Department of Obstetrics and Gynecology, Academic Medical Centre, University of Amsterdam, The Netherlands.
Am J Perinatol. 2011 Feb;28(2):103-10. doi: 10.1055/s-0030-1262909. Epub 2010 Jul 26.
We aimed to develop a predictive model for the chance of a successful external cephalic version (ECV). We performed a prospective cohort study of women with a singleton fetus in breech presentation with a gestational age of 36 weeks or more. Data on parity, maternal age, body mass index, ethnicity, gestational age, placental location, fetal position, estimated fetal weight, and amniotic fluid were recorded in all participants. Multivariable logistic regression analysis with a stepwise backward selection procedure was used to construct a prediction model for the occurrence of successful ECV. We included a total of 310 women. Multivariable logistic regression analysis demonstrated that multiparity, increasing estimated fetal weight, and normal amniotic fluid were favorable predictors of successful ECV. Anterior placenta location was an unfavorable predictor for ECV outcome. Discrimination of the model was fair (area under the curve 0.71), and the calibration of the model was acceptable. Our prediction model appears to discriminate between women with a poor chance of successful ECV (less than 20%) and women with a good chance of success (more than 60%). When this model is validated externally, it could be used for patient counseling and clinical decision making.
我们旨在开发一种预测成功外部翻转术(ECV)机会的模型。我们对胎龄 36 周或以上臀位的单胎妊娠女性进行了前瞻性队列研究。所有参与者均记录了产次、母亲年龄、体重指数、种族、胎龄、胎盘位置、胎儿位置、估计胎儿体重和羊水等数据。采用逐步向后选择程序的多变量逻辑回归分析来构建成功 ECV 发生的预测模型。我们共纳入了 310 名女性。多变量逻辑回归分析表明,多产、估计胎儿体重增加和正常羊水是 ECV 成功的有利预测因素。前胎盘位置是 ECV 结局的不利预测因素。该模型的区分度为中等(曲线下面积为 0.71),校准度可接受。我们的预测模型似乎可以区分 ECV 成功率较低(小于 20%)和成功率较高(大于 60%)的女性。当该模型在外部得到验证时,可用于患者咨询和临床决策。