Maternal and perinatal outcomes associated with a trial of labour after previous caesarean section in sub‐Saharan countries
Bibliographic record
Abstract
OBJECTIVE: To assess the risks of uterine rupture, maternal and perinatal outcomes associated with a trial of labour (TOL) after one previous caesarean were compared with having an elective repeated caesarean section (ERCS) without labour in low-resource settings. DESIGN: A prospective 4-year observational study. SETTING: Senegal and Mali. SAMPLE: A cohort of 9712 women with one previous caesarean delivery. METHODS: Maternal and perinatal outcomes were compared between 8083 women who underwent a TOL and 1629 women who had an ERCS. Perinatal and maternal outcomes were then stratified according to the presence or absence of risk factors associated with vaginal birth after caesarean section. These outcomes were adjusted on maternal, perinatal and institutional characteristics. MAIN OUTCOME MEASURES: The risks of uterine rupture, maternal complication and perinatal mortality associated with TOL after one previous caesarean as compared with ERCS, RESULTS: The risks of hospital-based maternal complication [adjusted odds ratio (OR) 1.52; 95% CI 1.09-2.13; P = 0.013] and perinatal mortality (adjusted OR 4.53; 95% CI 2.30-9.92; P < 0.001) were significantly higher in women with a TOL compared with women who had an ERCS. However, when restricted to low-risk women, these differences were not significant (adjusted OR 0.90, 95% CI 0.55-1.46, P = 0.68, and adjusted OR 1.13; 95% CI 0.75-1.86; P = 0.53, for each outcome, respectively). Uterine rupture occurred in 25 (0.64%) of 3885 low-risk women compared with 70 (1.66%) of 4198 women with unfavourable risk factors. CONCLUSION: Low-risk women have no increased risk of maternal complications or perinatal mortality compared with women with one or more unfavourable factors. TWEETABLE ABSTRACT: Low-risk women have a lower risk of maternal complications or perinatal mortality compared with high-risk women.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".