Metformin for the Prevention of Hyperemesis Gravidarum: An Observational Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate if metformin treatment prior to pregnancy reduces the likelihood of nausea and vomiting in pregnancy (NVP) and hyperemesis gravidarum (HG) compared to no exposure. DESIGN: Observational cohort study. SETTING: The MotherToBaby Pregnancy Studies in the United States and Canada. SAMPLE: Live-born singleton pregnancies enrolled between 2012 and 2023, with HG diagnosis data available. METHODS: Data were collected via maternal telephone interviews during pregnancy and medical records. Outcomes were compared between women with preconceptional metformin exposure and those unexposed to metformin before or during pregnancy. MAIN OUTCOME MEASURES: Risk ratios (RR) and 95% confidence intervals (CI) for HG and NVP, and mean duration of NVP symptoms. RESULTS: Data from 80 women exposed to metformin before conception and 4411 non-exposed women were analysed. In this cohort, the frequency of women with HG was lower among the exposed than the unexposed women (n = 1/80; 1.25% vs. n = 97/4411; 2.20%), but the study was not powered to detect statistical significance (adjusted RR 0.50, 95% CI 0.07-3.39). Rates of NVP were similar between groups (n = 32/80; 88.90% in the exposed and n = 1664/4111; 82.60% in the unexposed), with adjusted RR 1.06; 95% CI, 0.94-1.19. The mean duration of NVP symptoms was also similar between the groups. CONCLUSIONS: This cohort study found a lower rate of HG in the preconceptional metformin-exposed group compared to unexposed, although the study was not powered to identify a significant association. Rated and durations NVP were similar between groups. These are relevant to guiding future clinical trials on the efficacy of metformin as a prophylactic agent for HG.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".