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

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, li...

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Autores principales: Antoniolli, Luciana Pavan, Nedel, Bárbara Limberger, Pazinato, Tassia Cividanes, de Andrade Mesquita, Leonardo, Gerchman, Fernando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102896/
https://www.ncbi.nlm.nih.gov/pubmed/30151057
http://dx.doi.org/10.1186/s13098-018-0365-y
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author Antoniolli, Luciana Pavan
Nedel, Bárbara Limberger
Pazinato, Tassia Cividanes
de Andrade Mesquita, Leonardo
Gerchman, Fernando
author_facet Antoniolli, Luciana Pavan
Nedel, Bárbara Limberger
Pazinato, Tassia Cividanes
de Andrade Mesquita, Leonardo
Gerchman, Fernando
author_sort Antoniolli, Luciana Pavan
collection PubMed
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 profile, and adiponectin measurements. Glucose tolerance status was determined by 2-h 75-g oral glucose tolerance test and glycosylated hemoglobin. Definition of metabolic syndrome was based on the Joint Interim Statement of different 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 identification of metabolic syndrome, but there were no statistical differences between Gutt and 11 AUC indices. Gutt presented 86.4% sensitivity and 76.7% specificity to identify metabolic syndrome. CONCLUSIONS: A number of commonly employed indices of insulin resistance are capable of identifying individuals with the metabolic syndrome. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13098-018-0365-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-61028962018-08-27 Accuracy of insulin resistance indices for metabolic syndrome: a cross-sectional study in adults Antoniolli, Luciana Pavan Nedel, Bárbara Limberger Pazinato, Tassia Cividanes de Andrade Mesquita, Leonardo Gerchman, Fernando Diabetol Metab Syndr Research 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 profile, and adiponectin measurements. Glucose tolerance status was determined by 2-h 75-g oral glucose tolerance test and glycosylated hemoglobin. Definition of metabolic syndrome was based on the Joint Interim Statement of different 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 identification of metabolic syndrome, but there were no statistical differences between Gutt and 11 AUC indices. Gutt presented 86.4% sensitivity and 76.7% specificity to identify metabolic syndrome. CONCLUSIONS: A number of commonly employed indices of insulin resistance are capable of identifying individuals with the metabolic syndrome. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13098-018-0365-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-08-20 /pmc/articles/PMC6102896/ /pubmed/30151057 http://dx.doi.org/10.1186/s13098-018-0365-y Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Antoniolli, Luciana Pavan
Nedel, Bárbara Limberger
Pazinato, Tassia Cividanes
de Andrade Mesquita, Leonardo
Gerchman, Fernando
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
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_short 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
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102896/
https://www.ncbi.nlm.nih.gov/pubmed/30151057
http://dx.doi.org/10.1186/s13098-018-0365-y
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