Regional Variation in the Cesarean Delivery and Assisted Vaginal Delivery Rates
Bibliographic record
Abstract
OBJECTIVE: To examine regional variations in rates of primary cesarean delivery and assisted vaginal delivery in the population of British Columbia, while adjusting for the maternal characteristics and conditions that increase the likelihood of operative delivery. METHODS: Using data from the British Columbia Perinatal Database Registry, we studied all deliveries in British Columbia between 2004 and 2007, excluding women who had a previous cesarean delivery (n=116,839). Our primary outcome of interest was mode of delivery, further defined as delivery by cesarean or assisted vaginal delivery. We calculated crude and risk-adjusted rates of primary cesarean delivery and assisted vaginal delivery across British Columbia's 16 Health Service Delivery Areas and examined cesarean delivery rates by indication for the procedure. RESULTS: Crude primary cesarean delivery and assisted vaginal delivery rates varied markedly across the Health Service Delivery Areas ranging from 16.1 to 27.5 per 100 deliveries, and from 8.6 to 18.6 per 100 deliveries, respectively. The most common indication for cesarean delivery was dystocia, which accounted for 30.0% of all cesarean deliveries and varied more than fivefold across regions. After controlling for maternal characteristics and conditions known to increase the likelihood of cesarean delivery and assisted vaginal delivery, adjusted cesarean delivery rates varied twofold, ranging from 14.7 to 27.6 per 100 deliveries, while adjusted assisted vaginal delivery rates varied by more than twofold, ranging from 6.5 to 15.3 per 100 deliveries. CONCLUSION: Our results illustrate substantial regional variation in the use of cesarean delivery that cannot be explained by patient illness or preferences. This variation likely reflects differences in practitioners' approaches to medical decision-making. LEVEL OF EVIDENCE: II.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".