Pregnancy weight gain by gestational age and stillbirth: a population‐based cohort study
Bibliographic record
Abstract
OBJECTIVE: To study the association between total and early pregnancy (<22 completed weeks) weight gain and risk of stillbirth, stratified by early-pregnancy body mass index (BMI). DESIGN: Population-based cohort study. SETTING: Stockholm-Gotland Region, Sweden. POPULATION: Pregnant women with singleton births (n = 160 560). METHODS: Pregnancy weight gain was standardised into gestational age-specific z-scores. For analyses of total pregnancy weight gain, a matched design with an incidence density sampling approach was used. Findings were also contrasted with current Institute of Medicine (IOM) weight gain recommendations. MAIN OUTCOME MEASURES: Stillbirth defined as fetal death at ≥22 completed weeks of gestation. RESULTS: For all BMI categories, there was no statistical association between total or early pregnancy weight gain and stillbirth within the range of a weight gain z-score of -2.0 SD to +2.0 SD. Among normal-weight women, the adjusted odds ratio of stillbirth for lower (-2.0 to -1.0 SD) and higher (+1.0 to +1.9 SD) total weight gain was 0.85 (95% CI; 0.48-1.49) and 1.03 (0.60-1.77), respectively, as compared with the reference category. Further, there were no associations between total or early pregnancy weight gain and stillbirth within the range of weight gain currently recommended by the IOM. For the majority of the BMI categories, the point estimates at the extremes of weight gain values (<-2.0SD and ≥2.0 SD) suggested protective effects of low weight gain and increased risks of high weight gain, but estimates were imprecise and not statistically significant. CONCLUSION: We found no associations between total or early pregnancy weight gain and stillbirth across the range of weight gain experienced by most women. TWEETABLE ABSTRACT: There was no association between weight gain during pregnancy and stillbirth among most women.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".