Oxytocin Use in Trial of Labor after Cesarean and Its Relationship with Risk of Uterine Rupture in Women with One Previous Cesarean Section: A Meta-analysis of Observational Studies.
Bibliographic record
Abstract
Abstract Background Trial of labor after a previous cesarean delivery (TOLAC) has helped to reduce the rate of cesarean section (CS). But the increased rate of adverse outcomes limites the spread of TOLAC. The most serious one is the risk of symptomatic uterine rupture, which is possibly associated with oxytocin. This meta-analysis was to evaluate the risk association between oxytocin use and uterine rupture in TOLAC. Methods Multiple electronic databases (PubMed, Embase, Web of Science, and Google Scholar) were searched for case-control or cross-sectional studies about TOLAC, oxytocin and uterine rupture, which were published between January 1986 and October 2019. The bias-corrected Hedge's g was calculated as the effect size using the random-effects model. The risk of bias was evaluated by the Newcastle-Ottawa Scale (NOS). Quality of the evidence was assessed with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) certainty ratings system. Results There were 14 studies meeting inclusion criteria including 48457 women undergoing TOLAC. The pooled rate of VBAC and rate of uterine rupture in spontaneous labor were 74.3% and 0.7%. And the pooled rate of VBAC and rate of uterine rupture in induction labor were 60.7% and 2.2%. The women with spontaneous labor had significantly higher rate of VBAC (p=0.0032) and lower rate of uterine rupture (p=0.0003) than that with induction labor. The pooled rates of uterine rupture in women using oxytocin and women not using oxytocin in TOLAC were 1.4% and 0.5%. There was significant difference between these two groups (p=0.0002). Conclusions In TOLAC, women with induction labor had higher risk of uterine rupture than that with spontaneous labor. Oxytocin use may increase the risk. So simplified and standardized intrapartum management, precise procotol and cautiously monitoring of oxytocin in TOLAC are necessary.
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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 | 0.020 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.048 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".