Validation of a Prediction Model for Predicting the Probability of Morbidity Related to a Trial of Labour in Quebec

Background: Pregnant women with a history of previous Caesarean section face the decision either to undergo an elective repeat Caesarean section (ERCS) or to attempt a trial of labour with the goal of achieving a vaginal birth after Caesarean (VBAC). Both choices are associated with their own risks of maternal and neonatal morbidity. We aimed to determine the external validity of a prediction model for the success of trial of labour after Caesarean section (TOLAC) that could help these women in their decision-making. Methods: We used a perinatal database including 185 437 deliveries from 32 obstetrical centres in Quebec between 2007 and 2011 and selected women with one previous Caesarean section who were eligible for a TOLAC. We compared the frequency of maternal and neonatal morbidity between women who underwent TOLAC and those who underwent an ERCS according to the probability of success of TOLAC calculated from a published model of prediction. Results: Of 8508 eligible women, including 3113 who underwent TOLAC, both maternal and neonatal morbidities became less frequent as the predicted chance of VBAC increased (P < 0.05). Women undergoing a TOLAC were more likely to have maternal morbidity than those who underwent an ERCS when the predicted probability of VBAC was less than 60% (relative risk [RR] 2.3; 95% CI 1.4 to 4.0); conversely, maternal morbidity was not different between the two groups when the predicted probability of VBAC was at least 60% (RR 0.8; 95% CI 0.6 to 1.1). Neonatal morbidity was similar between groups when the probability of VBAC success was 70% or greater (RR 1.2; 95% CI 0.9 to 1.5). Conclusion: The use of a prediction model for TOLAC success could be useful in the prediction of TOLAC success and perinatal morbidity in a Canadian population. Neither maternal nor neonatal morbidity are increased with a TOLAC when the probability of VBAC success is at least 70%.