Maternal, Fetal, and Infant Outcomes Associated With Bariatric Surgery
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to determine the association between bariatric surgery and maternal, fetal, and infant outcomes. BACKGROUND: Obesity during pregnancy is a risk factor for adverse pregnancy outcomes. Bariatric surgery is the most effective weight loss treatment but the impact of bariatric surgery on pregnancy outcomes remains poorly characterized. METHODS: This was a population-based, matched cohort study of prospective databases in Ontario, Canada. Patients with obesity who received bariatric surgery from 2010 to 2016 and subsequently became pregnant matched on multiple factors to nonsurgical pregnant patients with obesity. The primary outcomes of interest were the incidence included of gestational diabetes, preeclampsia/hemolysis, elevated liver enzymes, and low platelets syndrome, small for gestational age, large for gestational age, and a composite of severe fetal/infant morbidity/mortality. Multivariable regression evaluated outcomes. RESULTS: Six hundred eighty patients who underwent bariatric surgery and later became pregnant were matched to 2002 pregnant patients with obesity. Gestational diabetes occurred in 8.7% of the surgery group and 18.8% of the nonsurgical group [adjusted OR (aOR) 0.29, 95% CI: 0.21-0.40, P<0.001]. A lower incidence of preeclampsia/hemolysis, elevated liver enzymes and low platelets was observed postsurgery (aOR 0.20, 95% CI: 0.13-0.31, P<0.001). Bariatric surgery impacted small for gestational age (aOR 2.74, 95% CI: 2.04-3.70, P<0.001) and large for gestational age (aOR 0.25, 95% CI: 0.18-0.36, P<0.001). There were no observed associations between bariatric surgery and any adverse fetal or infant outcomes. A lower composite severe fetal/infant morbidity/mortality was observed postsurgery (aOR 0.73, 95% CI: 0.54-0.97, P<0.05). CONCLUSIONS: Pregnancy after bariatric surgery appears safe and was associated with a reduced risk of several obesity related adverse pregnancy 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".