Publication Description
OBJECTIVE: This study aimed to develop and validate a model to predict the probability of vaginal delivery (VD) in low-risk term nulliparous patients, and to determine whether it can predict the risk overe maternal and neonatal morbidity. METHODS: Secondary analysis of an obstetric cohort of patients and their neonates born in 25 hospitals across the United States (n = 115,502). Trained and certified research personnel abstracted the maternal and neonatal records. Nulliparous patients with singleton, nonanomalous vertex fetuses, admitted with an intent for VD >/= 37 weeks were included in this analysis. Patients in active labor (cervical exam > 5 cm), those with prior cesarean and other comorbidities were excluded. Eligible patients were randomly divided into a training and test sets. Based on the training set, and using factors available at the time of admission for delivery, we developed and validated a logistic regression model to predict the probability of VD, and then estimated the prevalences of severe morbidity according to the predicted probability of VD. RESULTS: A total of 19,611 patients were included. Based on the training set (n = 9,739), a logistic regression model was developed that included maternal age, body mass index (BMI), cervical dilatation, and gestational age on admission. The model was internally validated on the test set (n = 9,872 patients) and yielded a receiver operating characteristic-area under the curve (ROC-AUC) of 0.71 (95% confidence interval [CI]: 0.70-0.72). Based on a subset of 18,803 patients with calculated predicted probabilities, we demonstrated that the prevalences of severe morbidity decreased as the predicted probability of VD increased (p