Antoniolli LP, Nedel BL, Pazinato TC, de Andrade Mesquita L, Gerchman F. Accuracy of insulin resistance indices for metabolic syndrome: a cross-sectional study in adults.
Diabetol Metab Syndr 2018;
10:65. [PMID:
30151057 PMCID:
PMC6102896 DOI:
10.1186/s13098-018-0365-y]
[Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Accepted: 08/11/2018] [Indexed: 02/04/2023] Open
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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