Context/Objective: Current diagnostic criteria for polycystic ovary syndrome (PCOS) have generated distinct PCOS phenotypes, based on the different diagnostic feature combinations found in each patient. Our aim was to assess whether either each single diagnostic feature or their combinations into the PCOS phenotypes may predict insulin resistance in these women.Patients/Design: One hundred thirty-seven consecutive Caucasian women with PCOS, diagnosed by the Rotterdam criteria, underwent accurate assessment of diagnostic and metabolic features. Insulin sensitivity was measured by the glucose clamp technique.Results: Among PCOS women, 84.7% had hyperandrogenism, 84.7% chronic oligoanovulation, and 89% polycystic ovaries. According to the individual combinations of these features‬, 69.4% of women had the Classic, 15.3% the Ovulatory and 15.3% the Normoandrogenic phenotype. Most subjects (71.4%) were insulin resistant. However, insulin resistance frequency differed between phenotypes, being 80.4, 65.0 and 38.1% respectively in the three subgroups (p<0.001). Although none of the PCOS diagnostic features per se was associated with the impairment in insulin action, after adjustment for covariates, the Classic phenotype and, to a lesser extent, the Ovulatory phenotype were independently associated with insulin resistance, whereas the Normoandrogenic phenotype was not. Metabolic syndrome frequency was also different between phenotypes (p=0.030).Conclusions: There is a scale of metabolic risk among PCOS women. Although no single diagnostic features of PCOS are independently associated with insulin resistance, their combinations, which define PCOS phenotypes, may allow physicians to establish which women deserve metabolic screening. In metabolic terms, women belonging to the Normoandrogenic phenotype behave as a separate group.

Divergences in Insulin Resistance Between the Different Phenotypes of the Polycystic Ovary Syndrome.

MOGHETTI, Paolo;BONIN, Cecilia;DI SARRA, Daniela;ZANOLIN, Maria Elisabetta;BONORA, Enzo
2013-01-01

Abstract

Context/Objective: Current diagnostic criteria for polycystic ovary syndrome (PCOS) have generated distinct PCOS phenotypes, based on the different diagnostic feature combinations found in each patient. Our aim was to assess whether either each single diagnostic feature or their combinations into the PCOS phenotypes may predict insulin resistance in these women.Patients/Design: One hundred thirty-seven consecutive Caucasian women with PCOS, diagnosed by the Rotterdam criteria, underwent accurate assessment of diagnostic and metabolic features. Insulin sensitivity was measured by the glucose clamp technique.Results: Among PCOS women, 84.7% had hyperandrogenism, 84.7% chronic oligoanovulation, and 89% polycystic ovaries. According to the individual combinations of these features‬, 69.4% of women had the Classic, 15.3% the Ovulatory and 15.3% the Normoandrogenic phenotype. Most subjects (71.4%) were insulin resistant. However, insulin resistance frequency differed between phenotypes, being 80.4, 65.0 and 38.1% respectively in the three subgroups (p<0.001). Although none of the PCOS diagnostic features per se was associated with the impairment in insulin action, after adjustment for covariates, the Classic phenotype and, to a lesser extent, the Ovulatory phenotype were independently associated with insulin resistance, whereas the Normoandrogenic phenotype was not. Metabolic syndrome frequency was also different between phenotypes (p=0.030).Conclusions: There is a scale of metabolic risk among PCOS women. Although no single diagnostic features of PCOS are independently associated with insulin resistance, their combinations, which define PCOS phenotypes, may allow physicians to establish which women deserve metabolic screening. In metabolic terms, women belonging to the Normoandrogenic phenotype behave as a separate group.
2013
Polycystic ovary syndrome; Insulin resistance; Metabolic syndrome; PCOS phenotypes; Testosterone; clamp
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/527349
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