PCOS, coronary heart disease, stroke and the influence of obesity: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Patients with polycystic ovary syndrome (PCOS) are at risk of arterial disease. We examined the risk of (non)fatal coronary heart disease (CHD) or stroke in patients with PCOS and ovulatory women without PCOS, and assessed whether obesity might explain a higher risk of CHD or stroke. METHODS: We performed a systematic review and meta-analysis of controlled observational studies. Four definitions of PCOS were considered: World Health Organization type II anovulation, National Institutes of Health criteria, Rotterdam consensus and Androgen-excess criteria. Obesity was defined as BMI > 30 kg/m(2) and/or waist circumference >88 cm. Study quality was assessed using the Newcastle-Ottawa Scale. Primary outcome was fatal/non-fatal CHD or stroke. Definitions of CHD and stroke were based on criteria used by the various authors. The effect measure was the pooled relative risk in a random effects model. Risk ratios and rate ratios were combined here. RESULTS: After identifying 1340 articles, 5 follow-up studies published between 2000 and 2008 were included. The studies showed heterogeneity in design, definitions and quality. In a random effects model the relative risk for CHD or stroke were 2.02 comparing women with PCOS to women without PCOS (95% confidence interval 1.47, 2.76). Pooling the two studies with risk estimates adjusted for BMI showed a relative risk of 1.55 (1.27, 1.89). CONCLUSIONS: This meta-analysis showed a 2-fold risk of arterial disease for patients with PCOS relative to women without PCOS. BMI adjustment did not affect this finding, suggesting the increased risk for cardiovascular events in PCOS is not completely related to a higher BMI in patients with PCOS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".