Effect of metformin treatment during pregnancy on women with PCOS: a systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: Some previous studies have found that continued metformin use is beneficial in the management of polycystic ovary syndrome (PCOS) in pregnant women. A systemic review and meta-analysis were needed to more fully assess the effects of metformin on pregnant PCOS patients. METHODS: The literature was fully searched using MEDLINE, EMBASE, SCOPUS, and COCHRANE for continued metformin use during pregnancy in women with PCOS. A systematic review and meta-analysis were performed to evaluate the comprehensive effects of continued metformin treatment on pregnancy-related outcomes in these women. RESULTS: Eleven eligible studies out of 127 relevant publications were included in meta-analysis. The rates of early pregnancy loss and preterm delivery were found to be significantly decreased in metformin-treated PCOS women. A non-significant difference was found in fetal abnormality and fetal birth weight between the metformin-treated and the non-treated groups. The incidence of gestational diabetes mellitus (GDM) and hypertension/preeclampsia were not significantly different in the two groups, probably because of inconsistent results in the subgroup analysis. CONCLUSIONS: Our results showed that continued use during of metformin, during pregnancy in women with PCOS, had no effect on incidence of fetal abnormalities or fetal birth weight. The effects of metformin on GDM and hypertension/preeclampsia should be determined through high-quality randomized controlled trials.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.022 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".