Adherence to Guidelines on the Management of Dystocia and Cesarean Section Rates
Bibliographic record
Abstract
The purpose of this study was to investigate to what extent the Society of Obstetricians and Gynecologists of Canada (SOGC) guidelines on dystocia are being followed, and whether adherence to the guidelines is related to cesarean section rates. Data were extracted from a maternity database for nulliparous women with singleton, cephalic pregnancies at 37 or more completed weeks of gestation for a 4-year period. Patients delivered by elective cesarean section were excluded. Data were examined to determine whether those who had a cesarean section for dystocia in the first stage of labor fulfilled SOGC guidelines. In addition, the obstetricians were divided into two groups (high or low) according to their cesarean section rate for dystocia to determine whether a higher section rate was associated with an increased guideline violation rate. There were 239 nulliparous women who had a cesarean section for dystocia in the first stage of labor. The guidelines were followed in 47.7% of spontaneous labors and 77.5% of inductions. The mean section rate for dystocia in the first stage of labor was 10.8% in the high group and 6.6% in the low group, and the incidence of guideline violations in these groups was 48.0% and 39.6%, respectively ( P = 0.07). The study had a power of 0.88 to detect a 40% difference in guideline violation rates between the two groups. We conclude that many women have cesarean section for dystocia performed without fulfilling SOGC guidelines.
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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 | 0.007 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".