Outcome of Vaginal Birth After Cesarean Section (VBAC)
Bibliographic record
Abstract
Background: Generally, it is agreed that all women who previously had a cesarean section should be attempted for normal vaginal delivery. Of course, post-cesarean normal vaginal delivery is associated with potential risks and is sometimes clinically indicative of recurrent cesarean section. Objectives: This study aimed to evaluate the success and complications of vaginal birth after a cesarean section in pregnant women referred to Ali Ibn Abi Talib Hospital in Zahedan in 2016 - 17. Methods: The present descriptive-analytical study was carried out after the approval of the Student Ethics Committee by visiting the archive of Ali Ibn Abi Talib Hospital in Zahedan to review the hospital records of women admitted to the gynecological ward for vaginal birth after a cesarean section. The researcher abstracted data into predetermined checklists. Finally, SPSS software was used for data analysis. Results: In this study, 176 patients were evaluated. The mean gestational age was 37.64 ± 3.13 weeks. The success rate of vaginal birth after one cesarean section was 92% (162 patients), and the failure rate was 8% (14 patients). Also, the complications of vaginal birth after cesarean section were transfusion (n = 4, 2.3%), cervical rupture (n = 3, 1.7%), neonatal death (n = 4, 1.7%), and uterine rupture (n = 1, 6%) (P = 0.0). Conclusions: In the present study, the success rate of vaginal birth after one cesarean section was 92% (162 patients), and the failure rate was 8% (14 patients). Complications included blood transfusion with 2.3%, cervical rupture with 1.7%, infant mortality with 1.7%, and uterine rupture with 0.6%.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".