Reduction of maternal and neonatal harm through prevention of the primary Cesarean section
Bibliographic record
Abstract
While there are clear life-saving indications for Cesarean section (C-section), rates of this procedure have seen a continued rise without a concomitant improvement in maternal or neonatal outcomes. There is some evidence that outcomes may actually be worse for low-risk C-sections versus vaginal delivery. However, this is not necessarily common knowledge for healthcare providers, and therefore, their patients. Measures to safely reduce the C-section rate target management of labour arrest and specific indications for progression to C-section. In the active phase of the first stage of labour, C-section should be considered only in cases of failure to progress after 4 hours of adequate uterine contraction, or 6 hours of inadequate contraction. In the second stage of labour, expectant management of 3 hours of pushing in nulliparous women and 2 hours in multiparous women is safe and appropriate. Furthermore, manual rotation and operative vaginal delivery in the second stage are reasonable alternatives to C-section. Expectant management is also appropriate for certain non-reassuring fetal heart rate tracings. In post-dates pregnancies, induction of labour reduces both rates of C-section and neonatal mortality. Finally, evidence supports the use of external cephalic version in breech presentation as well as a more conservative approach to suspected macrosomia and multiple pregnancy. Taken together, these measures target the most common indications for progression to C-section and can allow us to safely reduce the C-section rate. Educating patients and physicians on the risks of the procedure and reasonable alternatives can improve outcomes for mothers and neonates.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".