Prediction Models for Successful External Cephalic Version: An Updated Systematic Review.

Area of Science:

• Obstetrics and Gynecology
• Medical Decision Making
• Clinical Prediction Models

Background:

• External cephalic version (ECV) is a procedure to turn a breech baby to a head-down position before birth.
• Predicting the success of ECV is crucial for optimizing patient care and outcomes.
• Existing decision aids for ECV success prediction require systematic review and evaluation.

Purpose of the Study:

• To conduct a comprehensive review of available and developing decision aids for predicting external cephalic version (ECV) success.
• To identify and evaluate prediction models designed for individual ECV success outcomes.
• To assess the validation status and clinical readiness of identified ECV prediction models.

Main Methods:

• Systematic literature search of PubMed/MEDLINE, Cochrane Central, and ClinicalTrials.gov (2015-2022), including a prior review.
• Selection of English-language articles describing or evaluating prediction models for ECV outcomes (cephalic presentation, vaginal delivery).
• Independent article selection by two authors following PRISMA 2020 guidelines; assessment of model validation and risk of bias.

Main Results:

• 25 ECV prediction models were identified, with 14 published in the last 5 years.
• The Newman-Peacock model is the only model with repeated external validation and readiness for clinical use.
• Newer models demonstrate more robust design and potential for improved prediction but require further external validation.

Conclusions:

• The Newman-Peacock model remains the sole prediction tool validated for routine clinical application in ECV.
• Emerging ECV prediction models show promise due to improved methodologies and larger datasets.
• Further rigorous external validation is essential for newer models to establish their clinical utility and predictive accuracy.