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Development and internal validation of a clinical prediction model for external cephalic version. | LitMetric

AI Article Synopsis

Article Abstract

Objective: To develop a prediction model for the chance of successful external cephalic version (ECV).

Study Design: This is a secondary analysis of a multicenter, open-label randomized controlled trial that assessed the effectiveness of atosiban compared to fenoterol as uterine relaxant during ECV in women with a singleton fetus in breech presentation with a gestational age of 36 weeks or more. Potential predictors included maternal, pregnancy, fetal, and treatment characteristics and were recorded in all participants. Multivariable logistic regression analysis with a stepwise backward selection procedure was used to construct a prediction model for the occurrence of successful ECV. Model performance was assessed using calibration and discrimination.

Results: We included a total of 818 women with an overall ECV success rate of 37%. Ten predictive factors were identified with the stepwise selection procedure to be associated with a successful ECV: fenoterol as uterine relaxant, nulliparity, Caucasian ethnicity, gestational age at ECV, Amniotic Fluid Index, type of breech presentation, placental location, breech engagement, possibility to palpate the head and relaxation of the uterus. Our model showed good calibration and a good discriminative ability with a c-statistic of 0.78 (95% CI 0.75 to 0.81).

Conclusion: Prediction of success of ECV seems feasible with a model showing good performance. This can be used in clinical practice after external validation.

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Source
http://dx.doi.org/10.1016/j.ejogrb.2018.06.019DOI Listing

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