Abstract
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. 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. 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. 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.
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