Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/205785 |
Resumo: | Background: This study aimed to determine the ability of commonly used insulin resistance indices to identify the metabolic syndrome. Methods: 183 people referred for outpatient care at the Metabolism Unit of Hospital de Clínicas de Porto Alegre were evaluated with anthropometric, blood pressure, lipid profle, and adiponectin measurements. Glucose tolerance status was determined by 2-h 75-g oral glucose tolerance test and glycosylated hemoglobin. Defnition of metabolic syndrome was based on the Joint Interim Statement of diferent medical associations. Twenty-one indices of insulin resistance were estimated from published equations. The accuracy of these indices was determined by area under the ROC curve (AUC) analysis. In addition, we determined an optimal cut point for each index and its performance as a diagnostic test. Results: The study population was comprised of 183 people (73.2% women; 78.7% white; age 52.6±12.0 years, mean±standard deviation), of whom 140 (76.5%) had metabolic syndrome. The reciprocal of the Gutt index provided the greatest AUC for identifcation of metabolic syndrome, but there were no statistical diferences between Gutt and 11 AUC indices. Gutt presented 86.4% sensitivity and 76.7% specifcity to identify metabolic syndrome. Conclusions: A number of commonly employed indices of insulin resistance are capable of identifying individuals with the metabolic syndrome. |
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Antoniolli, Luciana PavanNedel, Bárbara LimbergerPazinato, Tássia CividanesMesquita, Leonardo de AndradeGerchman, Fernando2020-02-13T04:21:40Z20181758-5996http://hdl.handle.net/10183/205785001110566Background: This study aimed to determine the ability of commonly used insulin resistance indices to identify the metabolic syndrome. Methods: 183 people referred for outpatient care at the Metabolism Unit of Hospital de Clínicas de Porto Alegre were evaluated with anthropometric, blood pressure, lipid profle, and adiponectin measurements. Glucose tolerance status was determined by 2-h 75-g oral glucose tolerance test and glycosylated hemoglobin. Defnition of metabolic syndrome was based on the Joint Interim Statement of diferent medical associations. Twenty-one indices of insulin resistance were estimated from published equations. The accuracy of these indices was determined by area under the ROC curve (AUC) analysis. In addition, we determined an optimal cut point for each index and its performance as a diagnostic test. Results: The study population was comprised of 183 people (73.2% women; 78.7% white; age 52.6±12.0 years, mean±standard deviation), of whom 140 (76.5%) had metabolic syndrome. The reciprocal of the Gutt index provided the greatest AUC for identifcation of metabolic syndrome, but there were no statistical diferences between Gutt and 11 AUC indices. Gutt presented 86.4% sensitivity and 76.7% specifcity to identify metabolic syndrome. Conclusions: A number of commonly employed indices of insulin resistance are capable of identifying individuals with the metabolic syndrome.application/pdfengDiabetology and metabolic syndrome. London. Vol. 10 (2018), 65, 9 p.Síndrome metabólicaResistência à insulinaInsulinaMetabolic syndromeInsulin resistanceInsulin sensitivityAccuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adultsEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001110566.pdf.txt001110566.pdf.txtExtracted Texttext/plain38290http://www.lume.ufrgs.br/bitstream/10183/205785/2/001110566.pdf.txt66eb7609464a25731d517c0e818af069MD52ORIGINAL001110566.pdfTexto completo (inglês)application/pdf1264766http://www.lume.ufrgs.br/bitstream/10183/205785/1/001110566.pdf21ed75bc0a42ad7cf84f2366ac6bd889MD5110183/2057852020-02-14 05:15:57.005242oai:www.lume.ufrgs.br:10183/205785Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2020-02-14T07:15:57Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults |
title |
Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults |
spellingShingle |
Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults Antoniolli, Luciana Pavan Síndrome metabólica Resistência à insulina Insulina Metabolic syndrome Insulin resistance Insulin sensitivity |
title_short |
Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults |
title_full |
Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults |
title_fullStr |
Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults |
title_full_unstemmed |
Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults |
title_sort |
Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults |
author |
Antoniolli, Luciana Pavan |
author_facet |
Antoniolli, Luciana Pavan Nedel, Bárbara Limberger Pazinato, Tássia Cividanes Mesquita, Leonardo de Andrade Gerchman, Fernando |
author_role |
author |
author2 |
Nedel, Bárbara Limberger Pazinato, Tássia Cividanes Mesquita, Leonardo de Andrade Gerchman, Fernando |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Antoniolli, Luciana Pavan Nedel, Bárbara Limberger Pazinato, Tássia Cividanes Mesquita, Leonardo de Andrade Gerchman, Fernando |
dc.subject.por.fl_str_mv |
Síndrome metabólica Resistência à insulina Insulina |
topic |
Síndrome metabólica Resistência à insulina Insulina Metabolic syndrome Insulin resistance Insulin sensitivity |
dc.subject.eng.fl_str_mv |
Metabolic syndrome Insulin resistance Insulin sensitivity |
description |
Background: This study aimed to determine the ability of commonly used insulin resistance indices to identify the metabolic syndrome. Methods: 183 people referred for outpatient care at the Metabolism Unit of Hospital de Clínicas de Porto Alegre were evaluated with anthropometric, blood pressure, lipid profle, and adiponectin measurements. Glucose tolerance status was determined by 2-h 75-g oral glucose tolerance test and glycosylated hemoglobin. Defnition of metabolic syndrome was based on the Joint Interim Statement of diferent medical associations. Twenty-one indices of insulin resistance were estimated from published equations. The accuracy of these indices was determined by area under the ROC curve (AUC) analysis. In addition, we determined an optimal cut point for each index and its performance as a diagnostic test. Results: The study population was comprised of 183 people (73.2% women; 78.7% white; age 52.6±12.0 years, mean±standard deviation), of whom 140 (76.5%) had metabolic syndrome. The reciprocal of the Gutt index provided the greatest AUC for identifcation of metabolic syndrome, but there were no statistical diferences between Gutt and 11 AUC indices. Gutt presented 86.4% sensitivity and 76.7% specifcity to identify metabolic syndrome. Conclusions: A number of commonly employed indices of insulin resistance are capable of identifying individuals with the metabolic syndrome. |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018 |
dc.date.accessioned.fl_str_mv |
2020-02-13T04:21:40Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/205785 |
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1758-5996 |
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001110566 |
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http://hdl.handle.net/10183/205785 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Diabetology and metabolic syndrome. London. Vol. 10 (2018), 65, 9 p. |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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