Birth outcomes following cesarean delivery on maternal request: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Data on the effect of cesarean delivery on maternal request (CDMR) on maternal and neonatal outcomes are inconsistent and often limited by inadequate case definitions and other methodological issues. Our objective was to evaluate the trends, determinants and outcomes of CDMR using an intent-to-treat approach. METHODS: We designed a population-based retrospective cohort study using data on low-risk pregnancies in Ontario, Canada (April 2012-March 2018). We assessed temporal trends and determinants of CDMR. We estimated the relative risks for component and composite outcomes used in the Adverse Outcome Index (AOI) related to planned CDMR compared with planned vaginal delivery using generalized estimating equation models. We compared the Weighted Adverse Outcome Score (WAOS) and the Severity Index (SI) across planned modes of delivery using analysis of variance. RESULTS: = 420 383) had a planned vaginal delivery. The prevalence of CDMR remained stable over time at 3.9% of all cesarean deliveries. Factors associated with CDMR included late maternal age, higher education, conception via in vitro fertilization, anxiety, nulliparity, being White, delivery at a hospital providing higher levels of maternal care and obstetrician-based antenatal care. Women who planned CDMR had a lower risk of adverse outcomes than women who planned vaginal delivery (adjusted relative risk 0.42, 95% confidence interval [CI] 0.33 to 0.53). The WAOS was lower for planned CDMR than planned vaginal delivery (mean difference -1.28, 95% CI -2.02 to -0.55). The SI was not statistically different between groups (mean difference 3.6, 95% CI -7.4 to 14.5). INTERPRETATION: Rates of CDMR have not increased in Ontario. Planned CDMR is associated with a decreased risk of short-term adverse outcomes compared with planned vaginal delivery. Investigation into the long-term implications of CDMR is warranted.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".