Accuracy of insulin resistance indices for metabolic syndrome : a cross-sectional study in adults

Detalhes bibliográficos
Autor(a) principal: Antoniolli, Luciana Pavan
Data de Publicação: 2018
Outros Autores: Nedel, Bárbara Limberger, Pazinato, Tássia Cividanes, Mesquita, Leonardo de Andrade, Gerchman, Fernando
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.
id UFRGS-2_86d84c7144a3ef3e5826e7671caacb33
oai_identifier_str oai:www.lume.ufrgs.br:10183/205785
network_acronym_str UFRGS-2
network_name_str Repositório Institucional da UFRGS
repository_id_str
spelling 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
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10183/205785
dc.identifier.issn.pt_BR.fl_str_mv 1758-5996
dc.identifier.nrb.pt_BR.fl_str_mv 001110566
identifier_str_mv 1758-5996
001110566
url 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.
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFRGS
instname:Universidade Federal do Rio Grande do Sul (UFRGS)
instacron:UFRGS
instname_str Universidade Federal do Rio Grande do Sul (UFRGS)
instacron_str UFRGS
institution UFRGS
reponame_str Repositório Institucional da UFRGS
collection Repositório Institucional da UFRGS
bitstream.url.fl_str_mv http://www.lume.ufrgs.br/bitstream/10183/205785/2/001110566.pdf.txt
http://www.lume.ufrgs.br/bitstream/10183/205785/1/001110566.pdf
bitstream.checksum.fl_str_mv 66eb7609464a25731d517c0e818af069
21ed75bc0a42ad7cf84f2366ac6bd889
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)
repository.mail.fl_str_mv
_version_ 1815447707818393600