Unintended lower‐segment hysterotomy extension at cesarean delivery and the risk for uterine rupture during a subsequent trial of labor
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between unintended uterine extension in cesarean delivery and uterine scar disruption (rupture or dehiscence) at the subsequent trial of labor after cesarean delivery (TOLAC). METHODS: This is a multicenter retrospective cohort study (2005-2021). Parturients with a singleton pregnancy who had unintended lower-segment uterine extension during the primary cesarean delivery (excluding T and J vertical extensions) were compared with patients who did not have an unintended uterine extension. We assessed the subsequent uterine scar disruption rate following the subsequent TOLAC and the rate of adverse maternal outcome. RESULTS: During the study period, 7199 patients underwent a trial of labor and were eligible for the study, of whom 1245 (17.3%) had a previous unintended uterine extension and 5954 (82.7%) did not. In univariate analysis, previous unintended uterine extension during the primary cesarean delivery was not significantly associated with uterine scar rupture in the following subsequent TOLAC. Nevertheless, it was associated with uterine scar dehiscence, higher rates of TOLAC failure, and a composite adverse maternal outcome. In multivariate analyses, only the association between previous unintended uterine extension and higher rates of TOLAC failure was confirmed. CONCLUSION: A history of unintended lower-segment uterine extension is not associated with an increased risk for uterine scar disruption following subsequent TOLAC.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".