Liu Haiyan, Yu Yi, Zhang Xiaoyue, Pei Jiangnan, Tang Yao, Hu Rong, Gu Weirong
Department of Obstetrics, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.
Ann Med. 2025 Dec;57(1):2523617. doi: 10.1080/07853890.2025.2523617. Epub 2025 Jun 28.
The transition from one-child to two-child and three-child policy in China has increasingly led to a rise in the number of women who choose trial of labor after cesarean section (TOLAC). Achieving vaginal birth after cesarean section (VBAC) is, however, not always guaranteed, and a failed TOLAC is associated with a high risk of maternal and neonatal complications. Although Grobman's model may help predict VBAC, variations in population characteristics and healthcare settings can limit its generalizability and validity on a global scale. This study, therefore, seeks to develop and validate an improved prediction model for VBAC at the onset of labor among the Chinese population.
Seven hundred and twenty women who attempted a TOLAC were enrolled. The development dataset comprised 481 women, while the other 239 women constituted the temporal validation dataset. Variable selection was executed using the least absolute shrinkage and selection operator method. Model development was performed using logistic regression techniques and was presented as a nomogram.
Of the participants, 81.4% achieved VBAC. The model included maternal age, maternal height, ratio of weight gain to pre-pregnancy weight, interval time of pregnancies, previous vaginal delivery, premature rupture of membranes, oxytocin administration, spontaneous labor onset, labor analgesia, and newborn weight. The development and temporally validated areas under the curve were 0.780 (95% confidence interval 0.726-0.834) and 0.774 (95% confidence interval 0.694-0.854), respectively. Internal validation performed by bootstrap resampling, calibration curves, and Hosmer-Lemeshow test confirmed the model's robust performance. An optimal predicted probability cut-off of 0.7 was identified by decision curve analysis and clinical considerations.
The improved predictive VBAC model exhibited adequate performance such that women with a prior low transverse cesarean delivery who scored 0.7 or higher (in the model-derived probability score) would consider TOLAC, potentially leading to a reduction in maternal-neonatal morbidity.
The study was approved by the Ethical Committee of Obstetrics and Gynecology Hospital, Fudan University (2018-43) and was registered in the Chinese Clinical Trial Registry (ChiCTR1900022484), https://www.chictr.org.cn/showproj.html?proj=37898. The study adhered to the Declaration of Helsinki. The first participant was enrolled on January 1, 2016. The requirement for informed consent was waived because the data were anonymized.
中国从独生子女政策向二孩、三孩政策的转变,使得越来越多的女性选择剖宫产术后试产(TOLAC)。然而,并非总能保证剖宫产术后经阴道分娩(VBAC)成功,TOLAC失败与母婴并发症的高风险相关。尽管格罗布曼模型可能有助于预测VBAC,但人群特征和医疗环境的差异会限制其在全球范围内的普遍性和有效性。因此,本研究旨在开发并验证一种针对中国人群分娩开始时VBAC的改进预测模型。
纳入720名尝试TOLAC的女性。开发数据集包括481名女性,另外239名女性构成时间验证数据集。使用最小绝对收缩和选择算子方法进行变量选择。采用逻辑回归技术进行模型开发,并以列线图形式呈现。
参与者中,81.4%实现了VBAC。该模型包括产妇年龄、产妇身高、体重增加与孕前体重之比、妊娠间隔时间、既往阴道分娩史、胎膜早破、缩宫素使用、自然临产、分娩镇痛和新生儿体重。开发数据集和时间验证数据集的曲线下面积分别为0.780(95%置信区间0.726 - 0.834)和0.774(95%置信区间0.694 - 0.854)。通过自助重采样、校准曲线和霍斯默 - 莱梅肖检验进行的内部验证证实了该模型的稳健性能。通过决策曲线分析和临床考虑确定最佳预测概率截断值为0.7。
改进的VBAC预测模型表现出足够的性能,使得既往有低位横切口剖宫产史且模型得出的概率评分达到或高于0.7的女性可以考虑TOLAC,这可能会降低母婴发病率。
本研究经复旦大学附属妇产科医院伦理委员会批准(2018 - 43),并在中国临床试验注册中心(ChiCTR1900022484)注册,网址为https://www.chictr.org.cn/showproj.html?proj=37898。本研究遵循赫尔辛基宣言。首位参与者于2016年1月1日入组。由于数据已匿名,故豁免知情同意要求。