Césarienne après déclenchement du travail : facteurs de risque et score de prédiction

Abstract

ObjectivesThe objective of the study is to determine the risk factors for caesarean section at the time of labor induction, to establish a prediction algorithm, to evaluate its relevance and to compare the results with observation. MethodsA retrospective study was carried out over a year at Nantes University Hospital with 941 cervical ripening and labor inductions (24.1%) terminated by 167 caesarean sections (17.8%). Within the cohort, a case-control study was conducted with 147 caesarean sections and 148 vaginal deliveries. A multivariate analysis was carried out with a logistic regression allowing the elaboration of an equation of prediction and an ROC curve and the confrontation between the prediction and the reality. ResultsIn univariate analysis, six variables were significant: nulliparity, small size of the mother, history of scarried uterus, use of prostaglandins as a mode of induction, unfavorable Bishop score<6, variety of posterior release. In multivariate analysis, five variables were significant: nulliparity, maternal size, maternal BMI, scar uterus and Bishop score. The most predictive model corresponded to an area under the curve of 0.86 (0.82–0.90) with a correct prediction percentage (“well classified”) of 67.6% for a caesarean section risk of 80%. ConclusionThe prediction criteria would make it possible to inform the woman and the couple about the potential risk of Caesarean section in urgency or to favor a planned Caesarean section or a low-lying attempt on more objective, repeatable and transposable arguments in a medical team.