Cervical Ripening With Transcervical Foley Catheter and the Risk of Uterine Rupture
Bibliographic record
Abstract
OBJECTIVE: To estimate whether the rate of uterine rupture in patients with a previous cesarean delivery is related to labor induction and/or cervical ripening using transcervical Foley catheter. METHODS: Charts of all patients who had a trial of labor after a previous cesarean delivery in our institution between 1988 and 2002 were reviewed. The rates of successful vaginal birth after cesarean delivery and uterine rupture in patients with spontaneous labor (control group) were compared with those of patients who underwent a labor induction by means of amniotomy with or without oxytocin and patients who underwent a labor induction/cervical ripening using a transcervical Foley catheter. Logistic regression analysis was performed to adjust for confounding variables. RESULTS: Of 2479 patients, 1807 had a spontaneous labor, 417 had labor induced by amniotomy with or without oxytocin, and 255 had labor induced by using transcervical Foley catheter. The rate of successful vaginal birth after cesarean delivery was significantly different among the groups (78.0% versus 77.9% versus 55.7%, P <.001), but not the rate of uterine rupture (1.1% versus 1.2% versus 1.6%, P =.81). After adjusting for confounding variables, the odds ratio (OR) for successful vaginal birth after cesarean delivery was 0.68 (95% confidence interval [CI] 0.41, 1.15), and the OR for uterine rupture was 0.47 (95% CI 0.06, 3.59) in patients who underwent an induction of labor using a transcervical Foley catheter when compared with patients with spontaneous labor. CONCLUSION: Labor induction using a transcervical Foley catheter was not associated with an increased risk of uterine rupture.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".