Risk associated with planned mode of delivery in women with obesity: a large population-based retrospective cohort study
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: As the pregnancy progresses, a decision about planned mode of delivery must be made. There is no consensus on optimal mode of delivery among pregnant women with obesity. We aimed to assess the risks associated with planned mode of delivery in women with obesity. METHODS: This large population-based retrospective cohort study included 27472 nulliparous women with obesity who had live, singleton, and uncomplicated term gestations between April 1st 2012 and March 31st 2019. Planned mode of delivery included waiting for spontaneous labor, a plan for induction of labor, and planned non-labor cesarean section (NLCS). NLCS was defined as an elective CS that would happen before the pregnant woman goes into labor. The most common reasons for NLCS include maternal request, fetal position, and repeated CS. Adverse Outcome Index (AOI) was the primary outcome, a binary composite of 10 maternal-neonatal outcomes. Overall, maternal-specific, and neonatal-specific AOI scores were analyzed. Analyses were conducted using multivariable regression models and were stratified by each week of gestational age and by obesity class. RESULTS: Planned NLCS was associated with reduced risk of overall, maternal-specific, and neonatal-specific AOI by 41% (adjusted risk ratio [aRR]: 0.59, 95% confidence interval [CI]: 0.50-0.70), 54% (aRR: 0.46, 95% CI: 0.35-0.60), and 30% (aRR: 0.70, 95% CI: 0.57-0.87) respectively when compared to spontaneous labor at term gestation. There was no statistically significant difference in overall AOI when comparing planned induction of labor to spontaneous labor (aRR: 1.03, 95% CI: 0.96-1.10). CONCLUSION: Among women with obesity, NLCS may be considered as an option for planned mode of delivery due to the decreased AOI risk. However, further research on the association between NLCS and severe outcomes is needed. Shared decision making between patient and practitioner regarding plan for delivery remains paramount in the provision of quality obstetrical care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".