The effects of morbid obesity on maternal and neonatal health outcomes: a systematic review and meta‐analyses
Bibliographic record
Abstract
Morbidly obese (Class III, body mass index [BMI] ≥ 40 kg m(-2)) women constitute 8% of reproductive-aged women and are an increasing proportion; however, their pregnancy risks have not yet been well understood. Hence, we performed meta-analyses following the MOOSE (Meta-Analysis of Observational Studies in Epidemiology) guideline, searching Medline and Embase from their inceptions. To examine graded relationships, we compared Class III obesity to Class I and I/II, and separately to normal weight. We found important effects on all three primary outcomes in morbidly obese women: preterm birth <37 weeks was 31% higher compared with Class I (relative risk [RR] 1.31 [1.19, 1.43]) and 20% higher than Class I/II (RR 1.20 [1.13, 1.27]), large-for-gestational age was higher (RR 1.37 [1.29, 1.45] and RR 1.30 [1.24, 1.36] compared with Class I and I/II, respectively), while small-for-gestational age was lower (RR 0.89 [0.84, 0.93] compared with Class I, with nearly identical reductions for Class I/II). Morbidly obese women have higher risks of preterm birth, large-for-gestational age and numerous other adverse maternal and infant health outcomes, relative to not only normal weight but also Class I or I/II obese women. These findings have important implications for screening and care of morbidly obese pregnant women, to try to decrease adverse 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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.037 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".