A Novel and Modern Calculator to Predict Vaginal Birth After Cesarean Delivery

Background: Counseling patients who are considering a trial of labor after cesarean (TOLAC) is a challenging task given the risks and benefits of either approach. While calculators exist to predict likelihood of having a successful vaginal birth after cesarean (VBAC), their validity is limited by outdated mathematical methods used to develop them. Importantly, current VBAC calculators only offer insight into the chance of successful VBAC, without any ability to predict the risk of adverse outcomes Objective: To develop a modernized tool for individualized risks and benefits of TOLAC. Study Design: This was a secondary analysis of the Cesarean Registry database. The primary outcome was the prediction of successful VBAC. Secondary outcomes were the prediction of maternal complications and neonatal complications. Inclusion criteria were term, singleton gestation, cephalic presentation pregnancies with one prior low transverse cesarean delivery. Univariate comparisons identified variables that were independently associated with VBAC. An optimal decision tree was used to create a prediction model. A calculator tool was developed for prediction of VBAC and adverse outcomes including uterine dehiscence, hysterectomy, postpartum hemorrhage, neonatal hypoxic ischemic encephalopathy, respiratory distress, and death, among others. Results: The population included 73,262 deliveries of which 12,942 met inclusion criteria. After removing the test set, the included patients were 8,078 of which 5,970 had a successful VBAC (73.9%). Parity, years since prior cesarean delivery, pre-pregnancy body mass index (BMI), delivery BMI, maternal age, previous VBAC were associated with successful VBAC. A calculator was created and a receiver operator characteristic curve was developed with an AUC of 0.72. Conclusion: VBAC was associated with several variables. This calculator facilitates shared decision making about the value of a TOLAC, and by using more advanced mathematical models, allows providers to predict likelihood of successful VBAC and risk of adverse outcomes

Publication History

Received: 20 February 2025

Accepted after revision: 11 May 2025

Accepted Manuscript online:
12 May 2025