Department of Obstetrics and Gynaecology, Academic Medical Center, Amsterdam, The Netherlands.
Stanford Prevention Research Center, Stanford University, Stanford, CA, USA; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Eur J Obstet Gynecol Reprod Biol. 2018 Sep;228:137-142. doi: 10.1016/j.ejogrb.2018.06.019. Epub 2018 Jun 18.
To develop a prediction model for the chance of successful external cephalic version (ECV).
This is a secondary analysis of a multicenter, open-label randomized controlled trial that assessed the effectiveness of atosiban compared to fenoterol as uterine relaxant during ECV in women with a singleton fetus in breech presentation with a gestational age of 36 weeks or more. Potential predictors included maternal, pregnancy, fetal, and treatment characteristics and 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. Model performance was assessed using calibration and discrimination.
We included a total of 818 women with an overall ECV success rate of 37%. Ten predictive factors were identified with the stepwise selection procedure to be associated with a successful ECV: fenoterol as uterine relaxant, nulliparity, Caucasian ethnicity, gestational age at ECV, Amniotic Fluid Index, type of breech presentation, placental location, breech engagement, possibility to palpate the head and relaxation of the uterus. Our model showed good calibration and a good discriminative ability with a c-statistic of 0.78 (95% CI 0.75 to 0.81).
Prediction of success of ECV seems feasible with a model showing good performance. This can be used in clinical practice after external validation.
建立预测外倒转术（ECV）成功机会的模型。
这是一项多中心、开放标签随机对照试验的二次分析，该试验评估阿托西班与特布他林作为子宫松弛剂在 36 周或以上单胎臀位孕妇 ECV 中的有效性。潜在的预测因素包括母体、妊娠、胎儿和治疗特征，并记录在所有参与者中。使用逐步后退选择程序的多变量逻辑回归分析构建预测 ECV 成功发生的模型。使用校准和区分来评估模型性能。
我们共纳入 818 名女性，ECV 总体成功率为 37%。通过逐步选择程序确定了 10 个与 ECV 成功相关的预测因素：特布他林作为子宫松弛剂、初产妇、白种人、ECV 时的孕龄、羊水指数、臀位类型、胎盘位置、臀位衔接、触诊头的可能性和子宫松弛。我们的模型显示出良好的校准和良好的区分能力，C 统计量为 0.78（95%置信区间 0.75 至 0.81）。
使用表现良好的模型预测 ECV 的成功似乎是可行的。这可以在外部验证后在临床实践中使用。
