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