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The Association Between Triglyceride-Glucose Index and Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis Across Different Populations Publisher Pubmed



A Javidan AMIN ; A Azarboo ALIREZA ; S Jalali SAYEH ; P Fallahtafti PARISA ; S Moayyed SHABBOO ; M Ghaemi MARJAN ; Am Tarafdari Azam MANSHADI ; S Hantoushzade SEDIGHEH
Authors

Source: Journal of Ovarian Research Published:2025


Abstract

Background: Polycystic ovary syndrome (PCOS) is a common disorder affecting women of reproductive age. The triglyceride-glucose (TyG) index, a surrogate marker of insulin resistence, has gained attention for its simplicity and diagnostic accuracy across metabolic disorders. This study aims to assess the association of the TyG index with PCOS. Methods: A systematic review and meta-analysis were conducted following PRISMA guidelines. PubMed, Scopus, Embase, and Web of Science were searched up to December 2024. Observational studies reporting TyG indices in PCOS and control groups were included. Subgroup and meta-regression analyses explored sources of heterogeneity. Sensitivity analysis and publication bias assessments ensured robustness. Results: Fifteen studies (7,175 participants) were analyzed. The TyG index was significantly higher in women with PCOS compared to non-PCOS controls (SMD 0.34, 95% CI 0.14–0.54). Subgroup analysis revealed a significant association in Chinese studies (SMD 0.42, 95% CI 0.35–0.49) and cross-sectional studies (SMD 0.45, 95% CI 0.32–0.57). The TyG index exhibited excellent diagnostic accuracy for distinguishing PCOS patients with metabolic syndrome (AUC 0.91, 95% CI 0.85–0.96). Similarly, the TyG-BMI index showed a significant association with PCOS (SMD 0.34, 95% CI 0.10–0.57) and considerable diagnostic performance for insulin resistance in PCOS population (AUC 0.81, 95% CI 0.75–0.88). Meta-regression analysis identified no significant impact of age, body mass index (BMI), or lipid profiles on heterogeneity. Conclusions: The TyG index demonstrates strong potential for PCOS screening, though cut-off values require further validation and accuracy may differ across populations. © 2025 Elsevier B.V., All rights reserved.
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