Weight Loss Instead of Weight Gain within the Guidelines in Obese Women during Pregnancy: A Systematic Review and Meta-Analyses of Maternal and Infant Outcomes
Bibliographic record
Abstract
BACKGROUND: Controversy exists about how much, if any, weight obese pregnant women should gain. While the revised Institute of Medicine guidelines on gestational weight gain (GWG) in 2009 recommended a weight gain of 5-9 kg for obese pregnant women, many studies suggested even gestational weight loss (GWL) for obese women. OBJECTIVES: A systematic review was conducted to summarize pregnancy outcomes in obese women with GWL compared to GWG within the 2009 Institute of Medicine guidelines (5-9 kg). DESIGN: Five databases were searched from 1 January 2009 to 31 July 2014. The Cochrane Handbook for Systematic Reviews of Interventions and the PRISMA Statement were followed. A modified version of the Newcastle-Ottawa scale was used to assess individual study quality. Small for gestational age (SGA), large for gestational age (LGA) and preterm birth were our primary outcomes. RESULTS: Six cohort studies were included, none of which assessed preterm birth. Compared to GWG within the guidelines, women with GWL had higher odds of SGA <10th percentile (adjusted odds ratio [AOR] 1.76; 95% confidence interval [CI] 1.45-2.14) and SGA <3rd percentile (AOR 1.62; 95% CI 1.19-2.20) but lower odds of LGA >90th percentile (AOR 0.57; 95% CI 0.52-0.62). There was a trend towards a graded relationship between SGA <10th percentile and each of three obesity classes (I: AOR 1.73; 95% CI 1.53-1.97; II: AOR 1.63; 95% CI 1.44-1.85 and III: AOR 1.39; 95% CI 1.17-1.66, respectively). CONCLUSION: Despite decreased odds of LGA, increased odds of SGA and a lack of information on preterm birth indicate that GWL should not be advocated in general for obese 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 | 0.017 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.033 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".