Effectiveness of metformin to pregnant women with PCOS to reduce spontaneous abortion and gestational diabetes mellitus: a protocol for an overview of reviews
Bibliographic record
Abstract
INTRODUCTION: Polycystic ovary syndrome (PCOS) is a globally prevalent endocrinological disorder and has been associated with poor pregnancy outcomes, including a higher rate of gestational diabetes and miscarriage. Metformin is among the drugs investigated to improve the prognosis of pregnant women with PCOS. OBJECTIVE: To conduct an overview of systematic reviews examining the effects of metformin versus placebo or no intervention throughout pregnancy among pregnant women with a preconception PCOS diagnosis to reduce the incidence of miscarriage and gestational diabetes. METHODS AND ANALYSIS: We will perform an overview of systematic reviews by searching Embase, PubMed, Virtual Health Library, Cochrane Central Register of Controlled Trials, Trip Database, Scopus, Web of Science and Cumulative Index to Nursing and Allied Health Literature from inception to 17 August 2023. Language, publication status and year indexed or published filters will not be applied. Two reviewers will independently screen and select papers, assess their quality, evaluate their risk of bias and collect the data. The included reviews will be summarised narratively. The quality and risk of bias of the systematic review and meta-analysis studies included will be assessed using AMSTAR 2 (A Measurement Tool to Assess Systematic Reviews, Second Version) and ROBIS (Risk of Bias in Systematic Reviews), respectively. ETHICS AND DISSEMINATION: This overview of reviews will analyse data from systematic reviews on the use of metformin for prepregnancy diagnosis of PCOS to reduce adverse outcomes. As there will be no primary data collection, a formal ethical analysis is unnecessary. The study outcomes will be submitted to a peer-reviewed journal and presented at conferences. PROSPERO REGISTRATION NUMBER: CRD42023441488.
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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 | 0.037 | 0.060 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.021 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.062 | 0.009 |
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".