Polycystic ovary syndrome with stroke, hypertension, and cardiovascular diseases: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder among women of reproductive age and has been associated with increased risks of hypertension (HTN), stroke, and cardiovascular disease (CVD). However, the magnitude and consistency of these associations remain unclear due to varying diagnostic criteria, study designs, and population characteristics. OBJECTIVE: To systematically review and meta-analyze observational studies evaluating the association between PCOS and the risks of hypertension, stroke, and CVD. METHODS: A systematic literature search was conducted across PubMed, Scopus, Web of Science, Embase, and Cochrane CENTRAL for studies published between January 1, 1990, and January 1, 2025. Eligible studies included cohort, case-control, and cross-sectional designs comparing women with and without PCOS, as defined by established criteria (Rotterdam, NIH, AES, etc.). Data extraction and quality assessment were performed using standardized checklists and the Newcastle-Ottawa Scale. Relative risks (RR) and 95% confidence intervals (CI) were pooled using a random-effects model. RESULTS: : 97.05%). The risk of hypertension was most pronounced in cohort studies (RR: 1.47; 95% CI: 1.23-1.76) and in European populations (RR: 1.74; 95% CI: 1.40-2.16). PCOS was also associated with elevated risks of stroke and CVD, independent of body mass index (BMI). Heterogeneity across studies was moderate to high, and no significant publication bias was detected. CONCLUSION: PCOS may be linked to an increased risk of hypertension, stroke, and CVD across populations and independent of BMI. Given the high heterogeneity among included studies, these findings should be interpreted with caution. These findings highlight the importance of comprehensive cardiovascular risk assessment and management in women with PCOS. More well-designed, large-scale prospective studies are needed to clarify the underlying mechanisms and improve risk stratification.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".