Prediction of cesarean delivery after induction of labor in twin pregnant women: a retrospective cohort study

Objective: The purpose of this study was to develop a predictive model for cesarean delivery after induction of labor (IOL) in twin pregnancy. Design: Retrospective cohort study Setting: University hospital. Population: Twin pregnancy who underwent IOL from 2005 to 2018 Methods: The study population was randomly divided into the training and test sets at a ratio of 2:1. Three-fold cross-validation (CV) with 100 times repetitions was applied to select the best model. Main outcome measure to develop and validate a prediction model for cesarean delivery after IOL in twin pregnancies. Results: A total of 1,703 twin pregnancies were analyzed, including 1,356 women in the development cohort of the SNUH database and 347 women in the external validation cohort of the SNUBH database. In the development cohort, the clinical variables that were different between the successful and failed IOL groups were included in the logistic regression analysis, and the final prediction model, composed of five variables (maternal age, maternal height, parity, cervical effacement, and summated birth weight of both twins), was selected with an AUROC of 0.742 (95% confidence interval [CI], 0.700-0.785) and 0.733 (95% CI, 0.671-0.794) in the training set and test set, respectively. A nomogram for predicting the risk of cesarean delivery after IOL in twin pregnancies was also developed. Conclusion: A prediction model to provide information and evaluate the risk of cesarean delivery after IOL in twin pregnancies was developed. Keywords Twin pregnancy, induction of labor, cesarean section, prediction model