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.