/Documents/in/Statistical_Analysis?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="78190" rel="nofollow" href="https://www.academia.edu/Documents/in/Trabecular_Bone">Trabecular Bone</a><script data-card-contents-for-ri="78190" type="text/json">{"id":78190,"name":"Trabecular Bone","url":"https://www.academia.edu/Documents/in/Trabecular_Bone?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=23000954]'), work: {"id":23000954,"title":"Comparison of diagnostic accuracy of digital imaging by using CCD and CMOS-APS sensors with E-speed film in the detection of periapical bony lesions","created_at":"2016-03-08T10:21:50.955-08:00","url":"https://www.academia.edu/23000954/Comparison_of_diagnostic_accuracy_of_digital_imaging_by_using_CCD_and_CMOS_APS_sensors_with_E_speed_film_in_the_detection_of_periapical_bony_lesions?f_ri=194916","dom_id":"work_23000954","summary":"The identification and interpretation of periapical bony lesions is important for accurate diagnosis and treatment. Diagnostic accuracy may depend on the extent of bony involvement of the lesion as well as on the type of diagnostic imaging system used. A recent advance in imaging technology is direct digital imaging (DDI). The standard DDI system uses a sensor containing a charge-coupled device (CCD) that produces an image as an array of pixels displayed on a computer monitor. The computerized image can be manipulated and enhanced with computer software. Advantages of DDI include a 50% reduction in radiation exposure, 1 immediate image generation, image manipulation, elimination of chemical processing of radiographs, and enhancement of one's ability to educate patients.","downloadable_attachments":[{"id":43514536,"asset_id":23000954,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":44615002,"first_name":"James","last_name":"Geist","domain_name":"independent","page_name":"JamesGeist","display_name":"James Geist","profile_url":"https://independent.academia.edu/JamesGeist?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":596,"name":"Dentistry","url":"https://www.academia.edu/Documents/in/Dentistry?f_ri=194916","nofollow":true},{"id":640,"name":"Radiology","url":"https://www.academia.edu/Documents/in/Radiology?f_ri=194916","nofollow":true},{"id":5187,"name":"Statistical Analysis","url":"https://www.academia.edu/Documents/in/Statistical_Analysis?f_ri=194916","nofollow":true},{"id":78190,"name":"Trabecular Bone","url":"https://www.academia.edu/Documents/in/Trabecular_Bone?f_ri=194916","nofollow":true},{"id":110415,"name":"Oral Surgery","url":"https://www.academia.edu/Documents/in/Oral_Surgery?f_ri=194916"},{"id":125564,"name":"Statistical Significance","url":"https://www.academia.edu/Documents/in/Statistical_Significance?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":295775,"name":"Tooth Root","url":"https://www.academia.edu/Documents/in/Tooth_Root?f_ri=194916"},{"id":372652,"name":"Endodontics","url":"https://www.academia.edu/Documents/in/Endodontics?f_ri=194916"},{"id":413194,"name":"Analysis of Variance","url":"https://www.academia.edu/Documents/in/Analysis_of_Variance?f_ri=194916"},{"id":538554,"name":"Study design","url":"https://www.academia.edu/Documents/in/Study_design?f_ri=194916"},{"id":600686,"name":"Cortical Bone","url":"https://www.academia.edu/Documents/in/Cortical_Bone?f_ri=194916"},{"id":675221,"name":"Diagnostic Accuracy","url":"https://www.academia.edu/Documents/in/Diagnostic_Accuracy?f_ri=194916"},{"id":907382,"name":"Digital Image","url":"https://www.academia.edu/Documents/in/Digital_Image?f_ri=194916"},{"id":1127828,"name":"Life Span","url":"https://www.academia.edu/Documents/in/Life_Span?f_ri=194916"},{"id":1145520,"name":"Equipment Design","url":"https://www.academia.edu/Documents/in/Equipment_Design?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_21121411" data-work_id="21121411" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/21121411/A_risk_score_to_predict_need_for_treatment_for_uppergastrointestinal_haemorrhage">A risk score to predict need for treatment for uppergastrointestinal haemorrhage</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Current risk-stratification systems for patients with acute upper-gastrointestinal bleeding discriminate between patients at high or low risks of dying or rebleeding. We therefore developed and prospectively validated a risk score to... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_21121411" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Current risk-stratification systems for patients with acute upper-gastrointestinal bleeding discriminate between patients at high or low risks of dying or rebleeding. We therefore developed and prospectively validated a risk score to identify a patient&amp;#39;s need for treatment. Our first study used data from 1748 patients admitted for upper-gastrointestinal haemorrhage. By logistic regression, we derived a risk score that predicts patients&amp;#39; risks of needing blood transfusion or intervention to control bleeding, rebleeding, or dying. From this score, we developed a simplified fast-track screen for use at initial presentation. In a second study, we prospectively validated this score using receiver operating characteristic (ROC) curves--a measure of the validity of a scoring system--and chi2 goodness-of-fit testing with data from 197 patients. We also validated the quicker screening tool. We calculated risk scores from patients&amp;#39; admission haemoglobin, blood urea, pulse, and systolic blood pressure, as well as presentation with syncope or melaena, and evidence of hepatic disease or cardiac failure. The score discriminated well with a ROC curve area of 0.92 (95% CI 0.88-0.95). The score was well calibrated for patients needing treatment (p=0.84). Our score identified patients at low or high risk of needing treatment to manage their bleeding. This score should assist the clinical management of patients presenting with upper-gastrointestinal haemorrhage, but requires external validation.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/21121411" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="6f3e535e68d02ed93c19874796c75fc0" rel="nofollow" data-download="{"attachment_id":41911177,"asset_id":21121411,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/41911177/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="42321354" href="https://independent.academia.edu/OBlatchford">O. Blatchford</a><script data-card-contents-for-user="42321354" type="text/json">{"id":42321354,"first_name":"O.","last_name":"Blatchford","domain_name":"independent","page_name":"OBlatchford","display_name":"O. Blatchford","profile_url":"https://independent.academia.edu/OBlatchford?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_21121411 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="21121411"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 21121411, container: ".js-paper-rank-work_21121411", }); });</script></li><li class="js-percentile-work_21121411 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 21121411; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_21121411"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_21121411 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="21121411"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 21121411; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=21121411]").text(description); $(".js-view-count-work_21121411").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_21121411").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="21121411"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">11</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="62112" rel="nofollow" href="https://www.academia.edu/Documents/in/Prospective_studies">Prospective studies</a>, <script data-card-contents-for-ri="62112" type="text/json">{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="81559" rel="nofollow" href="https://www.academia.edu/Documents/in/Scotland">Scotland</a>, <script data-card-contents-for-ri="81559" type="text/json">{"id":81559,"name":"Scotland","url":"https://www.academia.edu/Documents/in/Scotland?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="88321" rel="nofollow" href="https://www.academia.edu/Documents/in/Blood_Pressure">Blood Pressure</a>, <script data-card-contents-for-ri="88321" type="text/json">{"id":88321,"name":"Blood Pressure","url":"https://www.academia.edu/Documents/in/Blood_Pressure?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="192721" rel="nofollow" href="https://www.academia.edu/Documents/in/Risk_factors">Risk factors</a><script data-card-contents-for-ri="192721" type="text/json">{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=21121411]'), work: {"id":21121411,"title":"A risk score to predict need for treatment for uppergastrointestinal haemorrhage","created_at":"2016-01-29T04:11:11.077-08:00","url":"https://www.academia.edu/21121411/A_risk_score_to_predict_need_for_treatment_for_uppergastrointestinal_haemorrhage?f_ri=194916","dom_id":"work_21121411","summary":"Current risk-stratification systems for patients with acute upper-gastrointestinal bleeding discriminate between patients at high or low risks of dying or rebleeding. We therefore developed and prospectively validated a risk score to identify a patient\u0026amp;#39;s need for treatment. Our first study used data from 1748 patients admitted for upper-gastrointestinal haemorrhage. By logistic regression, we derived a risk score that predicts patients\u0026amp;#39; risks of needing blood transfusion or intervention to control bleeding, rebleeding, or dying. From this score, we developed a simplified fast-track screen for use at initial presentation. In a second study, we prospectively validated this score using receiver operating characteristic (ROC) curves--a measure of the validity of a scoring system--and chi2 goodness-of-fit testing with data from 197 patients. We also validated the quicker screening tool. We calculated risk scores from patients\u0026amp;#39; admission haemoglobin, blood urea, pulse, and systolic blood pressure, as well as presentation with syncope or melaena, and evidence of hepatic disease or cardiac failure. The score discriminated well with a ROC curve area of 0.92 (95% CI 0.88-0.95). The score was well calibrated for patients needing treatment (p=0.84). Our score identified patients at low or high risk of needing treatment to manage their bleeding. This score should assist the clinical management of patients presenting with upper-gastrointestinal haemorrhage, but requires external validation.","downloadable_attachments":[{"id":41911177,"asset_id":21121411,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":42321354,"first_name":"O.","last_name":"Blatchford","domain_name":"independent","page_name":"OBlatchford","display_name":"O. Blatchford","profile_url":"https://independent.academia.edu/OBlatchford?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":62112,"name":"Prospective studies","url":"https://www.academia.edu/Documents/in/Prospective_studies?f_ri=194916","nofollow":true},{"id":81559,"name":"Scotland","url":"https://www.academia.edu/Documents/in/Scotland?f_ri=194916","nofollow":true},{"id":88321,"name":"Blood Pressure","url":"https://www.academia.edu/Documents/in/Blood_Pressure?f_ri=194916","nofollow":true},{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":243629,"name":"Lancet","url":"https://www.academia.edu/Documents/in/Lancet?f_ri=194916"},{"id":620049,"name":"Risk Factors","url":"https://www.academia.edu/Documents/in/Risk_Factors-1?f_ri=194916"},{"id":627890,"name":"Blood Transfusion","url":"https://www.academia.edu/Documents/in/Blood_Transfusion?f_ri=194916"},{"id":1311261,"name":"Hemoglobins","url":"https://www.academia.edu/Documents/in/Hemoglobins?f_ri=194916"},{"id":1318932,"name":"Predictive value of tests","url":"https://www.academia.edu/Documents/in/Predictive_value_of_tests?f_ri=194916"},{"id":1937356,"name":"Risk Score","url":"https://www.academia.edu/Documents/in/Risk_Score?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_17418485 coauthored" data-work_id="17418485" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/17418485/Clinical_prediction_models_for_bronchopulmonary_dysplasia_a_systematic_review_and_external_validation_study">Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Background: Bronchopulmonary dysplasia (BPD) is a common complication of preterm birth. Very different models using clinical parameters at an early postnatal age to predict BPD have been developed with little extensive quantitative... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_17418485" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Background: Bronchopulmonary dysplasia (BPD) is a common complication of preterm birth. Very different models using clinical parameters at an early postnatal age to predict BPD have been developed with little extensive quantitative validation. The objective of this study is to review and validate clinical prediction models for BPD.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/17418485" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="f72bfc01bce4c042df7fb1d692b8cd18" rel="nofollow" data-download="{"attachment_id":39496496,"asset_id":17418485,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/39496496/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="37144812" href="https://independent.academia.edu/WesOnland">Wes Onland</a><script data-card-contents-for-user="37144812" type="text/json">{"id":37144812,"first_name":"Wes","last_name":"Onland","domain_name":"independent","page_name":"WesOnland","display_name":"Wes Onland","profile_url":"https://independent.academia.edu/WesOnland?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-17418485">+3</span><div class="hidden js-additional-users-17418485"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://umcutrecht.academia.edu/ThomasDebray">Thomas Debray</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://uwa.academia.edu/JanePillow">Jane Pillow</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://unicatt.academia.edu/GiovanniVento">Giovanni Vento</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-17418485'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-17418485').html(); 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container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_17418485 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="17418485"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 17418485; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=17418485]").text(description); $(".js-view-count-work_17418485").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_17418485").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="17418485"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">14</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="47155" rel="nofollow" href="https://www.academia.edu/Documents/in/Birth_Weight">Birth Weight</a>, <script data-card-contents-for-ri="47155" type="text/json">{"id":47155,"name":"Birth Weight","url":"https://www.academia.edu/Documents/in/Birth_Weight?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="67133" rel="nofollow" href="https://www.academia.edu/Documents/in/Anoxia">Anoxia</a>, <script data-card-contents-for-ri="67133" type="text/json">{"id":67133,"name":"Anoxia","url":"https://www.academia.edu/Documents/in/Anoxia?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="89805" rel="nofollow" href="https://www.academia.edu/Documents/in/Weight_Loss">Weight Loss</a>, <script data-card-contents-for-ri="89805" type="text/json">{"id":89805,"name":"Weight Loss","url":"https://www.academia.edu/Documents/in/Weight_Loss?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="96893" rel="nofollow" href="https://www.academia.edu/Documents/in/Calibration">Calibration</a><script data-card-contents-for-ri="96893" type="text/json">{"id":96893,"name":"Calibration","url":"https://www.academia.edu/Documents/in/Calibration?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=17418485]'), work: {"id":17418485,"title":"Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study","created_at":"2015-10-28T07:47:08.371-07:00","url":"https://www.academia.edu/17418485/Clinical_prediction_models_for_bronchopulmonary_dysplasia_a_systematic_review_and_external_validation_study?f_ri=194916","dom_id":"work_17418485","summary":"Background: Bronchopulmonary dysplasia (BPD) is a common complication of preterm birth. Very different models using clinical parameters at an early postnatal age to predict BPD have been developed with little extensive quantitative validation. The objective of this study is to review and validate clinical prediction models for BPD.","downloadable_attachments":[{"id":39496496,"asset_id":17418485,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":37144812,"first_name":"Wes","last_name":"Onland","domain_name":"independent","page_name":"WesOnland","display_name":"Wes Onland","profile_url":"https://independent.academia.edu/WesOnland?f_ri=194916","photo":"/images/s65_no_pic.png"},{"id":19602482,"first_name":"Thomas","last_name":"Debray","domain_name":"umcutrecht","page_name":"ThomasDebray","display_name":"Thomas Debray","profile_url":"https://umcutrecht.academia.edu/ThomasDebray?f_ri=194916","photo":"https://0.academia-photos.com/19602482/5465545/6230848/s65_thomas.debray.jpg"},{"id":21696307,"first_name":"Jane","last_name":"Pillow","domain_name":"uwa","page_name":"JanePillow","display_name":"Jane Pillow","profile_url":"https://uwa.academia.edu/JanePillow?f_ri=194916","photo":"/images/s65_no_pic.png"},{"id":37285789,"first_name":"Giovanni","last_name":"Vento","domain_name":"unicatt","page_name":"GiovanniVento","display_name":"Giovanni Vento","profile_url":"https://unicatt.academia.edu/GiovanniVento?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":47155,"name":"Birth Weight","url":"https://www.academia.edu/Documents/in/Birth_Weight?f_ri=194916","nofollow":true},{"id":67133,"name":"Anoxia","url":"https://www.academia.edu/Documents/in/Anoxia?f_ri=194916","nofollow":true},{"id":89805,"name":"Weight Loss","url":"https://www.academia.edu/Documents/in/Weight_Loss?f_ri=194916","nofollow":true},{"id":96893,"name":"Calibration","url":"https://www.academia.edu/Documents/in/Calibration?f_ri=194916","nofollow":true},{"id":134346,"name":"Infant","url":"https://www.academia.edu/Documents/in/Infant?f_ri=194916"},{"id":194916,"name":"ROC 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tests","url":"https://www.academia.edu/Documents/in/Predictive_value_of_tests?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_18664853" data-work_id="18664853" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/18664853/The_Role_of_Cardiac_Risk_Factor_Burden_in_Diagnosing_Acute_Coronary_Syndromes_in_the_Emergency_Department_Setting">The Role of Cardiac Risk Factor Burden in Diagnosing Acute Coronary Syndromes in the Emergency Department Setting</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest">and The Cleveland Clinic Foundation, Cleveland, OH (Peacock).</div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/18664853" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="6774d7628e81ee529c8bb58923f31268" rel="nofollow" data-download="{"attachment_id":40189455,"asset_id":18664853,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/40189455/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" 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href="https://www.academia.edu/Documents/in/Electrocardiography">Electrocardiography</a>, <script data-card-contents-for-ri="39000" type="text/json">{"id":39000,"name":"Electrocardiography","url":"https://www.academia.edu/Documents/in/Electrocardiography?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="192721" rel="nofollow" href="https://www.academia.edu/Documents/in/Risk_factors">Risk factors</a>, <script data-card-contents-for-ri="192721" type="text/json">{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a>, <script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="209856" rel="nofollow" href="https://www.academia.edu/Documents/in/Registries">Registries</a><script data-card-contents-for-ri="209856" type="text/json">{"id":209856,"name":"Registries","url":"https://www.academia.edu/Documents/in/Registries?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=18664853]'), work: {"id":18664853,"title":"The Role of Cardiac Risk Factor Burden in Diagnosing Acute Coronary Syndromes in the Emergency Department Setting","created_at":"2015-11-19T19:03:47.007-08:00","url":"https://www.academia.edu/18664853/The_Role_of_Cardiac_Risk_Factor_Burden_in_Diagnosing_Acute_Coronary_Syndromes_in_the_Emergency_Department_Setting?f_ri=194916","dom_id":"work_18664853","summary":"and The Cleveland Clinic Foundation, Cleveland, OH (Peacock).","downloadable_attachments":[{"id":40189455,"asset_id":18664853,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":38739872,"first_name":"Judd","last_name":"Hollander","domain_name":"independent","page_name":"JuddHollander","display_name":"Judd Hollander","profile_url":"https://independent.academia.edu/JuddHollander?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":39000,"name":"Electrocardiography","url":"https://www.academia.edu/Documents/in/Electrocardiography?f_ri=194916","nofollow":true},{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":209856,"name":"Registries","url":"https://www.academia.edu/Documents/in/Registries?f_ri=194916","nofollow":true},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916"},{"id":300876,"name":"Acute Coronary Syndrome","url":"https://www.academia.edu/Documents/in/Acute_Coronary_Syndrome?f_ri=194916"},{"id":398808,"name":"Coronary heart disease","url":"https://www.academia.edu/Documents/in/Coronary_heart_disease?f_ri=194916"},{"id":568482,"name":"Biological markers","url":"https://www.academia.edu/Documents/in/Biological_markers?f_ri=194916"},{"id":620049,"name":"Risk Factors","url":"https://www.academia.edu/Documents/in/Risk_Factors-1?f_ri=194916"},{"id":1294607,"name":"Logistic Models","url":"https://www.academia.edu/Documents/in/Logistic_Models?f_ri=194916"},{"id":1435137,"name":"Emergency Department","url":"https://www.academia.edu/Documents/in/Emergency_Department?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_71532347" data-work_id="71532347" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/71532347/An_analysis_of_co_occurrence_texture_statistics_as_a_function_of_grey_level_quantization">An analysis of co-occurrence texture statistics as a function of grey level quantization</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this paper, the effect of grey level quantization on the ability of co-occurrence probability statistics to classify natural textures is studied. Generally, as a function of increasing grey levels, many of the statistics demonstrate a... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_71532347" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this paper, the effect of grey level quantization on the ability of co-occurrence probability statistics to classify natural textures is studied. Generally, as a function of increasing grey levels, many of the statistics demonstrate a decrease in classification ability while a few maintain constant classification accuracy. None of the individual statistics show increasing classification accuracy throughout all grey levels. Correlation analysis is used to rationalize a preferred subset of statistics. The preferred statistics set (contrast, correlation, and ...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/71532347" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8a79f4d5698d2f84a3f5b85964081a32" rel="nofollow" data-download="{"attachment_id":80834250,"asset_id":71532347,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/80834250/download_file?st=MTc0MDU1Mjc0NCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="60713983" href="https://independent.academia.edu/WanderJoseGomez">Wander Jose Gomez</a><script data-card-contents-for-user="60713983" type="text/json">{"id":60713983,"first_name":"Wander Jose","last_name":"Gomez","domain_name":"independent","page_name":"WanderJoseGomez","display_name":"Wander Jose Gomez","profile_url":"https://independent.academia.edu/WanderJoseGomez?f_ri=194916","photo":"https://0.academia-photos.com/60713983/15802895/16325101/s65_wander_jose.gomez.jpg"}</script></span></span></li><li class="js-paper-rank-work_71532347 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="71532347"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 71532347, container: ".js-paper-rank-work_71532347", }); 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$(".js-view-count[data-work-id=71532347]").text(description); $(".js-view-count-work_71532347").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_71532347").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="71532347"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">14</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="48" rel="nofollow" href="https://www.academia.edu/Documents/in/Engineering">Engineering</a>, <script data-card-contents-for-ri="48" type="text/json">{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="428" rel="nofollow" href="https://www.academia.edu/Documents/in/Algorithms">Algorithms</a>, <script data-card-contents-for-ri="428" type="text/json">{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="1185" rel="nofollow" href="https://www.academia.edu/Documents/in/Image_Processing">Image Processing</a>, <script data-card-contents-for-ri="1185" type="text/json">{"id":1185,"name":"Image Processing","url":"https://www.academia.edu/Documents/in/Image_Processing?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="2008" rel="nofollow" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a><script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=71532347]'), work: {"id":71532347,"title":"An analysis of co-occurrence texture statistics as a function of grey level quantization","created_at":"2022-02-14T11:36:15.926-08:00","url":"https://www.academia.edu/71532347/An_analysis_of_co_occurrence_texture_statistics_as_a_function_of_grey_level_quantization?f_ri=194916","dom_id":"work_71532347","summary":"In this paper, the effect of grey level quantization on the ability of co-occurrence probability statistics to classify natural textures is studied. Generally, as a function of increasing grey levels, many of the statistics demonstrate a decrease in classification ability while a few maintain constant classification accuracy. None of the individual statistics show increasing classification accuracy throughout all grey levels. Correlation analysis is used to rationalize a preferred subset of statistics. The preferred statistics set (contrast, correlation, and ...","downloadable_attachments":[{"id":80834250,"asset_id":71532347,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":60713983,"first_name":"Wander Jose","last_name":"Gomez","domain_name":"independent","page_name":"WanderJoseGomez","display_name":"Wander Jose Gomez","profile_url":"https://independent.academia.edu/WanderJoseGomez?f_ri=194916","photo":"https://0.academia-photos.com/60713983/15802895/16325101/s65_wander_jose.gomez.jpg"}],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=194916","nofollow":true},{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms?f_ri=194916","nofollow":true},{"id":1185,"name":"Image Processing","url":"https://www.academia.edu/Documents/in/Image_Processing?f_ri=194916","nofollow":true},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=194916","nofollow":true},{"id":29759,"name":"Sea Ice","url":"https://www.academia.edu/Documents/in/Sea_Ice?f_ri=194916"},{"id":162010,"name":"Geomatic Engineering","url":"https://www.academia.edu/Documents/in/Geomatic_Engineering?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":410595,"name":"Correlation Analysis","url":"https://www.academia.edu/Documents/in/Correlation_Analysis?f_ri=194916"},{"id":464260,"name":"Gray Level Co-occurrence Matrix","url":"https://www.academia.edu/Documents/in/Gray_Level_Co-occurrence_Matrix?f_ri=194916"},{"id":749302,"name":"Indexation","url":"https://www.academia.edu/Documents/in/Indexation?f_ri=194916"},{"id":1309706,"name":"Area Under Curve","url":"https://www.academia.edu/Documents/in/Area_Under_Curve?f_ri=194916"},{"id":1425602,"name":"Classification Accuracy","url":"https://www.academia.edu/Documents/in/Classification_Accuracy?f_ri=194916"},{"id":1555442,"name":"Feature Space","url":"https://www.academia.edu/Documents/in/Feature_Space?f_ri=194916"},{"id":2847999,"name":"Breast Neoplasms","url":"https://www.academia.edu/Documents/in/Breast_Neoplasms?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_68090283" data-work_id="68090283" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/68090283/Brief_cognitive_battery_in_the_diagnosis_of_mild_Alzheimers_disease_in_subjects_with_medium_and_high_levels_of_education">Brief cognitive battery in the diagnosis of mild Alzheimer's disease in subjects with medium and high levels of education</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">There has been an increasing trend to utilize short cognitive batteries for the diagnosis of dementia. Most of these batteries have been designed in countries with high standards of education and are less suitable for populations with low... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_68090283" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">There has been an increasing trend to utilize short cognitive batteries for the diagnosis of dementia. Most of these batteries have been designed in countries with high standards of education and are less suitable for populations with low levels of education. We developed a battery that has been previously shown to be highly accurate in the diagnosis of dementia in individuals with low levels of education. The accuracy of this battery for patients with higher levels of education is unknown. Objectives: To evaluate the accuracy of a brief cognitive battery in the diagnosis of Alzheimer&#39;s disease (AD) in subjects with medium and high levels of schooling, and to develop a mathematical model that includes the most discriminative tests. Methods: Seventy-three mildly demented patients with probable AD and 94 control subjects were evaluated. Sixty patients and 60 controls were randomly selected to generate a mathematical model including the most discriminative tests of the battery usin...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/68090283" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="95f29c029ca5e5757a02e508d9114d96" rel="nofollow" data-download="{"attachment_id":78691093,"asset_id":68090283,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/78691093/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="118460954" href="https://independent.academia.edu/TeresaCarthery">Teresa Carthery</a><script data-card-contents-for-user="118460954" type="text/json">{"id":118460954,"first_name":"Teresa","last_name":"Carthery","domain_name":"independent","page_name":"TeresaCarthery","display_name":"Teresa Carthery","profile_url":"https://independent.academia.edu/TeresaCarthery?f_ri=194916","photo":"https://0.academia-photos.com/118460954/100214450/89357227/s65_teresa.carthery.jpeg"}</script></span></span></li><li class="js-paper-rank-work_68090283 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="68090283"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 68090283, container: ".js-paper-rank-work_68090283", }); });</script></li><li class="js-percentile-work_68090283 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 68090283; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_68090283"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_68090283 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="68090283"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 68090283; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=68090283]").text(description); $(".js-view-count-work_68090283").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_68090283").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="68090283"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="221" rel="nofollow" href="https://www.academia.edu/Documents/in/Psychology">Psychology</a>, <script data-card-contents-for-ri="221" type="text/json">{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="26327" rel="nofollow" href="https://www.academia.edu/Documents/in/Medicine">Medicine</a>, <script data-card-contents-for-ri="26327" type="text/json">{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="32433" rel="nofollow" href="https://www.academia.edu/Documents/in/Logistic_Regression">Logistic Regression</a>, <script data-card-contents-for-ri="32433" type="text/json">{"id":32433,"name":"Logistic Regression","url":"https://www.academia.edu/Documents/in/Logistic_Regression?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a><script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=68090283]'), work: {"id":68090283,"title":"Brief cognitive battery in the diagnosis of mild Alzheimer's disease in subjects with medium and high levels of education","created_at":"2022-01-14T03:47:57.900-08:00","url":"https://www.academia.edu/68090283/Brief_cognitive_battery_in_the_diagnosis_of_mild_Alzheimers_disease_in_subjects_with_medium_and_high_levels_of_education?f_ri=194916","dom_id":"work_68090283","summary":"There has been an increasing trend to utilize short cognitive batteries for the diagnosis of dementia. Most of these batteries have been designed in countries with high standards of education and are less suitable for populations with low levels of education. We developed a battery that has been previously shown to be highly accurate in the diagnosis of dementia in individuals with low levels of education. The accuracy of this battery for patients with higher levels of education is unknown. Objectives: To evaluate the accuracy of a brief cognitive battery in the diagnosis of Alzheimer\u0026#39;s disease (AD) in subjects with medium and high levels of schooling, and to develop a mathematical model that includes the most discriminative tests. Methods: Seventy-three mildly demented patients with probable AD and 94 control subjects were evaluated. Sixty patients and 60 controls were randomly selected to generate a mathematical model including the most discriminative tests of the battery usin...","downloadable_attachments":[{"id":78691093,"asset_id":68090283,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":118460954,"first_name":"Teresa","last_name":"Carthery","domain_name":"independent","page_name":"TeresaCarthery","display_name":"Teresa Carthery","profile_url":"https://independent.academia.edu/TeresaCarthery?f_ri=194916","photo":"https://0.academia-photos.com/118460954/100214450/89357227/s65_teresa.carthery.jpeg"}],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=194916","nofollow":true},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine?f_ri=194916","nofollow":true},{"id":32433,"name":"Logistic Regression","url":"https://www.academia.edu/Documents/in/Logistic_Regression?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":291387,"name":"Mathematical Model","url":"https://www.academia.edu/Documents/in/Mathematical_Model?f_ri=194916"},{"id":1120234,"name":"Alzheimer Disease","url":"https://www.academia.edu/Documents/in/Alzheimer_Disease?f_ri=194916"},{"id":2467548,"name":"Neuropsychological Tests","url":"https://www.academia.edu/Documents/in/Neuropsychological_Tests?f_ri=194916"},{"id":2736714,"name":"Test Methods","url":"https://www.academia.edu/Documents/in/Test_Methods?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_66762509" data-work_id="66762509" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/66762509/The_glycolyzer_Automated_glycan_annotation_software_for_high_performance_mass_spectrometry_and_its_application_to_ovarian_cancer_glycan_biomarker_discovery">The glycolyzer: Automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Human serum glycomics is a promising method for finding cancer biomarkers but often lacks the tools for streamlined data analysis. The Glycolyzer software incorporates a suite of analytic tools capable of identifying informative glycan... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_66762509" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Human serum glycomics is a promising method for finding cancer biomarkers but often lacks the tools for streamlined data analysis. The Glycolyzer software incorporates a suite of analytic tools capable of identifying informative glycan peaks out of raw mass spectrometry data. As a demonstration of its utility, the program was used to identify putative biomarkers for epithelial ovarian cancer from a human serum sample set. A randomized, blocked and blinded experimental design was used on a discovery set consisting of 46 cases and 48 controls. Retrosynthetic glycan libraries were used for data analysis and several significant candidate glycan biomarkers were discovered via hypothesis testing. The significant glycans were attributed to a glycan family based on glycan composition relationships and incorporated into a linear classifier motif test. The motif test was then applied to the discovery set to evaluate the disease state discrimination performance. The test provided strongly predictive results based on receiver operator characteristic curve analysis. The area under the receiver operator characteristic curve was 0.93. Using the Glycolyzer software, we were able to identify a set of glycan biomarkers that highly discriminate between cases and controls, and are ready to be formally validated in subsequent studies.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/66762509" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="dd18046bd2f2e54e9eb7e55d1bc664fe" rel="nofollow" data-download="{"attachment_id":77829164,"asset_id":66762509,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/77829164/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="20904451" href="https://independent.academia.edu/AndresGuerrero7">Andres Guerrero</a><script data-card-contents-for-user="20904451" type="text/json">{"id":20904451,"first_name":"Andres","last_name":"Guerrero","domain_name":"independent","page_name":"AndresGuerrero7","display_name":"Andres Guerrero","profile_url":"https://independent.academia.edu/AndresGuerrero7?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_66762509 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="66762509"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 66762509, container: ".js-paper-rank-work_66762509", }); 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$(".js-view-count[data-work-id=66762509]").text(description); $(".js-view-count-work_66762509").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_66762509").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="66762509"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">15</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="428" rel="nofollow" href="https://www.academia.edu/Documents/in/Algorithms">Algorithms</a>, <script data-card-contents-for-ri="428" type="text/json">{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="5769" rel="nofollow" href="https://www.academia.edu/Documents/in/Mass_Spectrometry">Mass Spectrometry</a>, <script data-card-contents-for-ri="5769" type="text/json">{"id":5769,"name":"Mass Spectrometry","url":"https://www.academia.edu/Documents/in/Mass_Spectrometry?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="6970" rel="nofollow" href="https://www.academia.edu/Documents/in/Biomarkers">Biomarkers</a>, <script data-card-contents-for-ri="6970" type="text/json">{"id":6970,"name":"Biomarkers","url":"https://www.academia.edu/Documents/in/Biomarkers?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="9786" rel="nofollow" href="https://www.academia.edu/Documents/in/Proteomics">Proteomics</a><script data-card-contents-for-ri="9786" type="text/json">{"id":9786,"name":"Proteomics","url":"https://www.academia.edu/Documents/in/Proteomics?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=66762509]'), work: {"id":66762509,"title":"The glycolyzer: Automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery","created_at":"2022-01-01T00:10:45.781-08:00","url":"https://www.academia.edu/66762509/The_glycolyzer_Automated_glycan_annotation_software_for_high_performance_mass_spectrometry_and_its_application_to_ovarian_cancer_glycan_biomarker_discovery?f_ri=194916","dom_id":"work_66762509","summary":"Human serum glycomics is a promising method for finding cancer biomarkers but often lacks the tools for streamlined data analysis. The Glycolyzer software incorporates a suite of analytic tools capable of identifying informative glycan peaks out of raw mass spectrometry data. As a demonstration of its utility, the program was used to identify putative biomarkers for epithelial ovarian cancer from a human serum sample set. A randomized, blocked and blinded experimental design was used on a discovery set consisting of 46 cases and 48 controls. Retrosynthetic glycan libraries were used for data analysis and several significant candidate glycan biomarkers were discovered via hypothesis testing. The significant glycans were attributed to a glycan family based on glycan composition relationships and incorporated into a linear classifier motif test. The motif test was then applied to the discovery set to evaluate the disease state discrimination performance. The test provided strongly predictive results based on receiver operator characteristic curve analysis. The area under the receiver operator characteristic curve was 0.93. Using the Glycolyzer software, we were able to identify a set of glycan biomarkers that highly discriminate between cases and controls, and are ready to be formally validated in subsequent studies.","downloadable_attachments":[{"id":77829164,"asset_id":66762509,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":20904451,"first_name":"Andres","last_name":"Guerrero","domain_name":"independent","page_name":"AndresGuerrero7","display_name":"Andres Guerrero","profile_url":"https://independent.academia.edu/AndresGuerrero7?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":428,"name":"Algorithms","url":"https://www.academia.edu/Documents/in/Algorithms?f_ri=194916","nofollow":true},{"id":5769,"name":"Mass Spectrometry","url":"https://www.academia.edu/Documents/in/Mass_Spectrometry?f_ri=194916","nofollow":true},{"id":6970,"name":"Biomarkers","url":"https://www.academia.edu/Documents/in/Biomarkers?f_ri=194916","nofollow":true},{"id":9786,"name":"Proteomics","url":"https://www.academia.edu/Documents/in/Proteomics?f_ri=194916","nofollow":true},{"id":16061,"name":"Polysaccharides","url":"https://www.academia.edu/Documents/in/Polysaccharides?f_ri=194916"},{"id":47884,"name":"Biological Sciences","url":"https://www.academia.edu/Documents/in/Biological_Sciences?f_ri=194916"},{"id":53293,"name":"Software","url":"https://www.academia.edu/Documents/in/Software?f_ri=194916"},{"id":66379,"name":"Automation","url":"https://www.academia.edu/Documents/in/Automation?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":581652,"name":"Data Processing","url":"https://www.academia.edu/Documents/in/Data_Processing?f_ri=194916"},{"id":1134595,"name":"Glycomics","url":"https://www.academia.edu/Documents/in/Glycomics?f_ri=194916"},{"id":1341074,"name":"Isotope Labeling","url":"https://www.academia.edu/Documents/in/Isotope_Labeling?f_ri=194916"},{"id":3012647,"name":"Glycoproteomics","url":"https://www.academia.edu/Documents/in/Glycoproteomics?f_ri=194916"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences?f_ri=194916"},{"id":3881525,"name":"Ovarian Neoplasms","url":"https://www.academia.edu/Documents/in/Ovarian_Neoplasms?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_61896001" data-work_id="61896001" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/61896001/Diagnostic_criteria_for_atrophic_rhinosinusitis">Diagnostic criteria for atrophic rhinosinusitis</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">BACKGROUND: Patients with atrophic rhinosinusitis have intractable upper airway symptoms that result from loss of the normal nasal epithelium. There is no consensus on how to diagnose this condition, and diagnostic criteria are not... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_61896001" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">BACKGROUND: Patients with atrophic rhinosinusitis have intractable upper airway symptoms that result from loss of the normal nasal epithelium. There is no consensus on how to diagnose this condition, and diagnostic criteria are not available to perform multicenter treatment trials. We sought to establish diagnostic criteria for atrophic rhinosinusitis. METHODS: Twenty-two patients for whom there was a consensus on the diagnosis of atrophic rhinosinusitis were compared with a control group of 22 randomly selected patients with garden-variety chronic rhinosinusitis. Medical records were reviewed on all patients and clinical data were tabulated. Clinical variables included the presence of nasal obstruction, epistaxis, anosmia, purulence, crusting, chronic inflammatory disease involving the upper airway, and multiple sinus surgeries. RESULTS: Both groups had similar degrees of persistent nasal obstruction (82% vs 77%). The other 6 clinical features occurred more frequently in patients with atrophic rhinosinusitis than controls (P Ͻ.05). Patients with chronic rhinosinusitis and recurrent nasal purulence had a 25-fold (95% confidence interval [CI], 2.9-221.7) increased probability, those with recurrent epistaxis had a 12-fold increased probability (95% CI, 1.3-106.8), and those with 2 or more sinus surgeries had a 15-fold (95% CI, 3.5-66.7) increased probability of having atrophic rhinosinusitis. As the number of symptoms increased, there was an increasing probability of the predetermined diagnosis of atrophic rhinosinusitis (P Ͻ.05). The presence of chronic rhinosinusitis and any 2 of the 6 clinical features for 6 months or longer resulted in a sensitivity of 0.95 and specificity of 0.77 for the diagnosis of atrophic rhinosinusitis. CONCLUSION: The diagnosis of the common secondary form of atrophic rhinosinusitis may be made with certainty if a patient with chronic rhinosinusitis demonstrates 2 or more clinical features for 6 months and longer. These features are patient-reported recurrent epistaxis or episodic anosmia; or physician-documented nasal purulence, nasal crusting, chronic inflammatory disease of the upper airway, or 2 or more sinus surgeries.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/61896001" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="769eefcb97e95b2c2e2e86aeee8bfcfc" rel="nofollow" data-download="{"attachment_id":74813581,"asset_id":61896001,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/74813581/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="200853521" href="https://independent.academia.edu/tranly84">tran ly</a><script data-card-contents-for-user="200853521" type="text/json">{"id":200853521,"first_name":"tran","last_name":"ly","domain_name":"independent","page_name":"tranly84","display_name":"tran ly","profile_url":"https://independent.academia.edu/tranly84?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_61896001 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="61896001"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 61896001, container: ".js-paper-rank-work_61896001", }); });</script></li><li class="js-percentile-work_61896001 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 61896001; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_61896001"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_61896001 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="61896001"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 61896001; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=61896001]").text(description); $(".js-view-count-work_61896001").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_61896001").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="61896001"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">14</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="26327" rel="nofollow" href="https://www.academia.edu/Documents/in/Medicine">Medicine</a>, <script data-card-contents-for-ri="26327" type="text/json">{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="37805" rel="nofollow" href="https://www.academia.edu/Documents/in/Endoscopy">Endoscopy</a>, <script data-card-contents-for-ri="37805" type="text/json">{"id":37805,"name":"Endoscopy","url":"https://www.academia.edu/Documents/in/Endoscopy?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="97269" rel="nofollow" href="https://www.academia.edu/Documents/in/Chronic_Disease">Chronic Disease</a>, <script data-card-contents-for-ri="97269" type="text/json">{"id":97269,"name":"Chronic Disease","url":"https://www.academia.edu/Documents/in/Chronic_Disease?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="162159" rel="nofollow" href="https://www.academia.edu/Documents/in/Differential_Diagnosis">Differential Diagnosis</a><script data-card-contents-for-ri="162159" type="text/json">{"id":162159,"name":"Differential Diagnosis","url":"https://www.academia.edu/Documents/in/Differential_Diagnosis?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=61896001]'), work: {"id":61896001,"title":"Diagnostic criteria for atrophic rhinosinusitis","created_at":"2021-11-17T20:06:22.889-08:00","url":"https://www.academia.edu/61896001/Diagnostic_criteria_for_atrophic_rhinosinusitis?f_ri=194916","dom_id":"work_61896001","summary":"BACKGROUND: Patients with atrophic rhinosinusitis have intractable upper airway symptoms that result from loss of the normal nasal epithelium. There is no consensus on how to diagnose this condition, and diagnostic criteria are not available to perform multicenter treatment trials. We sought to establish diagnostic criteria for atrophic rhinosinusitis. METHODS: Twenty-two patients for whom there was a consensus on the diagnosis of atrophic rhinosinusitis were compared with a control group of 22 randomly selected patients with garden-variety chronic rhinosinusitis. Medical records were reviewed on all patients and clinical data were tabulated. Clinical variables included the presence of nasal obstruction, epistaxis, anosmia, purulence, crusting, chronic inflammatory disease involving the upper airway, and multiple sinus surgeries. RESULTS: Both groups had similar degrees of persistent nasal obstruction (82% vs 77%). The other 6 clinical features occurred more frequently in patients with atrophic rhinosinusitis than controls (P Ͻ.05). Patients with chronic rhinosinusitis and recurrent nasal purulence had a 25-fold (95% confidence interval [CI], 2.9-221.7) increased probability, those with recurrent epistaxis had a 12-fold increased probability (95% CI, 1.3-106.8), and those with 2 or more sinus surgeries had a 15-fold (95% CI, 3.5-66.7) increased probability of having atrophic rhinosinusitis. As the number of symptoms increased, there was an increasing probability of the predetermined diagnosis of atrophic rhinosinusitis (P Ͻ.05). The presence of chronic rhinosinusitis and any 2 of the 6 clinical features for 6 months or longer resulted in a sensitivity of 0.95 and specificity of 0.77 for the diagnosis of atrophic rhinosinusitis. CONCLUSION: The diagnosis of the common secondary form of atrophic rhinosinusitis may be made with certainty if a patient with chronic rhinosinusitis demonstrates 2 or more clinical features for 6 months and longer. These features are patient-reported recurrent epistaxis or episodic anosmia; or physician-documented nasal purulence, nasal crusting, chronic inflammatory disease of the upper airway, or 2 or more sinus surgeries.","downloadable_attachments":[{"id":74813581,"asset_id":61896001,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":200853521,"first_name":"tran","last_name":"ly","domain_name":"independent","page_name":"tranly84","display_name":"tran ly","profile_url":"https://independent.academia.edu/tranly84?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine?f_ri=194916","nofollow":true},{"id":37805,"name":"Endoscopy","url":"https://www.academia.edu/Documents/in/Endoscopy?f_ri=194916","nofollow":true},{"id":97269,"name":"Chronic Disease","url":"https://www.academia.edu/Documents/in/Chronic_Disease?f_ri=194916","nofollow":true},{"id":162159,"name":"Differential Diagnosis","url":"https://www.academia.edu/Documents/in/Differential_Diagnosis?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":350152,"name":"Sinusitis","url":"https://www.academia.edu/Documents/in/Sinusitis?f_ri=194916"},{"id":357850,"name":"Atrophy","url":"https://www.academia.edu/Documents/in/Atrophy?f_ri=194916"},{"id":901876,"name":"Sensitivity and Specificity","url":"https://www.academia.edu/Documents/in/Sensitivity_and_Specificity?f_ri=194916"},{"id":959921,"name":"X ray Computed Tomography","url":"https://www.academia.edu/Documents/in/X_ray_Computed_Tomography?f_ri=194916"},{"id":1537866,"name":"Nasal Mucosa","url":"https://www.academia.edu/Documents/in/Nasal_Mucosa?f_ri=194916"},{"id":1799441,"name":"Rhinitis","url":"https://www.academia.edu/Documents/in/Rhinitis?f_ri=194916"},{"id":1863718,"name":"The American","url":"https://www.academia.edu/Documents/in/The_American?f_ri=194916"},{"id":2330264,"name":"Diagnostic Criteria","url":"https://www.academia.edu/Documents/in/Diagnostic_Criteria?f_ri=194916"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_56824809" data-work_id="56824809" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/56824809/Establishment_of_a_paediatric_age_related_reference_interval_for_the_measurement_of_urinary_total_fractionated_metanephrines">Establishment of a paediatric age-related reference interval for the measurement of urinary total fractionated metanephrines</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Introduction: Normetanephrine and metanephrine are intermediate metabolites of noradrenaline and adrenaline metabolism. To assess whether normetanephrine and metanephrine analysis may aid in the diagnosis of Neuroblastoma, a reference... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_56824809" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Introduction: Normetanephrine and metanephrine are intermediate metabolites of noradrenaline and adrenaline metabolism. To assess whether normetanephrine and metanephrine analysis may aid in the diagnosis of Neuroblastoma, a reference interval for these metabolites must first be established. Aim: The overall aim of this study was to establish a paediatric age-related reference interval for the measurement of total fractionated metanephrines. Methods: A total of 267 urine samples were analysed following acid hydrolysis. This releases the metanephrines from their sulphate-bound metabolites. The samples were analysed using reverse phase high-performance liquid chromatography with electro-chemical detection on a Gilson automated sequential trace enrichment of dialysate sample system. Results: Data were analysed using Minitab Release version 14. Outliers were removed using the Dixon/Reed one-third rule. Partitioning of the age groups was achieved using Harris and Boyd's standard normal deviate test. Non-parametric analysis of the data was performed, followed by the establishment of the 2.5th and the 97.5th reference limits. Conclusions: The established reference intervals are described in Table 2.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/56824809" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="2668f20543cafd36fabcbc7765c395d9" rel="nofollow" data-download="{"attachment_id":72021460,"asset_id":56824809,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/72021460/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="3749039" href="https://ulster.academia.edu/WilliamTormey">William P Tormey</a><script data-card-contents-for-user="3749039" type="text/json">{"id":3749039,"first_name":"William","last_name":"Tormey","domain_name":"ulster","page_name":"WilliamTormey","display_name":"William P Tormey","profile_url":"https://ulster.academia.edu/WilliamTormey?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_56824809 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="56824809"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 56824809, container: ".js-paper-rank-work_56824809", }); 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$(".js-view-count[data-work-id=56824809]").text(description); $(".js-view-count-work_56824809").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_56824809").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="56824809"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">17</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="3243" rel="nofollow" href="https://www.academia.edu/Documents/in/Nonparametric_Statistics">Nonparametric Statistics</a>, <script data-card-contents-for-ri="3243" type="text/json">{"id":3243,"name":"Nonparametric Statistics","url":"https://www.academia.edu/Documents/in/Nonparametric_Statistics?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="22506" rel="nofollow" href="https://www.academia.edu/Documents/in/Adolescent">Adolescent</a>, <script data-card-contents-for-ri="22506" type="text/json">{"id":22506,"name":"Adolescent","url":"https://www.academia.edu/Documents/in/Adolescent?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="51566" rel="nofollow" href="https://www.academia.edu/Documents/in/Dopamine">Dopamine</a>, <script data-card-contents-for-ri="51566" type="text/json">{"id":51566,"name":"Dopamine","url":"https://www.academia.edu/Documents/in/Dopamine?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="64657" rel="nofollow" href="https://www.academia.edu/Documents/in/Prolactin">Prolactin</a><script data-card-contents-for-ri="64657" type="text/json">{"id":64657,"name":"Prolactin","url":"https://www.academia.edu/Documents/in/Prolactin?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=56824809]'), work: {"id":56824809,"title":"Establishment of a paediatric age-related reference interval for the measurement of urinary total fractionated metanephrines","created_at":"2021-10-09T12:22:19.253-07:00","url":"https://www.academia.edu/56824809/Establishment_of_a_paediatric_age_related_reference_interval_for_the_measurement_of_urinary_total_fractionated_metanephrines?f_ri=194916","dom_id":"work_56824809","summary":"Introduction: Normetanephrine and metanephrine are intermediate metabolites of noradrenaline and adrenaline metabolism. To assess whether normetanephrine and metanephrine analysis may aid in the diagnosis of Neuroblastoma, a reference interval for these metabolites must first be established. Aim: The overall aim of this study was to establish a paediatric age-related reference interval for the measurement of total fractionated metanephrines. Methods: A total of 267 urine samples were analysed following acid hydrolysis. This releases the metanephrines from their sulphate-bound metabolites. The samples were analysed using reverse phase high-performance liquid chromatography with electro-chemical detection on a Gilson automated sequential trace enrichment of dialysate sample system. Results: Data were analysed using Minitab Release version 14. Outliers were removed using the Dixon/Reed one-third rule. Partitioning of the age groups was achieved using Harris and Boyd's standard normal deviate test. Non-parametric analysis of the data was performed, followed by the establishment of the 2.5th and the 97.5th reference limits. Conclusions: The established reference intervals are described in Table 2.","downloadable_attachments":[{"id":72021460,"asset_id":56824809,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":3749039,"first_name":"William","last_name":"Tormey","domain_name":"ulster","page_name":"WilliamTormey","display_name":"William P Tormey","profile_url":"https://ulster.academia.edu/WilliamTormey?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":3243,"name":"Nonparametric Statistics","url":"https://www.academia.edu/Documents/in/Nonparametric_Statistics?f_ri=194916","nofollow":true},{"id":22506,"name":"Adolescent","url":"https://www.academia.edu/Documents/in/Adolescent?f_ri=194916","nofollow":true},{"id":51566,"name":"Dopamine","url":"https://www.academia.edu/Documents/in/Dopamine?f_ri=194916","nofollow":true},{"id":64657,"name":"Prolactin","url":"https://www.academia.edu/Documents/in/Prolactin?f_ri=194916","nofollow":true},{"id":64933,"name":"Child","url":"https://www.academia.edu/Documents/in/Child?f_ri=194916"},{"id":71454,"name":"Epinephrine","url":"https://www.academia.edu/Documents/in/Epinephrine?f_ri=194916"},{"id":134346,"name":"Infant","url":"https://www.academia.edu/Documents/in/Infant?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":235189,"name":"Norepinephrine","url":"https://www.academia.edu/Documents/in/Norepinephrine?f_ri=194916"},{"id":253560,"name":"Newborn Infant","url":"https://www.academia.edu/Documents/in/Newborn_Infant?f_ri=194916"},{"id":256805,"name":"Neuroblastoma","url":"https://www.academia.edu/Documents/in/Neuroblastoma?f_ri=194916"},{"id":413192,"name":"Sex Factors","url":"https://www.academia.edu/Documents/in/Sex_Factors?f_ri=194916"},{"id":546419,"name":"Age Factors","url":"https://www.academia.edu/Documents/in/Age_Factors?f_ri=194916"},{"id":1000427,"name":"Reference Values","url":"https://www.academia.edu/Documents/in/Reference_Values?f_ri=194916"},{"id":1423078,"name":"Nervous System Diseases","url":"https://www.academia.edu/Documents/in/Nervous_System_Diseases?f_ri=194916"},{"id":2489700,"name":"Child preschool","url":"https://www.academia.edu/Documents/in/Child_preschool?f_ri=194916"},{"id":3789880,"name":"Medical biochemistry and metabolomics","url":"https://www.academia.edu/Documents/in/Medical_biochemistry_and_metabolomics?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_54314759" data-work_id="54314759" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/54314759/The_management_of_deep_vein_thrombosis_the_Autar_DVT_risk_assessment_scale_re_visited">The management of deep vein thrombosis: the Autar DVT risk assessment scale re-visited</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Deep vein thrombosis (DVT) is a precursor of potentially fatal pulmonary embolism (PE). The Autar DVT scale (1994) was developed to assess patient risk and enable the application of the most effective prophylaxis. The scale is composed of... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_54314759" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Deep vein thrombosis (DVT) is a precursor of potentially fatal pulmonary embolism (PE). The Autar DVT scale (1994) was developed to assess patient risk and enable the application of the most effective prophylaxis. The scale is composed of seven categories of risk factors derived from Virchow's triad. The DVT scale was re-evaluated on 150 patients across three distinct clinical specialities to allow for generalisation of the findings. Five reproducibility studies achieved total percentage agreement of between 91 and 98%, j values within 0.88-0.95 and intra-class correlation coefficients of 0.94-0.99, confirming the consistency of the instrument. A receiver operating characteristic (ROC) curve was constructed to determine the optimal predictive accuracy of the scale and a cutoff score of 11 yielded approximately 70% sensitivity. Partially completed data from two patients were excluded from the sensitivity analysis of the DVT scale. Out of the 148 (78%) 115 patients were correctly predicted. However, the predictive accuracy of the DVT scale was partially masked by the 50% of patients who were recipient of some proven venous thromboprophylaxis.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/54314759" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="e5256f4ed0f800e4a07bc398021961b2" rel="nofollow" data-download="{"attachment_id":70738661,"asset_id":54314759,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/70738661/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="105492149" href="https://independent.academia.edu/AgusMartinez10">Agus Martinez</a><script data-card-contents-for-user="105492149" type="text/json">{"id":105492149,"first_name":"Agus","last_name":"Martinez","domain_name":"independent","page_name":"AgusMartinez10","display_name":"Agus Martinez","profile_url":"https://independent.academia.edu/AgusMartinez10?f_ri=194916","photo":"https://0.academia-photos.com/105492149/24116237/23083909/s65_agus.martinez.jpg"}</script></span></span></li><li class="js-paper-rank-work_54314759 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="54314759"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 54314759, container: ".js-paper-rank-work_54314759", }); });</script></li><li class="js-percentile-work_54314759 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 54314759; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_54314759"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_54314759 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="54314759"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54314759; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=54314759]").text(description); $(".js-view-count-work_54314759").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_54314759").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="54314759"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">11</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="588" rel="nofollow" href="https://www.academia.edu/Documents/in/Nursing">Nursing</a>, <script data-card-contents-for-ri="588" type="text/json">{"id":588,"name":"Nursing","url":"https://www.academia.edu/Documents/in/Nursing?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="16664" rel="nofollow" href="https://www.academia.edu/Documents/in/Risk_assessment">Risk assessment</a>, <script data-card-contents-for-ri="16664" type="text/json">{"id":16664,"name":"Risk assessment","url":"https://www.academia.edu/Documents/in/Risk_assessment?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="20099" rel="nofollow" href="https://www.academia.edu/Documents/in/Sensitivity_Analysis">Sensitivity Analysis</a>, <script data-card-contents-for-ri="20099" type="text/json">{"id":20099,"name":"Sensitivity Analysis","url":"https://www.academia.edu/Documents/in/Sensitivity_Analysis?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="66324" rel="nofollow" href="https://www.academia.edu/Documents/in/Deep_Vein_Thrombosis">Deep Vein Thrombosis</a><script data-card-contents-for-ri="66324" type="text/json">{"id":66324,"name":"Deep Vein Thrombosis","url":"https://www.academia.edu/Documents/in/Deep_Vein_Thrombosis?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=54314759]'), work: {"id":54314759,"title":"The management of deep vein thrombosis: the Autar DVT risk assessment scale re-visited","created_at":"2021-09-30T06:47:02.675-07:00","url":"https://www.academia.edu/54314759/The_management_of_deep_vein_thrombosis_the_Autar_DVT_risk_assessment_scale_re_visited?f_ri=194916","dom_id":"work_54314759","summary":"Deep vein thrombosis (DVT) is a precursor of potentially fatal pulmonary embolism (PE). The Autar DVT scale (1994) was developed to assess patient risk and enable the application of the most effective prophylaxis. The scale is composed of seven categories of risk factors derived from Virchow's triad. The DVT scale was re-evaluated on 150 patients across three distinct clinical specialities to allow for generalisation of the findings. Five reproducibility studies achieved total percentage agreement of between 91 and 98%, j values within 0.88-0.95 and intra-class correlation coefficients of 0.94-0.99, confirming the consistency of the instrument. A receiver operating characteristic (ROC) curve was constructed to determine the optimal predictive accuracy of the scale and a cutoff score of 11 yielded approximately 70% sensitivity. Partially completed data from two patients were excluded from the sensitivity analysis of the DVT scale. Out of the 148 (78%) 115 patients were correctly predicted. However, the predictive accuracy of the DVT scale was partially masked by the 50% of patients who were recipient of some proven venous thromboprophylaxis.","downloadable_attachments":[{"id":70738661,"asset_id":54314759,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":105492149,"first_name":"Agus","last_name":"Martinez","domain_name":"independent","page_name":"AgusMartinez10","display_name":"Agus Martinez","profile_url":"https://independent.academia.edu/AgusMartinez10?f_ri=194916","photo":"https://0.academia-photos.com/105492149/24116237/23083909/s65_agus.martinez.jpg"}],"research_interests":[{"id":588,"name":"Nursing","url":"https://www.academia.edu/Documents/in/Nursing?f_ri=194916","nofollow":true},{"id":16664,"name":"Risk assessment","url":"https://www.academia.edu/Documents/in/Risk_assessment?f_ri=194916","nofollow":true},{"id":20099,"name":"Sensitivity Analysis","url":"https://www.academia.edu/Documents/in/Sensitivity_Analysis?f_ri=194916","nofollow":true},{"id":66324,"name":"Deep Vein Thrombosis","url":"https://www.academia.edu/Documents/in/Deep_Vein_Thrombosis?f_ri=194916","nofollow":true},{"id":102587,"name":"Pulmonary Embolism","url":"https://www.academia.edu/Documents/in/Pulmonary_Embolism?f_ri=194916"},{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":620049,"name":"Risk Factors","url":"https://www.academia.edu/Documents/in/Risk_Factors-1?f_ri=194916"},{"id":622589,"name":"Risk Assessment","url":"https://www.academia.edu/Documents/in/Risk_Assessment-2?f_ri=194916"},{"id":1671808,"name":"Prediction Accuracy","url":"https://www.academia.edu/Documents/in/Prediction_Accuracy?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_47421960" data-work_id="47421960" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/47421960/Brief_case_finding_tools_for_anxiety_disorders_Validation_of_GAD_7_and_GAD_2_in_addictions_treatment">Brief case finding tools for anxiety disorders: Validation of GAD-7 and GAD-2 in addictions treatment</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Background: Anxiety disorders are the most common mental health problems and often co-exist with substance use. Little evidence exists to support the use of brief screening tools for anxiety disorders in routine addictions treatment. This... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_47421960" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Background: Anxiety disorders are the most common mental health problems and often co-exist with substance use. Little evidence exists to support the use of brief screening tools for anxiety disorders in routine addictions treatment. This is the first study to test the validity and reliability of GAD-7 and GAD-2 in an outpatient drugs treatment population. Methods: A sample of 103 patients completed brief screening questionnaires and took part in structured diagnostic assessments using CIS-R. A subgroup of 60 patients completed retests after 4 weeks. The results of brief questionnaires were compared to those of gold-standard diagnostic interviews using Receiver Operating Characteristic (ROC) curves. Psychometric properties were also calculated to evaluate the validity and reliability of self-completed questionnaires. Results: A GAD-7 score ≥9 had a sensitivity of 80% and specificity of 86% for any anxiety disorder, also displaying adequate temporal stability at repeated measurements (intra-class correlation = 0.85) and high internal consistency (Cronbach's alpha = 0.91). A GAD-2 score ≥2 had 94% sensitivity and 53% specificity, with adequate internal consistency (0.82). Conclusions: GAD-7 adequately detected the presence of an anxiety disorder in drug and alcohol users; although this study was limited by sample size to determine its reliability for specific diagnoses. Results in this small sample suggest that GAD-7 may be a useful screening tool in addiction services, although replication in a larger sample is warranted.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/47421960" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="7fb32c67fc8d9750d04949b2fb9004cd" rel="nofollow" data-download="{"attachment_id":66522161,"asset_id":47421960,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/66522161/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="32100758" href="https://york.academia.edu/ChristineGodfrey">Christine Godfrey</a><script data-card-contents-for-user="32100758" type="text/json">{"id":32100758,"first_name":"Christine","last_name":"Godfrey","domain_name":"york","page_name":"ChristineGodfrey","display_name":"Christine Godfrey","profile_url":"https://york.academia.edu/ChristineGodfrey?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_47421960 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="47421960"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 47421960, container: ".js-paper-rank-work_47421960", }); 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$(".js-view-count[data-work-id=47421960]").text(description); $(".js-view-count-work_47421960").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_47421960").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="47421960"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">16</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="1314" rel="nofollow" href="https://www.academia.edu/Documents/in/Anxiety_Disorders">Anxiety Disorders</a>, <script data-card-contents-for-ri="1314" type="text/json">{"id":1314,"name":"Anxiety Disorders","url":"https://www.academia.edu/Documents/in/Anxiety_Disorders?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="2483" rel="nofollow" href="https://www.academia.edu/Documents/in/Addiction">Addiction</a>, <script data-card-contents-for-ri="2483" type="text/json">{"id":2483,"name":"Addiction","url":"https://www.academia.edu/Documents/in/Addiction?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="2599" rel="nofollow" href="https://www.academia.edu/Documents/in/Psychometrics">Psychometrics</a>, <script data-card-contents-for-ri="2599" type="text/json">{"id":2599,"name":"Psychometrics","url":"https://www.academia.edu/Documents/in/Psychometrics?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="43363" rel="nofollow" href="https://www.academia.edu/Documents/in/Screening">Screening</a><script data-card-contents-for-ri="43363" type="text/json">{"id":43363,"name":"Screening","url":"https://www.academia.edu/Documents/in/Screening?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=47421960]'), work: {"id":47421960,"title":"Brief case finding tools for anxiety disorders: Validation of GAD-7 and GAD-2 in addictions treatment","created_at":"2021-04-22T03:31:02.037-07:00","url":"https://www.academia.edu/47421960/Brief_case_finding_tools_for_anxiety_disorders_Validation_of_GAD_7_and_GAD_2_in_addictions_treatment?f_ri=194916","dom_id":"work_47421960","summary":"Background: Anxiety disorders are the most common mental health problems and often co-exist with substance use. Little evidence exists to support the use of brief screening tools for anxiety disorders in routine addictions treatment. This is the first study to test the validity and reliability of GAD-7 and GAD-2 in an outpatient drugs treatment population. Methods: A sample of 103 patients completed brief screening questionnaires and took part in structured diagnostic assessments using CIS-R. A subgroup of 60 patients completed retests after 4 weeks. The results of brief questionnaires were compared to those of gold-standard diagnostic interviews using Receiver Operating Characteristic (ROC) curves. Psychometric properties were also calculated to evaluate the validity and reliability of self-completed questionnaires. Results: A GAD-7 score ≥9 had a sensitivity of 80% and specificity of 86% for any anxiety disorder, also displaying adequate temporal stability at repeated measurements (intra-class correlation = 0.85) and high internal consistency (Cronbach's alpha = 0.91). A GAD-2 score ≥2 had 94% sensitivity and 53% specificity, with adequate internal consistency (0.82). Conclusions: GAD-7 adequately detected the presence of an anxiety disorder in drug and alcohol users; although this study was limited by sample size to determine its reliability for specific diagnoses. Results in this small sample suggest that GAD-7 may be a useful screening tool in addiction services, although replication in a larger sample is warranted.","downloadable_attachments":[{"id":66522161,"asset_id":47421960,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":32100758,"first_name":"Christine","last_name":"Godfrey","domain_name":"york","page_name":"ChristineGodfrey","display_name":"Christine Godfrey","profile_url":"https://york.academia.edu/ChristineGodfrey?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":1314,"name":"Anxiety Disorders","url":"https://www.academia.edu/Documents/in/Anxiety_Disorders?f_ri=194916","nofollow":true},{"id":2483,"name":"Addiction","url":"https://www.academia.edu/Documents/in/Addiction?f_ri=194916","nofollow":true},{"id":2599,"name":"Psychometrics","url":"https://www.academia.edu/Documents/in/Psychometrics?f_ri=194916","nofollow":true},{"id":43363,"name":"Screening","url":"https://www.academia.edu/Documents/in/Screening?f_ri=194916","nofollow":true},{"id":86176,"name":"Alcohol","url":"https://www.academia.edu/Documents/in/Alcohol?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":323476,"name":"International Classification of Diseases","url":"https://www.academia.edu/Documents/in/International_Classification_of_Diseases?f_ri=194916"},{"id":327850,"name":"Questionnaires","url":"https://www.academia.edu/Documents/in/Questionnaires?f_ri=194916"},{"id":378991,"name":"Outpatients","url":"https://www.academia.edu/Documents/in/Outpatients?f_ri=194916"},{"id":549280,"name":"Reproducibility of Results","url":"https://www.academia.edu/Documents/in/Reproducibility_of_Results?f_ri=194916"},{"id":1034181,"name":"Cross Sectional Studies","url":"https://www.academia.edu/Documents/in/Cross_Sectional_Studies?f_ri=194916"},{"id":1309706,"name":"Area Under Curve","url":"https://www.academia.edu/Documents/in/Area_Under_Curve?f_ri=194916"},{"id":1423077,"name":"Substance-Related Disorders","url":"https://www.academia.edu/Documents/in/Substance-Related_Disorders?f_ri=194916"},{"id":2467548,"name":"Neuropsychological Tests","url":"https://www.academia.edu/Documents/in/Neuropsychological_Tests?f_ri=194916"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences?f_ri=194916"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_45427038" data-work_id="45427038" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/45427038/Prolonged_hospital_stay_after_parathyroidectomy_for_secondary_hyperparathyroidism">Prolonged hospital stay after parathyroidectomy for secondary hyperparathyroidism</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Protracted hypocalcemia is the most common complication after parathyroidectomy for secondary hyperparathyroidism. Several parameters have been identified to predict the degree of postoperative hypocalcemia. The purpose of this study was... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_45427038" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Protracted hypocalcemia is the most common complication after parathyroidectomy for secondary hyperparathyroidism. Several parameters have been identified to predict the degree of postoperative hypocalcemia. The purpose of this study was to determine whether there were any factors associated with prolonged hospitalization in these patients. A total of 81 consecutive patients with end-stage renal disease and advanced secondary hyperparathyroidism who underwent parathyroidectomy between January 2004 and December 2006 were studied. The postoperative calcium infusion protocol and discharge criteria were standardized. Clinical variables were compared between patients with a shorter or longer postoperative stay. The mean postoperative hospital stay was 5.6 days. Preoperative alkaline phosphatase levels were significantly higher in patients with a longer stay (p=0.035). In a linear regression model, the postoperative length of stay was moderately but significantly correlated with preoperat...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/45427038" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="aba8e0b0658aa01a4c4d658e86d9c083" rel="nofollow" data-download="{"attachment_id":65939792,"asset_id":45427038,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/65939792/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="62998329" href="https://independent.academia.edu/ShihPingCheng">Shih-Ping Cheng</a><script data-card-contents-for-user="62998329" type="text/json">{"id":62998329,"first_name":"Shih-Ping","last_name":"Cheng","domain_name":"independent","page_name":"ShihPingCheng","display_name":"Shih-Ping Cheng","profile_url":"https://independent.academia.edu/ShihPingCheng?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_45427038 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="45427038"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 45427038, container: ".js-paper-rank-work_45427038", }); });</script></li><li class="js-percentile-work_45427038 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 45427038; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_45427038"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_45427038 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="45427038"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 45427038; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=45427038]").text(description); $(".js-view-count-work_45427038").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_45427038").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="45427038"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">15</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="73606" rel="nofollow" href="https://www.academia.edu/Documents/in/World">World</a>, <script data-card-contents-for-ri="73606" type="text/json">{"id":73606,"name":"World","url":"https://www.academia.edu/Documents/in/World?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="85188" rel="nofollow" href="https://www.academia.edu/Documents/in/End_Stage_Renal_Disease">End Stage Renal Disease</a>, <script data-card-contents-for-ri="85188" type="text/json">{"id":85188,"name":"End Stage Renal Disease","url":"https://www.academia.edu/Documents/in/End_Stage_Renal_Disease?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a>, <script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="204435" rel="nofollow" href="https://www.academia.edu/Documents/in/Alkaline_phosphatase">Alkaline phosphatase</a><script data-card-contents-for-ri="204435" type="text/json">{"id":204435,"name":"Alkaline phosphatase","url":"https://www.academia.edu/Documents/in/Alkaline_phosphatase?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=45427038]'), work: {"id":45427038,"title":"Prolonged hospital stay after parathyroidectomy for secondary hyperparathyroidism","created_at":"2021-03-08T05:11:14.090-08:00","url":"https://www.academia.edu/45427038/Prolonged_hospital_stay_after_parathyroidectomy_for_secondary_hyperparathyroidism?f_ri=194916","dom_id":"work_45427038","summary":"Protracted hypocalcemia is the most common complication after parathyroidectomy for secondary hyperparathyroidism. Several parameters have been identified to predict the degree of postoperative hypocalcemia. The purpose of this study was to determine whether there were any factors associated with prolonged hospitalization in these patients. A total of 81 consecutive patients with end-stage renal disease and advanced secondary hyperparathyroidism who underwent parathyroidectomy between January 2004 and December 2006 were studied. The postoperative calcium infusion protocol and discharge criteria were standardized. Clinical variables were compared between patients with a shorter or longer postoperative stay. The mean postoperative hospital stay was 5.6 days. Preoperative alkaline phosphatase levels were significantly higher in patients with a longer stay (p=0.035). In a linear regression model, the postoperative length of stay was moderately but significantly correlated with preoperat...","downloadable_attachments":[{"id":65939792,"asset_id":45427038,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":62998329,"first_name":"Shih-Ping","last_name":"Cheng","domain_name":"independent","page_name":"ShihPingCheng","display_name":"Shih-Ping Cheng","profile_url":"https://independent.academia.edu/ShihPingCheng?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":73606,"name":"World","url":"https://www.academia.edu/Documents/in/World?f_ri=194916","nofollow":true},{"id":85188,"name":"End Stage Renal Disease","url":"https://www.academia.edu/Documents/in/End_Stage_Renal_Disease?f_ri=194916","nofollow":true},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true},{"id":204435,"name":"Alkaline phosphatase","url":"https://www.academia.edu/Documents/in/Alkaline_phosphatase?f_ri=194916","nofollow":true},{"id":211917,"name":"Length of Stay","url":"https://www.academia.edu/Documents/in/Length_of_Stay?f_ri=194916"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences?f_ri=194916"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916"},{"id":469105,"name":"Retrospective Studies","url":"https://www.academia.edu/Documents/in/Retrospective_Studies?f_ri=194916"},{"id":568482,"name":"Biological markers","url":"https://www.academia.edu/Documents/in/Biological_markers?f_ri=194916"},{"id":990608,"name":"Linear Regression Model","url":"https://www.academia.edu/Documents/in/Linear_Regression_Model?f_ri=194916"},{"id":1141485,"name":"Area Under the Curve","url":"https://www.academia.edu/Documents/in/Area_Under_the_Curve?f_ri=194916"},{"id":1587858,"name":"Confidence Interval","url":"https://www.academia.edu/Documents/in/Confidence_Interval?f_ri=194916"},{"id":1953423,"name":"Postoperative Period","url":"https://www.academia.edu/Documents/in/Postoperative_Period?f_ri=194916"},{"id":2487845,"name":"Parathyroidectomy","url":"https://www.academia.edu/Documents/in/Parathyroidectomy?f_ri=194916"},{"id":3211541,"name":"Secondary Hyperparathyroidism","url":"https://www.academia.edu/Documents/in/Secondary_Hyperparathyroidism?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_34406242" data-work_id="34406242" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/34406242/Detecting_and_Tracking_Intruders_using_a_Pan_Tilt_Surveillance_System">Detecting and Tracking Intruders using a Pan-Tilt Surveillance System</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">ó The use of autonomous pan-tilt cameras as opposed to static cameras can dramatically enhance the range and effectiveness of surveillance systems, but effective tracking in such pan-tilt scenarios remains a challenge. Existing approaches... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_34406242" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">ó The use of autonomous pan-tilt cameras as opposed to static cameras can dramatically enhance the range and effectiveness of surveillance systems, but effective tracking in such pan-tilt scenarios remains a challenge. Existing approaches for constructing mosaiced background models require accurate camera motion parameters, and online updates for the back- ground model in the presence of scene activity, as well</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/34406242" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="7ecd470e0c99e9b8dfbdddba6ab0eb35" rel="nofollow" data-download="{"attachment_id":54287398,"asset_id":34406242,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/54287398/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="24649067" href="https://independent.academia.edu/ArindamBiswas3">Arindam Biswas</a><script data-card-contents-for-user="24649067" type="text/json">{"id":24649067,"first_name":"Arindam","last_name":"Biswas","domain_name":"independent","page_name":"ArindamBiswas3","display_name":"Arindam Biswas","profile_url":"https://independent.academia.edu/ArindamBiswas3?f_ri=194916","photo":"https://0.academia-photos.com/24649067/10237893/11425602/s65_arindam.biswas.jpg_oh_bb295a7817271c8e3aa8576c167670e9_oe_569e3104___gda___1453538428_0af172ef339c2b83aadd4e8f43b228d1"}</script></span></span></li><li class="js-paper-rank-work_34406242 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="34406242"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 34406242, container: ".js-paper-rank-work_34406242", }); 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$(".js-view-count[data-work-id=34406242]").text(description); $(".js-view-count-work_34406242").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_34406242").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="34406242"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="38111" rel="nofollow" href="https://www.academia.edu/Documents/in/Target_Tracking">Target Tracking</a>, <script data-card-contents-for-ri="38111" type="text/json">{"id":38111,"name":"Target Tracking","url":"https://www.academia.edu/Documents/in/Target_Tracking?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="154216" rel="nofollow" href="https://www.academia.edu/Documents/in/Background_modeling">Background modeling</a>, <script data-card-contents-for-ri="154216" type="text/json">{"id":154216,"name":"Background modeling","url":"https://www.academia.edu/Documents/in/Background_modeling?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="161944" rel="nofollow" href="https://www.academia.edu/Documents/in/Tracking_Vehicles_in_Real_Time">Tracking Vehicles in Real Time</a>, <script data-card-contents-for-ri="161944" type="text/json">{"id":161944,"name":"Tracking Vehicles in Real Time","url":"https://www.academia.edu/Documents/in/Tracking_Vehicles_in_Real_Time?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="194916" rel="nofollow" href="https://www.academia.edu/Documents/in/ROC_Curve">ROC Curve</a><script data-card-contents-for-ri="194916" type="text/json">{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=34406242]'), work: {"id":34406242,"title":"Detecting and Tracking Intruders using a Pan-Tilt Surveillance System","created_at":"2017-08-29T23:23:10.051-07:00","url":"https://www.academia.edu/34406242/Detecting_and_Tracking_Intruders_using_a_Pan_Tilt_Surveillance_System?f_ri=194916","dom_id":"work_34406242","summary":"ó The use of autonomous pan-tilt cameras as opposed to static cameras can dramatically enhance the range and effectiveness of surveillance systems, but effective tracking in such pan-tilt scenarios remains a challenge. 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The study was conducted in an elderly, ethnically diverse community-dwelling population. Sensitivity, specificity, positive and negative predictive values were calculated over a range of clinically relevant cut scores for each test. We analyzed the influence of age, education, reading ability and sex on test performance using logistic regression models.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/34047077" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="54f6af6f46503ce457031bc5dfde7bad" rel="nofollow" data-download="{"attachment_id":53986086,"asset_id":34047077,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/53986086/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="66756650" href="https://independent.academia.edu/JoeVerghese">Joe Verghese</a><script data-card-contents-for-user="66756650" type="text/json">{"id":66756650,"first_name":"Joe","last_name":"Verghese","domain_name":"independent","page_name":"JoeVerghese","display_name":"Joe Verghese","profile_url":"https://independent.academia.edu/JoeVerghese?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_34047077 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="34047077"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 34047077, container: ".js-paper-rank-work_34047077", }); 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$(".js-view-count[data-work-id=34047077]").text(description); $(".js-view-count-work_34047077").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_34047077").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="34047077"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">20</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="221" rel="nofollow" href="https://www.academia.edu/Documents/in/Psychology">Psychology</a>, <script data-card-contents-for-ri="221" type="text/json">{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="237" rel="nofollow" href="https://www.academia.edu/Documents/in/Cognitive_Science">Cognitive Science</a>, <script data-card-contents-for-ri="237" type="text/json">{"id":237,"name":"Cognitive Science","url":"https://www.academia.edu/Documents/in/Cognitive_Science?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="32433" rel="nofollow" href="https://www.academia.edu/Documents/in/Logistic_Regression">Logistic Regression</a>, <script data-card-contents-for-ri="32433" type="text/json">{"id":32433,"name":"Logistic Regression","url":"https://www.academia.edu/Documents/in/Logistic_Regression?f_ri=194916","nofollow":true}</script><a class="InlineList-item-text" data-has-card-for-ri="97766" rel="nofollow" href="https://www.academia.edu/Documents/in/Vascular_dementia">Vascular dementia</a><script data-card-contents-for-ri="97766" type="text/json">{"id":97766,"name":"Vascular dementia","url":"https://www.academia.edu/Documents/in/Vascular_dementia?f_ri=194916","nofollow":true}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=34047077]'), work: {"id":34047077,"title":"Detecting dementia with the Hopkins Verbal Learning Test and the Mini-Mental State Examination","created_at":"2017-07-26T18:25:03.684-07:00","url":"https://www.academia.edu/34047077/Detecting_dementia_with_the_Hopkins_Verbal_Learning_Test_and_the_Mini_Mental_State_Examination?f_ri=194916","dom_id":"work_34047077","summary":"The Hopkins Verbal Learning Test (HVLT) and the Mini-Mental State Examination (MMSE) were administered to 323 non-demented elderly and 70 individuals who meet DSM-IV criteria for dementia in order to compare the validity of these two measures for detecting mild dementia and for the two most common dementia subtypes, Alzheimer's disease (AD) and vascular dementia (VaD). The study was conducted in an elderly, ethnically diverse community-dwelling population. Sensitivity, specificity, positive and negative predictive values were calculated over a range of clinically relevant cut scores for each test. We analyzed the influence of age, education, reading ability and sex on test performance using logistic regression models.","downloadable_attachments":[{"id":53986086,"asset_id":34047077,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":66756650,"first_name":"Joe","last_name":"Verghese","domain_name":"independent","page_name":"JoeVerghese","display_name":"Joe Verghese","profile_url":"https://independent.academia.edu/JoeVerghese?f_ri=194916","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=194916","nofollow":true},{"id":237,"name":"Cognitive Science","url":"https://www.academia.edu/Documents/in/Cognitive_Science?f_ri=194916","nofollow":true},{"id":32433,"name":"Logistic Regression","url":"https://www.academia.edu/Documents/in/Logistic_Regression?f_ri=194916","nofollow":true},{"id":97766,"name":"Vascular dementia","url":"https://www.academia.edu/Documents/in/Vascular_dementia?f_ri=194916","nofollow":true},{"id":162159,"name":"Differential Diagnosis","url":"https://www.academia.edu/Documents/in/Differential_Diagnosis?f_ri=194916"},{"id":194916,"name":"ROC Curve","url":"https://www.academia.edu/Documents/in/ROC_Curve?f_ri=194916"},{"id":254133,"name":"Mini Mental State Examination","url":"https://www.academia.edu/Documents/in/Mini_Mental_State_Examination?f_ri=194916"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=194916"},{"id":406051,"name":"Regression Model","url":"https://www.academia.edu/Documents/in/Regression_Model?f_ri=194916"},{"id":502712,"name":"Ethnic diversity","url":"https://www.academia.edu/Documents/in/Ethnic_diversity?f_ri=194916"},{"id":549280,"name":"Reproducibility of Results","url":"https://www.academia.edu/Documents/in/Reproducibility_of_Results?f_ri=194916"},{"id":601304,"name":"Verbal Memory","url":"https://www.academia.edu/Documents/in/Verbal_Memory?f_ri=194916"},{"id":644084,"name":"Intelligence tests","url":"https://www.academia.edu/Documents/in/Intelligence_tests?f_ri=194916"},{"id":968937,"name":"Logistic Regression Model","url":"https://www.academia.edu/Documents/in/Logistic_Regression_Model?f_ri=194916"},{"id":974411,"name":"Memory Disorders","url":"https://www.academia.edu/Documents/in/Memory_Disorders?f_ri=194916"},{"id":1120234,"name":"Alzheimer Disease","url":"https://www.academia.edu/Documents/in/Alzheimer_Disease?f_ri=194916"},{"id":1141485,"name":"Area Under the Curve","url":"https://www.academia.edu/Documents/in/Area_Under_the_Curve?f_ri=194916"},{"id":1239755,"name":"Neurosciences","url":"https://www.academia.edu/Documents/in/Neurosciences?f_ri=194916"},{"id":1318932,"name":"Predictive value of tests","url":"https://www.academia.edu/Documents/in/Predictive_value_of_tests?f_ri=194916"},{"id":2467548,"name":"Neuropsychological Tests","url":"https://www.academia.edu/Documents/in/Neuropsychological_Tests?f_ri=194916"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_34032621" data-work_id="34032621" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/34032621/Optimal_bedside_urinalysis_for_the_detection_of_proteinuria_in_hypertensive_pregnancy_a_study_of_diagnostic_accuracy">Optimal bedside urinalysis for the detection of proteinuria in hypertensive pregnancy: a study of diagnostic accuracy</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Objective To compare semi-quantitative visual and automated methods of urine testing with fully quantitative point of care urinalysis for the detection of significant proteinuria (0.3 g/24 hours) in pregnancy complicated by hypertension.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_34032621" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Objective To compare semi-quantitative visual and automated methods of urine testing with fully quantitative point of care urinalysis for the detection of significant proteinuria (0.3 g/24 hours) in pregnancy complicated by hypertension. Design A prospective comparative study.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/34032621" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="91138f0a41e7a426675ca721876341f9" rel="nofollow" data-download="{"attachment_id":53973716,"asset_id":34032621,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/53973716/download_file?st=MTc0MDU1Mjc0NSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="66717177" href="https://kcl.academia.edu/PaulSeed">Paul Seed</a><script data-card-contents-for-user="66717177" type="text/json">{"id":66717177,"first_name":"Paul","last_name":"Seed","domain_name":"kcl","page_name":"PaulSeed","display_name":"Paul Seed","profile_url":"https://kcl.academia.edu/PaulSeed?f_ri=194916","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_34032621 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="34032621"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 34032621, container: ".js-paper-rank-work_34032621", }); 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