Utility of hemoglobin-A1C in nondiabetic women with polycystic ovary syndrome

Rami Mortada, Kevin Comerford, K. James Kallail, Siddika E Karakas

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Objective: Hemoglobin A1c (A1C) ≥5.7% is now accepted as a biomarker for identifying individuals at risk for diabetes. Compared to the general population, women with polycystic ovary syndrome (PCOS) have a higher risk for diabetes. Our goal was to determine what glucose homeostasis abnormalities can be identified by A1C ≥5.7% in women with PCOS.Methods: In a cross-sectional study, nondiabetic women with PCOS (according to the National Institutes of Health [NIH] criteria) were divided into 2 groups based on A1C (<5.7% [n = 23] and ≥5.7% [n = 25]). Oral glucose tolerance tests (OGTT) and frequently sampled intravenous glucose tolerance tests (FS-IVGTT) were conducted, and body composition, cardiovascular risk factors, and sex steroid levels were assessed.Results: Compared to women with A1C <5.7%, those with A1C ≥5.7% were older (35.1 ± 1.1 years vs. 31.1 ± 1.1 years; P = .04), had higher glucose levels at fasting and during OGTT, and had a lower insulin sensitivity index (SI: 2.0 ± 0.2 vs. 4.2 ± 0.6; P = .0195) and disposition index (DI: 1,014 ± 82 vs. 1,901 ± 217; P = .011) during FS-IVGTT. They also had higher triglycerides, high-sensitivity C-reactive protein (hs-CRP), and fatty acid-binding protein 4 (FABP4) levels. There was no difference in serum androgen levels.Conclusion: A1C ≥5.7% identified the subgroup of PCOS patients with higher insulin resistance, inadequate compensatory insulin response, impaired glucose disposition, and increased cardiovascular risk factors. Thus, A1C represents an inexpensive and informative biomarker to identify PCOS patients at risk for metabolic abnormalities.

Original languageEnglish (US)
Pages (from-to)284-289
Number of pages6
JournalEndocrine Practice
Issue number2
StatePublished - Mar 1 2013

ASJC Scopus subject areas

  • Endocrinology
  • Endocrinology, Diabetes and Metabolism


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