Erratum: Predictive Factors for Successful Vaginal Delivery after a Trial of External Cephalic Version: A Retrospective Cohort Study of 946 Women

Bilgory, Asaf; Minich, Olena; Shvaikovsky, Maria; Gurevich, Genady; Lessing, Joseph B.; Olteanu, Ioana

doi:10.1055/s-0041-1742110

“…The remaining 11 articles were completely independent from each other; two of these articles proposed two models each 36,37 , while the remaining 9 proposed a single model each [38][39][40][41][42][43][44][45][46] (Figure 2). Two of the articles had an erratum: one was trivial 40,47 and only modi ed a sentence in the abstract, while the other was a correction of a gure describing the decision tree model 41,48 . See Appendix 4 for notes on how distinct models were counted in certain circumstances.…”

Section: Relationships Between Articlesmentioning

confidence: 99%

“…Of these articles, two were from the same team of authors and used the same dataset; Anand 2019 used the dataset to create a model predicting cephalic position after the ECV, while the Palepu 2021 created a model to predict vaginal delivery 30,31 The remaining 11 articles were completely independent from each other; two of these articles proposed two models each 32,33 , while the remaining 9 proposed a single model each [34][35][36][37][38][39][40][41][42] (Figure 2). Two of the articles had an erratum: one was trivial 36,43 and only modi ed a sentence in the abstract, while the other was a correction of a gure describing the decision tree model 37,44 . See Appendix 4 for notes on how distinct models were counted in certain circumstances.…”

Section: Relationships Between Articlesmentioning

confidence: 99%

“…The results of the study quality assessment based on the signaling questions are shown in Table 4. Out of 17 new articles, 10 studies were identi ed as having low overall risk of bias and high study quality 22,[29][30][31][32]35,37,[40][41][42] , 6 studies were identi ed as having moderate bias and moderate study quality 25,33,34,38,39,43 , and 1 was considered to have high bias and low quality 26 . This is in addition to Velzel et al's assessment of the 8 prior articles of which 4 were low risk of bias and high study quality and 4 were moderate risk of bias and study quality 10 .…”

Section: Quality and Biasmentioning

confidence: 99%

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

Yerrabelli

¹

,

Lee

²

,

Palsgaard

³

et al. 2023

Preprint

0

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PURPOSE: To review the decision aids currently available or being developed to predict a patient’s 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. 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. RESULTS: Of the 17 new articles, 10 were low, 6 moderate, and 1 high risk of bias. Almost all articles were from Europe (11/25) or Asia (10/25); only one study in the last 20 years was from the USA. 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. CONCLUSION: Only the Newman-Peacock model is ready for regular clinical use. Many newer models are promising but require further validation.

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“…The remaining 11 articles were completely independent from each other; two of these articles proposed two models each 36,37 , while the remaining 9 proposed a single model each [38][39][40][41][42][43][44][45][46] (Figure 2). Two of the articles had an erratum: one was trivial 40,47 and only modified a sentence in the abstract, while the other was a correction of a figure describing the decision tree model 41,48 .…”

Section: Relationships Between Articlesmentioning

confidence: 99%

“…The results of the study quality assessment based on the signaling questions are shown in Table 4. Out of 17 new articles, 10 studies were identified as having low overall risk of bias and high study quality 22,[33][34][35][36]39,41,[44][45][46] , 6 studies were identified as having moderate bias and moderate study quality 29,37,38,42,43,47 , and 1 was considered to have high bias and low quality 30 . This is in addition to Velzel et al's assessment of the 8 prior articles of which 4 were low risk of bias and high study quality and 4 were moderate risk of bias and study quality 10 .…”

Section: Quality and Biasmentioning

confidence: 99%

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

Yerrabelli,

Lee,

Palsgaard

et al. 2023

Am J Perinatol

2

0

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PURPOSE: To review the decision aids currently available or being developed to predict a patient’s 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. 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. RESULTS: Of the 17 new articles, 10 were low, 6 moderate, and 1 high risk of bias. Almost all articles were from Europe (11/25) or Asia (10/25); only one study in the last 20 years was from the USA. 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. CONCLUSION: Only the Newman-Peacock model is ready for regular clinical use. Many newer models are promising but require further validation.

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The Optimal Prediction Model for Successful External Cephalic Version

Yerrabelli,

Palsgaard,

Shankarappa

et al. 2024

Am J Perinatol

0

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OBJECTIVE: The majority of breech fetuses are delivered by Cesarean birth as few physicians are trained in vaginal breech birth. An external cephalic version (ECV) can prevent Cesarean delivery and the associated morbidity in these patients. Current guidelines recommend all patients with breech presentation be offered an ECV attempt. Not all attempts are successful, and an attempt does carry some risks so shared decision-making is necessary. To aid in patient counseling, over a dozen prediction models to predict ECV success have been proposed in the last few years. However, very few models have been externally validated, and thus none have been adopted into clinical practice. This study aims to use data from a United States hospital to provide further data on ECV prediction models. STUDY DESIGN: This study retrospectively gathered data from Carle Foundation Hospital and used it to test six models previously proposed to predict ECV success. These models were Dahl 2021, Bilgory 2023, López Pérez 2020, Kok 2011, Burgos 2010, and Tasnim 2012 (GNK-PIMS score). RESULTS: 125 patients undergoing 132 ECV attempts were included. 69 attempts were successful (52.2%). Dahl 2021 had the greatest predictive value (AUC 0.779), while Tasnim 2012 performed the worst (AUC 0.626). The remaining models had similar predictive values as each other (AUC 0.68-0.71). Bootstrapping confirmed that all models except Tasnim 2012 had confidence intervals not including 0.5. The bootstrapped 95% AUC confidence interval for Dahl 2021 was 0.71-0.84. In terms of calibration, Dahl 2021 was well calibrated with predicted probabilities matching observed probabilities. Bilgory 2023 and López Pérez were poorly calibrated. CONCLUSION: Multiple prediction tools have now been externally validated for ECV success. Dahl 2021 is the most promising prediction tool.

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Erratum: Predictive Factors for Successful Vaginal Delivery after a Trial of External Cephalic Version: A Retrospective Cohort Study of 946 Women

Abstract: The corrected Objective section should read as: Objective Our aim was to find the factors which predict a vertex presentation vaginal delivery (VD) in women who are admitted for a trial of external cephalic version (ECV).

Cited by 5 publications

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

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

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

The Optimal Prediction Model for Successful External Cephalic Version

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