Fagerberg Marie C, Maršál Karel, Källén Karin
Department of Obstetrics and Gynecology, Ystad Hospital, Ystad, Sweden; Department of Obstetrics and Gynecology, Clinical Sciences Lund, Lund University, Lund, Sweden.
Department of Obstetrics and Gynecology, Clinical Sciences Lund, Lund University, Lund, Sweden.
Eur J Obstet Gynecol Reprod Biol. 2015 May;188:88-94. doi: 10.1016/j.ejogrb.2015.02.031. Epub 2015 Mar 10.
We aimed to validate a widely used US prediction model for vaginal birth after cesarean (Grobman et al. [8]) and modify it to suit Swedish conditions.
Women having experienced one cesarean section and at least one subsequent delivery (n=49,472) in the Swedish Medical Birth Registry 1992-2011 were randomly divided into two data sets. In the development data set, variables associated with successful trial of labor were identified using multiple logistic regression. The predictive ability of the estimates previously published by Grobman et al., and of our modified and new estimates, respectively, was then evaluated using the validation data set. The accuracy of the models for prediction of vaginal birth after cesarean was measured by area under the receiver operating characteristics curve.
For maternal age, body mass index, prior vaginal delivery, and prior labor arrest, the odds ratio estimates for vaginal birth after cesarean were similar to those previously published. The prediction accuracy increased when information on indication for the previous cesarean section was added (from area under the receiver operating characteristics curve=0.69-0.71), and increased further when maternal height and delivery unit cesarean section rates were included (area under the receiver operating characteristics curve=0.74). The correlation between the individual predicted vaginal birth after cesarean probability and the observed trial of labor success rate was high in all the respective predicted probability decentiles.
Customization of prediction models for vaginal birth after cesarean is of considerable value. Choosing relevant indicators for a Swedish setting made it possible to achieve excellent prediction accuracy for success in trial of labor after cesarean. During the delicate process of counseling about preferred delivery mode after one cesarean section, considering the results of our study may facilitate the choice between a trial of labor or an elective repeat cesarean section.
我们旨在验证一种广泛使用的美国剖宫产术后阴道分娩预测模型（格罗布曼等人[8]），并对其进行修改以适应瑞典的情况。
1992 - 2011年瑞典医学出生登记处中经历过一次剖宫产且至少有一次后续分娩的女性（n = 49472）被随机分为两个数据集。在开发数据集中，使用多元逻辑回归确定与成功试产相关的变量。然后使用验证数据集评估格罗布曼等人先前发表的估计值以及我们修改后的和新的估计值的预测能力。剖宫产术后阴道分娩预测模型的准确性通过受试者操作特征曲线下面积来衡量。
对于产妇年龄、体重指数、既往阴道分娩和既往产程停滞，剖宫产术后阴道分娩的比值比估计值与先前发表的相似。添加先前剖宫产指征的信息后，预测准确性提高（受试者操作特征曲线下面积从0.69 - 0.71），纳入产妇身高和分娩单位剖宫产率后进一步提高（受试者操作特征曲线下面积 = 0.74）。在所有各自预测概率十分位数中，个体预测的剖宫产术后阴道分娩概率与观察到的试产成功率之间的相关性都很高。
剖宫产术后阴道分娩预测模型的定制具有相当大的价值。选择瑞典背景下的相关指标能够实现剖宫产术后试产成功的出色预测准确性。在关于一次剖宫产后首选分娩方式的精细咨询过程中，考虑我们的研究结果可能有助于在试产或择期再次剖宫产之间做出选择。
