Abstract

ObjectiveWe aimed to validate a widely used US prediction model for vaginal birth after cesarean (Grobman et al. [8]) and modify it to suit Swedish conditions. Study designWomen having experienced one cesarean section and at least one subsequent delivery (n=49,472) in the Swedish Medical Birth Registry 1992–2011 were randomly divided into two data sets. In the development data set, variables associated with successful trial of labor were identified using multiple logistic regression. The predictive ability of the estimates previously published by Grobman et al., and of our modified and new estimates, respectively, was then evaluated using the validation data set. The accuracy of the models for prediction of vaginal birth after cesarean was measured by area under the receiver operating characteristics curve. ResultsFor maternal age, body mass index, prior vaginal delivery, and prior labor arrest, the odds ratio estimates for vaginal birth after cesarean were similar to those previously published. The prediction accuracy increased when information on indication for the previous cesarean section was added (from area under the receiver operating characteristics curve=0.69–0.71), and increased further when maternal height and delivery unit cesarean section rates were included (area under the receiver operating characteristics curve=0.74). The correlation between the individual predicted vaginal birth after cesarean probability and the observed trial of labor success rate was high in all the respective predicted probability decentiles. ConclusionCustomization of prediction models for vaginal birth after cesarean is of considerable value. Choosing relevant indicators for a Swedish setting made it possible to achieve excellent prediction accuracy for success in trial of labor after cesarean. During the delicate process of counseling about preferred delivery mode after one cesarean section, considering the results of our study may facilitate the choice between a trial of labor or an elective repeat cesarean section.

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