SynthesisJournal of ovarian research2026
Polycystic ovary syndrome with metabolic syndrome and diabetes: a systematic review and meta-analysis.
Synthesis in Journal of ovarian research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
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Abstract
purposePolycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder linked to metabolic complications. This study systematically reviewed and meta-analyzed the association between PCOS and the risk of Metabolic Syndrome and Diabetes Mellitus.
methodsA comprehensive search was conducted in PubMed, Scopus, Web of Science, Embase, and Cochrane CENTRAL for studies published between 1990 and 2025, following PRISMA guidelines. Observational studies (cross-sectional, case-control, cohort) diagnosing PCOS by Rotterdam, NIH, or AES criteria were included. Data extraction used a standardized checklist, and study quality was assessed with the Newcastle-Ottawa Scale. Pooled relative risks (RR) were calculated using the DerSimonian-Laird random-effects model. Heterogeneity was evaluated with Cochrane Q and I², and subgroup analyses explored variations.
resultsFrom 3,747 articles, 44 studies (54 effect sizes) on DM and six on MetS were included. Women with PCOS had a 72% higher risk of DM (RR: 1.72, 95% CI: 1.43-2.06), strongest with Rotterdam criteria (RR: 1.86). Risk was highest for gestational DM (RR: 2.05) and in women > 40 years (RR: 1.88). For MetS, PCOS increased risk by 48% (RR: 1.48, 95% CI: 1.15-1.90), strongest with NIH criteria (RR: 3.41). Geographic differences showed higher DM risk in Europe (RR: 1.97) and MetS in Asia (RR: 1.99). Heterogeneity was substantial, but no publication bias was detected.
conclusionPCOS significantly elevates risks of DM and MetS, influenced by diagnostic criteria, age, BMI, and geography. Standardized diagnostic approaches and longitudinal studies are essential to refine risk assessment and guide targeted interventions.
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