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

Area of Science:

• Obstetrics and Gynecology
• Maternal-Fetal Medicine
• Clinical Prediction Modeling

Background:

• External cephalic version (ECV) is a procedure to turn a fetus from breech to cephalic presentation.
• Predicting ECV success is crucial for optimizing obstetric interventions and outcomes.
• Existing prediction models for ECV success require further development and validation.

Purpose of the Study:

• To develop and validate a predictive model for successful external cephalic version (ECV).
• To identify key maternal, fetal, and procedural factors associated with ECV success.
• To enhance clinical decision-making regarding ECV in singleton breech presentations.

Main Methods:

• Secondary analysis of a multicenter randomized controlled trial involving 818 women.
• Multivariable logistic regression with stepwise backward selection to identify predictors.
• Assessment of model performance using calibration and discrimination (c-statistic).

Main Results:

• The overall ECV success rate was 37%.
• Ten factors significantly predicted ECV success, including fenoterol use, nulliparity, Caucasian ethnicity, gestational age, Amniotic Fluid Index, breech presentation type, placental location, breech engagement, head palpability, and uterine relaxation.
• The developed model demonstrated good calibration and discrimination, with a c-statistic of 0.78.

Conclusions:

• A robust prediction model for ECV success has been developed.
• The model exhibits good performance and can potentially aid clinical practice.
• External validation is recommended before widespread clinical implementation.