Warwick Medical School, University of Warwick, and the University Hospitals Coventry and Warwickshire, Coventry, and the Reproductive Medicine Unit, University College London Hospitals, London, United Kingdom.
Obstet Gynecol. 2022 Nov 1;140(5):821-841. doi: 10.1097/AOG.0000000000004940. Epub 2022 Oct 5.
To systematically review all studies that developed or validated a vaginal birth after cesarean (VBAC) prediction model.
MEDLINE, EMBASE, CINAHL, Cochrane Library, and ClinicalTrials.gov were searched from inception until February 2022.
We included observational studies that developed or validated a multivariable VBAC prediction model in women with a singleton pregnancy and one previous lower segment cesarean delivery. A total of 3,758 articles were identified and screened.
TABULATION, INTEGRATION, AND RESULTS: For 57 included studies, data were extracted in duplicate using a CHARMS (Critical Appraisal and Data Extraction for Systematic Review of Prediction Modelling Studies) checklist-based tool and included participants' characteristics, sample size, predictors, timing of application, and performance. PROBAST (Prediction model Risk of Bias Assessment Tool) and TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis) were used to assess risk of bias and transparency of reporting. Several studies developed or validated more than one model. There were 38 unique prediction models, 42 external validations of 10 existing prediction models, and six modifications of existing models. Of the 38 unique models, only 19 (19/38, 50%) were internally validated in the initial study. No studies externally validated their model in the initial study. Age, previous vaginal birth, and previous cesarean delivery for labor dystocia were the commonest predictors. The area under the curve in included studies ranged from 0.61 to 0.95. Models used close to delivery generally outperformed those used earlier in pregnancy. Most studies demonstrated a high risk of bias (45/57, 79%), the remainder were unclear (7/57, 12%) and low (5/57, 9%). Median TRIPOD checklist adherence was 70% (range 32-93%).
Several prediction models for VBAC success exist, but many lack external validation and are at high risk of bias. Models used close to delivery outperformed those used earlier in pregnancy; however, their generalizability and applicability remain unclear. High-quality external validation and effect studies are required to guide clinical use.
PROSPERO, CRD42020190930.
系统回顾所有开发或验证阴道分娩后剖宫产（VBAC）预测模型的研究。
从建库至 2022 年 2 月，检索 MEDLINE、EMBASE、CINAHL、Cochrane 图书馆和 ClinicalTrials.gov 数据库。
纳入针对单胎妊娠和一次既往子宫下段剖宫产的女性，开发或验证多变量 VBAC 预测模型的观察性研究。共识别并筛选了 3758 篇文章。
列表、整合和结果：对于 57 项纳入的研究，使用基于 CHARMS（系统评价中预测模型研究的关键评估和数据提取）清单工具的重复数据提取，包括参与者特征、样本量、预测指标、应用时机和性能。使用 PROBAST（预测模型风险偏倚评估工具）和 TRIPOD（个体预后或诊断的多变量预测模型的透明报告）评估风险偏倚和报告的透明度。有几项研究开发或验证了不止一个模型。共有 38 个独特的预测模型、42 个 10 个现有预测模型的外部验证和 6 个现有模型的修改。在 38 个独特模型中，只有 19 个（19/38，50%）在初始研究中进行了内部验证。没有研究在初始研究中对其模型进行外部验证。年龄、既往阴道分娩和既往因产程延长而行剖宫产术是最常见的预测指标。纳入研究的曲线下面积范围为 0.61 至 0.95。接近分娩时使用的模型通常优于妊娠早期使用的模型。大多数研究显示出高风险偏倚（45/57，79%），其余研究为不明确（7/57，12%）和低（5/57，9%）。中位数 TRIPOD 清单遵守率为 70%（范围 32-93%）。
存在几种 VBAC 成功的预测模型，但许多模型缺乏外部验证，且存在高风险偏倚。接近分娩时使用的模型优于妊娠早期使用的模型；然而，它们的普遍性和适用性仍不清楚。需要高质量的外部验证和效果研究来指导临床应用。
PROSPERO，CRD42020190930。
