An Intrapartum Ultrasound-Based Predictive Model for Cesarean Section Conversion in Nulliparous Women Following Unsuccessful Vaginal Delivery Attempts

This study aimed to develop a predictive model for cesarean section conversion in nulliparous women using intrapartum ultrasound data. Low-risk nulliparous women carrying full-term singleton vertex fetuses were divided into derivation and validation cohorts. Ultrasound was used to measure the angle of progression and head-perineum distance for a cervical dilation of 4–6 cm. Regression analyses identified factors affecting failed vaginal delivery trials and subsequent cesarean section conversion, and a risk prediction model was constructed. Independent predictors of cesarean section conversion included oxytocin use for induction, fetal head circumference, estimated fetal weight, labor analgesia, and angle of progression when the active labor phase commenced. The nomogram showed good discrimination and calibration. The receiver operating characteristic curve area for the derivation and validation cohorts were 0.924 (95% confidence interval: 0.892–0.956) and 0.916 (95% confidence interval: 0.817–01.000), respectively, with sensitivities and specificities of 0.933 and 0.781 for the derivation cohort and 0.857 and 0.827 for the validation cohort. Concordance indexes for the derivation and validation cohorts were 0.92 and 0.91, respectively. The predictive model exhibited robust predictive capabilities and high precision. It can assist clinicians in the choice of the appropriate mode of delivery, thereby improving maternal and infant outcomes.