To build a score to predict the risk of cesarean delivery after labor induction with cervical ripening, and to compare its predictive capacities with other already existing scores.
This study is a secondary analysis of data collected in the prospective multicenter observational French population-based cohort study Methods of Induction of Labor and Perinatal Outcomes, the primary objective of which was to obtain national data regarding labor induction practices in 94 maternity units. A total of 1,692 patients were randomly split into a derivation data set of 1,024 patients (60%) and an internal validation set of 668 patients (40%). Statistical analyses were performed using a Bayesian approach, allowing the use of priors (ie, previous results published in the literature). The final score is a simplified 50-point score. The score was validated using the internal validation set and an external data set of 4,242 patients from the National Institutes of Health's Consortium for Safe Labor database. We compared the area under the curve (AUC) of our score with two other scores: the modified Bishop score and the Levine score, which is a recently published risk calculator for cesarean delivery after labor induction with unfavorable cervix.
In the multivariate analysis, height, body mass index, gestational age, parity, dilation, effacement, fetal head station, medical indication, suspicion of macrosomia, premature rupture of membranes and concerning fetal status were found to be strongly associated with cesarean delivery. The AUC in the derivation set and internal validation set were 0.76 (0.73–0.79) and 0.74 (0.70–0.78), respectively. On the external validation set, the AUC for the present score, the Levine score, and the modified Bishop score were 0.81 (0.79–0.82), 0.76 (0.75–0.78), and 0.74 (0.73–0.76), respectively.
Our easy-to-use, externally validated score is efficient in predicting cesarean delivery after labor induction with cervical ripening.
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