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Published in: Diabetology & Metabolic Syndrome 1/2018

Open Access 01-12-2018 | Research

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

Authors: Luciana Pavan Antoniolli, Bárbara Limberger Nedel, Tassia Cividanes Pazinato, Leonardo de Andrade Mesquita, Fernando Gerchman

Published in: Diabetology & Metabolic Syndrome | Issue 1/2018

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Abstract

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.
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Metadata
Title
Accuracy of insulin resistance indices for metabolic syndrome: a cross-sectional study in adults
Authors
Luciana Pavan Antoniolli
Bárbara Limberger Nedel
Tassia Cividanes Pazinato
Leonardo de Andrade Mesquita
Fernando Gerchman
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Diabetology & Metabolic Syndrome / Issue 1/2018
Electronic ISSN: 1758-5996
DOI
https://doi.org/10.1186/s13098-018-0365-y

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