Abstract
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