Using objective patient characteristics, develop a prediction model for external cephalic version (ECV) success. This retrospective analysis included pregnant women over the age of 18 who had a non anomalous, singleton pregnancy and completed an ECV attempt at a single quaternary care hospital between 2006 and 2016. Maternal age, height, weight, body mass index (BMI), parity, foetal sex, gestational age, estimated foetal weight, type of foetal malpresentation, placental position, and amniotic fluid volume were all evaluated. To evaluate the relationship between patient characteristics and ECV success, univariable and multivariable logistic regression models were employed. Estimated odds ratios and 95 percent confidence intervals were generated for each variable, and backward elimination and bootstrapping were used to determine the most parsimonious model for ECV success with the greatest discriminatory ability. This model was assessed using a calibration curve over success deciles. A total of 1,138 people attempted ECV and were included in this study. The overall success rate of ECV was 40.6 percent. Maternal age, parity, placental position, estimated foetal weight, and type of foetal malpresentation were all linked with ECV success. The best calibration was achieved using a final model that included BMI, parity, placental location, and kind of foetal malpresentation.
A prediction model was developed and internally verified to assess the likelihood of ECV success. This model combines easily accessible and objective patient variables known prior to ECV and may be utilised in ECV decision making and patient counselling.
