A meta-analysis of pregnancy outcomes in women with polycystic ovary syndrome
Bibliographic record
Abstract
Polycystic ovary syndrome (PCOS) is a common reproductive disorder associated with many characteristic features, including hyperandrogenaemia, insulin resistance and obesity which may have significant implications for pregnancy outcomes and long-term health of the woman. This meta-analysis was conducted to evaluate the risk of pregnancy and neonatal complications in women with PCOS. Electronic databases were searched for the following MeSH headings: PCOS, hyperandrogenism, pregnancy outcome, pregnancy complications, diabetes mellitus, type II. A handsearch of human reproduction and fertility and sterility was also conducted. Studies in which pregnancy outcomes in women with PCOS were compared with controls were considered for inclusion in this meta-analysis. Fifteen of 525 identified studies were included, involving 720 women presenting with PCOS and 4505 controls. Women with PCOS demonstrated a significantly higher risk of developing gestational diabetes [odds ratio (OR) 2.94; 95% confidence interval (CI): 1.70-5.08], pregnancy-induced hypertension (OR 3.67; 95% CI: 1.98-6.81), pre-eclampsia (OR 3.47; 95% CI: 1.95-6.17) and preterm birth (OR 1.75; 95% CI: 1.16-2.62). Their babies had a significantly higher risk of admission to a neonatal intensive care unit (OR 2.31; 95% CI: 1.25-4.26) and a higher perinatal mortality (OR 3.07; 95% CI: 1.03-9.21), unrelated to multiple births. In conclusion, women with PCOS are at increased risk of pregnancy and neonatal complications. Pre-pregnancy, antenatal and intrapartum care should be aimed at reducing these risks.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.048 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".