The Development of a Prediction Model for Vaginal Birth After Cesarean Section (VBAC) [34P

Abstract

INTRODUCTION: Pregnant women who have had a previous cesarean section face the decision to either undergo a repeat elective cesarean or to attempt vaginal birth after cesarean (VBAC). The goal of this project was to determine the factors that predict success of VBAC in women with one prior cesarean section in the population of British Columbia, Canada. METHODS: Data were drawn from the British Columbia Perinatal Data Registry. We performed a retrospective analysis of 8291 cephalic term singleton planned vaginal births in British Columbia to women with a previous cesarean. Using block multivariate logistic regression, we analyzed the variables, both modifiable and non-modifiable, most predictive of successful VBAC. A result was considered statistically significant if its p value was <.05. RESULTS: Of the 8291 planned VBAC births, 5960 were successful, while 2331 resulted in cesarean deliveries. Predictive variables were: maternal age, height and BMI, whether or not she had a vaginal birth within 2 years of the planned VBAC, whether she had a recurrent indication for the prior cesarean, whether she was administered oxytocin or prostaglandins for labor augmentation or induction, whether she was given an epidural, and the size of hospital in which she gave birth. CONCLUSION: A prediction model, incorporating eight variables has been developed. This model can inform shared decision-making and guide individualized counselling for eligible women on the chance of VBAC success. We hope that this prediction model will contribute to the literature and ultimately lower the probability of complications and adverse outcomes in childbirth.