Predictive Model for Cesarean Delivery in Term Nulliparous Women Undergoing Induction of Labor with Slow-Release Dinoprostone

Background Cesarean delivery after labor induction is a significant clinical concern, especially in nulliparous women with an unfavorable cervix. Early identification of patients at increased risk for cesarean section may support individualized obstetric care strategies. This study aimed to develop a predictive model for cesarean delivery among nulliparous women undergoing induction of labor with an unfavorable cervix. Methods This retrospective cohort study included 532 nulliparous women with unfavorable cervices who underwent labor induction using a slow-release dinoprostone vaginal insert at a tertiary care center between October 2023 and January 2025. A penalized logistic regression model (PMLE) was used to identify independent predictors of cesarean delivery. Internal validation was performed using 1,000 bootstrap resamples, and a nomogram was constructed based on significant variables. Results The overall cesarean delivery rate was 38.0%. Multivariable analysis identified higher body mass index (BMI) (aOR: 1.095, 95% CI: 1.041–1.151; p < 0.001) and lower Bishop score (aOR: 0.828, 95% CI: 0.723–0.976; p = 0.026) as independent predictors of cesarean delivery. A nomogram was developed to estimate individualized cesarean risk, and decision curve analysis demonstrated potential clinical utility, particularly within the 15–60% risk threshold range. Conclusion This study presents a predictive nomogram to estimate cesarean delivery risk in nulliparous women undergoing labor induction with an unfavorable cervix. While further prospective validation is warranted, the model incorporating BMI and Bishop score may serve as a useful tool for future research on personalized induction strategies.