Abstract
Objective: The purpose of this study was to develop a model that predicts individual-specific risk of uterine rupture during an attempted vaginal birth after cesarean delivery. Study Design: Women with 1 previous low-transverse cesarean delivery who underwent a trial of labor with a term singleton were identified in a concurrently collected database of deliveries that occurred at 19 academic centers during a 4-year period. We analyzed different classification techniques in an effort to develop an accurate prediction model for uterine rupture. Results: Of the 11,855 women who were available for analysis, 83 women (0.7%) had had a uterine rupture. The optimal final prediction model, which was based on a logistic regression, included 2 variables: any previous vaginal delivery (odds ratio, 0.44; 95% CI, 0.27-0.71) and induction of labor (odds ratio, 1.73; 95% CI, 1.11-2.69). This model, with a c-statistic of 0.627, had poor discriminating ability and did not allow the determination of a clinically useful estimate of the probability of uterine rupture for an individual patient. Conclusion: Factors that were available before or at admission for delivery cannot be used to predict accurately the relatively small proportion of women at term who will experience a uterine rupture during an attempted vaginal birth after cesarean delivery.
Original language | English (US) |
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Pages (from-to) | 30.e1-30.e5 |
Journal | American journal of obstetrics and gynecology |
Volume | 199 |
Issue number | 1 |
DOIs | |
State | Published - Jul 2008 |
Keywords
- prediction
- uterine rupture
- vaginal birth after cesarean delivery
ASJC Scopus subject areas
- Obstetrics and Gynecology