Perinatal outcomes of maternal overweight and obesity in term infants: a population-based cohort study in Canada
Bibliographic record
Abstract
The objective of this study was to assess the impact of increased pre-pregnancy maternal body mass index (BMI) on perinatal outcomes in term, singleton pregnancies who received prenatal care in community-based practices. The sample of 1996 infants included in the study was drawn from the All Our Babies Study, a prospective pregnancy cohort from Calgary. Multivariable logistic regression explored the relationship between the main outcomes, infant birth weight, Apgar score, admission to neonatal intensive care (NICU) and newborn duration of hospitalization, and BMI prior to pregnancy. Approximately 10% of the infants were macrosoms, 1.5% had a low Apgar score (<7 at 5 min), 6% were admitted to intensive care and 96% were discharged within 48 h after delivery. Although the infants of overweight and obese women were more likely to have increased birth weight as compared to infants of normal weight women, there were no differences in Apgar score, admission to NICU, or length of postnatal hospital stay among groups. This study suggests that in otherwise healthy term, singleton pregnancies, obesity does not seem to increase the risk of severe fetal impairment, neonatal admission to intensive care or duration of postnatal hospitalization.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| 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".