Examining the provisional guidelines for weight gain in twin pregnancies: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Weight gain during pregnancy has an important impact on maternal and neonatal health. Unlike the Institute of Medicine (IOM) recommendations for weight gain in singleton pregnancies, those for twin gestations are termed "provisional", as they are based on limited data. The objectives of this study were to determine the neonatal and maternal outcomes associated with gaining weight below, within and above the IOM provisional guidelines on gestational weight gain in twin pregnancies, and additionally, to explore ranges of gestational weight gain among women who delivered twins at the recommended gestational age and birth weight, and those who did not. METHODS: A retrospective cohort study of women who gave birth to twins at ≥20 weeks gestation, with a birth weight ≥ 500 g was conducted in Nova Scotia, Canada (2003-2014). Our primary outcome of interest was small for gestational age (<10th percentile). In order to account for gestational age at delivery, weekly rates of 2nd and 3rd trimester weight gain were used to categorize women as gaining below, within, or above guidelines. We performed traditional regression analyses for maternal outcomes, and to account for the correlated nature of the neonatal outcomes in twins, we used generalized estimating equations (GEE). RESULTS: A total of 1482 twins and 741 mothers were included, of whom 27%, 43%, and 30% gained below, within, and above guidelines, respectively. The incidence of small for gestational age in these three groups was 30%, 21%, and 20%, respectively, and relative to gaining within guidelines, the adjusted odds ratios were 1.44 (95% CI 1.01-2.06) for gaining below and 0.92 (95% CI 0.62-1.36) for gaining above. The gestational weight gain in women who delivered twins at 37-42 weeks with average birth weight ≥ 2500 g and those who delivered twins outside of the recommend ranges were comparable to each other and the IOM recommendations. CONCLUSIONS: While gestational weight gain below guidelines for twins was associated with some adverse neonatal outcomes, additional research exploring alternate ranges of gestational weight gain in twin pregnancies is warranted, in order to optimize neonatal and maternal outcomes.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".