An Updated Systematic Review on Prediction Models for Successful External Cephalic Version
Authors: Palsgaard Peggy , Yerrabelli Rahul , Lee Claire , Lauinger Alexa , Abdelsalam Omer , Maurice Joseph , Jennings Valerie 
Published: July 2024

Purpose: Current practice guidelines recommend offering patients an external cephalic version (ECV) when a fetus is found to be in breech position. If successful, vaginal delivery can then safely follow an ECV. ECV for a term breech presentation varies widely in success but is a well-studied topic, with many variables identified which relate to its success. This has led to a multitude of predictor models for ECV success. A systematic review by Velzel et al. published in 2015 examined prior predictor models for ECV success; however, many models have since been published. We aim to update this systematic review with the new predictive models published in the last seven years and thus review the decision aids currently available or being developed to predict a patients’ odds that their external cephalic version (ECV) will be successful. Methods: We searched PubMed/MEDLINE, Cochrane Central, and ClinicalTrials.gov from 2015-2022. Articles from a pre-2015 systematic review were also included. A clinical librarian helped with conducting a thorough search strategy. We selected English-language articles describing or evaluating models (prediction rules) designed to predict an outcome of ECV for an individual patient. Acceptable model outcomes included cephalic presentation after the ECV attempt and whether the ECV ultimately resulted in a vaginal delivery. Two authors independently performed article selection following PRISMA 2020 guidelines. Since 2015, 380 unique records underwent title and abstract screening, and 49 reports underwent full-text review. Ultimately, 17 new articles and 8 from the prior review were included. Of the 25 articles, 22 proposed 1-2 models each for a total of 25 models, while the remaining 3 articles validated prior models without proposing new ones. The studies were then analyzed for quality and risk of bias using a customized framework which analyzed four main domains: participants, predictors, outcome, and analysis. Ultimately, the largest factor considered when assessing study quality was whether the outcome was likely to be different amongst groups within a similar population. We then assessed the model’s calibration and discrimination metrics (if reported) to evaluate their overall model performance. Results: Of the 17 new articles, 10 were low, 6 moderate, and 1 high risk of bias. Studies were considered to have moderate risk of bias and quality if model-building strategies were not described, as it introduces concerns regarding consistency in applying the models to a similar population. Almost all articles were from Europe (11/25) or Asia (10/25); only one study in the last 20 years was from the USA. Four of the 17 new articles had some form of overlap with articles from the prior systematic reviews. The remaining 13 new articles used datasets, proposed models, and were performed by researchers that were entirely distinct from the 8 original articles The most included characteristics were parity (19/25), placental location (12/25), and breech engagement or station (10/25). Although many studies included BMI (8/25), only a few indicated whether this was to be pregravid, peri-ECV, or peripartum BMI. Some metrics for model discrimination (e.g., sensitivity, AUC, accuracy, PPV) was displayed in 17 of the 25 models. The models found had diverse presentations including score charts, decision trees (flowcharts), and equations. The majority (13/25) had no form of validation and only 5/25 reached external validation. Only the Newman-Peacock model (USA, 1993) was repeatedly externally validated (Pakistan, 2012 and Portugal, 2018). Most models (14/25) were published in the last 5 years. In general, newer models were designed more robustly, used larger sample sizes, and were more mathematically rigorous. Thus, although they await further validation, there is great potential for these models to be more predictive than the Newman-Peacock model. Based on the findings in this review, the Newman-Peacock model to predict ECV success (odds of cephalic presentation after the ECV procedure) is currently the most clinically useful model. Even though it is the oldest model in the review, it includes three of the most widely included prediction features: parity, placental location, and station. Furthermore, it is the only model that has been externally validated in a significantly different population and by a different investigational team than what was used to create the model. Conclusion: Only the Newman-Peacock model is ready for regular clinical use in predicting ECV success. Many newer models are promising but require further validation.