Dietary and/or physical activity interventions in women with overweight or obesity prior to fertility treatment: protocol for a systematic review and individual participant data meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Dietary and/or physical activity interventions are often recommended for women with overweight or obesity as the first step prior to fertility treatment. However, randomised controlled trials (RCTs) so far have shown inconsistent results. Therefore, we propose this individual participant data meta-analysis (IPDMA) to evaluate the effectiveness and safety of dietary and/or physical activity interventions in women with infertility and overweight or obesity on reproductive, maternal and perinatal outcomes and to explore if there are subgroup(s) of women who benefit from each specific intervention or their combination (treatment-covariate interactions). METHODS AND ANALYSIS: We will include RCTs with dietary and/or physical activity interventions as core interventions prior to fertility treatment in women with infertility and overweight or obesity. The primary outcome will be live birth. We will search MEDLINE, Embase, Cochrane Central Register of Controlled Trials and trial registries to identify eligible studies. We will approach authors of eligible trials to contribute individual participant data (IPD). We will perform risk of bias assessments according to the Risk of Bias 2 tool and a random-effects IPDMA. We will then explore treatment-covariate interactions for important participant-level characteristics. ETHICS AND DISSEMINATION: Formal ethical approval for the project (Venus-IPD) was exempted by the medical ethics committee of the University Medical Center Groningen (METc code: 2021/563, date: 17 November 2021). Data transfer agreement will be obtained from each participating institute/hospital. Outcomes will be disseminated internationally through the collaborative group, conference presentations and peer-reviewed publication. PROSPERO REGISTRATION NUMBER: CRD42021266201.
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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 | 0.060 | 0.097 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.026 | 0.033 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.057 | 0.007 |
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".