Department of Obstetrics and Gynaecology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, the Netherlands.
BJOG. 2014 Jan;121(2):194-201; discussion 201. doi: 10.1111/1471-0528.12539.
To develop and internally validate a model that predicts the outcome of an intended vaginal birth after caesarean (VBAC) for a Western European population that can be used to personalise counselling for deliveries at term.
Registration-based retrospective cohort study.
Five university teaching hospitals, seven non-university teaching hospitals, and five non-university non-teaching hospitals in the Netherlands.
A cohort of 515 women with a history of one caesarean section and a viable singleton pregnancy, without a contraindication for intended VBAC, who delivered at term.
Potential predictors for a vaginal delivery after caesarean section were chosen based on literature and expert opinions. We internally validated the prediction model using bootstrapping techniques.
Predictors for VBAC. For model validation, the area under the receiver operating characteristic curve (AUC) for discriminative capacity and calibration-per-risk-quantile for accuracy were calculated.
A total of 371 out of 515 women had a VBAC (72%). Variables included in the model were: estimated fetal weight greater than the 90(th) percentile in the third trimester; previous non-progressive labour; previous vaginal delivery; induction of labour; pre-pregnancy body mass index; and ethnicity. The AUC was 71% (95% confidence interval, 95% CI = 69-73%), indicating a good discriminative ability. The calibration plot shows that the predicted probabilities are well calibrated, especially from 65% up, which accounts for 77% of the total study population.
We developed an appropriate Western European population-based prediction model that is aimed to personalise counselling for term deliveries.
为西欧人群开发并内部验证一种预测剖宫产术后阴道分娩结局的模型，该模型可用于为足月分娩提供个性化咨询。
基于注册的回顾性队列研究。
荷兰五所大学附属医院、七所非大学附属医院和五所非大学非教学医院。
一组 515 名有一次剖宫产史和单活胎且无阴道分娩禁忌证的妇女，在足月时分娩。
根据文献和专家意见选择剖宫产术后阴道分娩的潜在预测因素。我们使用自举技术对内部分类准确性和校准风险定量进行了验证。
剖宫产术后阴道分娩的预测因素。为了验证模型，计算了接收者操作特征曲线（ROC）下面积（AUC）的判别能力和校准风险定量的准确性。
515 名妇女中有 371 名（72%）进行了 VBAC。纳入模型的变量包括：孕晚期估计胎儿体重大于第 90 百分位；前次非进展性产程；前次阴道分娩；引产；孕前体质量指数；和种族。AUC 为 71%（95%置信区间，95%CI=69-73%），表明具有良好的判别能力。校准图显示预测概率校准良好，尤其是从 65%开始，占总研究人群的 77%。
我们开发了一种适用于西欧人群的预测模型，旨在为足月分娩提供个性化咨询。
