Maternal and neonatal complications of trial of labor after two cesarean sections (TOLAC-2) compared with repeat cesarean section (RCS-2): Systematic review and meta-analysis
Bibliographic record
Abstract
Title: Maternal and neonatal complications of the trial of labour after two caesarean sections (PPDC-2) versus repeat caesarean section (CR-2): Systematic review and meta-analysis. Background: PPDC-2 is a behavior that is not accepted in all latitudes. Women who want natural childbirth do not receive the opportunity. The objective wasto conduct a systematic review and meta-analysis on the maternal and neonatal complications of PPDC-2 versus CR-2. Methods: The eligibility criteria were: pregnant women of ≥22 weeks, two cesarean sections, cephalic presentation, no contraindications to natural delivery, no fetal malformations who undergo PPDC-2. We searched the libraries PubMed, Scopus, Embase and other websites of organisations linked to Obstetrics and Gynaecology. We assessed risk of bias using the Newcastle-Ottawa Scale. The Synthetic Method was used to summarize and present the results. Results: The number of included articles that met the eligibility criteria was 10, with 3316 participants in the intervention group (PPDC-2) and 54054 in the control group (CR-2). The studies were cohort studies. The average success rate of PPDC-2 was 62.1%. There were no differences in maternal and neonatal complications in most publications. The rate of uterine rupture was very small. Discussion: The information comes from good quality cohort studies (level of evidence 2b). PPDC-2 is a reasonable and relatively safe option, comparable to CR-2. Others: It was financed with own resources, no protocol was carried out and it was not recorded on the basis of systematic reviews.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".