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Updated: Mar 14, 2026

Evaluation of Hepatic Glucose Production in a Polycystic Ovary Syndrome Mouse Model
Published on: March 5, 2022
Extended Oral Glucose Tolerance Test Unmasks Intermediate Metabolic Phenotypes in Polycystic Ovary Syndrome
Sanhu Wang1, Xiqiang Gao2, Fuxing Li1
1Department of Clinical Laboratory, Hunan University of Medicine General Hospital, Huaihua, Hunan, People's Republic of China.
Objective:
This study aims to investigate the efficacy of an extended oral glucose tolerance test (OGTT) incorporating 1- and 3-h time points in detecting early, heterogeneous glycemic phenotypes in polycystic ovary syndrome (PCOS).
Methods:
In this cross-sectional study, 103 treatment-naive patients with PCOS underwent a 75-g OGTT with measurements of glucose and insulin taken at 0, 1, 2, and 3 h. Participants were stratified into four groups: normal control, isolated 1-h glucose elevation (1-h plasma glucose [PG] ≥ 8.6 mmol/L), isolated 3-h glucose elevation (3-h PG > 6.1 mmol/L), and dysglycemia defined by conventional criteria. Comprehensive metabolic and endocrine profiles were evaluated and compared.
Results:
Two distinct early glycemic phenotypes were identified: isolated 1-h glucose elevation (13.6%, 14/103) and isolated 3-h glucose elevation (20.4%, 21/103). The isolated 3-h elevation group exhibited an intermediate phenotype characterized by significant central adiposity, hyperandrogenism, and menstrual irregularities, despite systemic insulin resistance (IR) levels comparable to those of the normoglycemic group. Conversely, the isolated 1-h elevation group exhibited transient hyperinsulinemic hyperglycemia and elevated low-density lipoprotein cholesterol (LDL-C) levels. Both phenotypes were undetected by standard glycemic criteria.
Conclusion:
An extended OGTT reveals two prevalent yet distinct early glycemic phenotypes in PCOS, suggesting heterogeneous pathophysiological pathways that may inform dynamic, phenotype-stratified assessment for risk stratification and targeted intervention. However, clinical implementation requires validation through prospective studies.
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