Risk of severe maternal morbidity associated with cesarean delivery and the role of maternal age: a population-based propensity score analysis
Bibliographic record
Abstract
BACKGROUND: Short-term maternal complications of cesarean delivery remain uncertain because of confounding by indication. Our objective was to assess whether cesarean delivery is associated with severe acute intra- or postpartum maternal morbidity compared with vaginal delivery, overall and according to the timing of the cesarean. METHODS: We performed a case-control analysis using data from EPIMOMS, a prospective population-based study of deliveries at 22 gestation weeks or later from 6 regions of France in 2012-2013. Cases of intra- or postpartum severe acute maternal morbidity that were not a result of a condition present before delivery were compared with controls randomly selected in a 1/50 ratio. Associations between delivery modes and severe acute maternal morbidity were estimated in a propensity score-matched sample. RESULTS: Among 182 300 deliveries, we identified 1444 cases and 3464 controls. The proportion of cesarean delivery was significantly higher among cases than controls (36.0% v. 18.2%). In the propensity score-matched analysis, cesarean deliveries were significantly associated with a higher risk of severe acute maternal morbidity (adjusted odds ratio [OR] 1.8, 95% confidence interval [CI] 1.5-2.2). This association increased with maternal age and was particularly marked for women aged 35 years or older (adjusted OR 2.9, 95% CI 1.9-4.4). This increased risk was significant for cesarean deliveries during labour in women of all age groups and for those before labour only in women aged 35 years or older (adjusted OR 5.1, 95% CI 2.3-11.0). INTERPRETATION: Cesarean delivery is associated with a higher risk of severe acute maternal morbidity than vaginal delivery, particularly in women aged 35 years and older. Clinical decisions regarding delivery mode should account for this excess risk accordingly.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".