Lakra Pinkey, Patil Bhagyashri, Siwach Sunita, Upadhyay Manisha, Shivani Shivani, Sangwan Vijayata, Mahendru Rajiv
Bhagat Phool Singh Government Medical College for Women, Khanpurkalan, Sonepat, Haryana, India.
Turk J Obstet Gynecol. 2020 Dec;17(4):278-284. doi: 10.4274/tjod.galenos.2020.82205. Epub 2020 Dec 10.
To create a new and simple model for predicting the likelihood of vaginal birth after cesarean (VBAC) section using variables available at the time of admission.
A prospective observational study was performed at a tertiary care centre in Haryana over a period of 12 months (January 2018 - December 2018) in pregnant women attending the labour room with one previous cesarean section fulfilling the criteria for undergoing trial of labour after cesarean (TOLAC). The sample size was 150. A VBAC score was calculated for each patient using a new prediction model that included variables available at the time of admission such as maternal age, gestational age, Bishop's score, body mass index, indication for primary cesarean section, and clinically estimated fetal weight. The results of the VBAC scores were correlated with outcomes i.e. successful VBAC or failed VBAC. The chi-square test and Student's t-test was used for comparison among the groups. Descriptive and regression analysis was performed for the study variables.
Out of 150 TOLAC cases, 78% had successful VBAC and the remainder (22%) had failed VBAC. The observed probability of having a successful VBAC for a VBAC score of 0-3 was 34%, 4-6 was 68%, 7-9 was 90%, and ≥10 was 97%. The prediction model performed well with an area under the curve of 0.77 (95% CI: 0.68 to 0.85) of the receiver operating characteristics receiver operating characteristic curve.
The present study shows that the proposed VBAC prediction model is a good tool to predict the outcome of TOLAC and can be used to counsel women regarding the mode of delivery in the current and subsequent pregnancies. Further studies of this model and other such models with different permutations and combinations of variables are required.
利用入院时可得的变量创建一种新的、简单的模型，用于预测剖宫产术后阴道分娩（VBAC）的可能性。
在哈里亚纳邦的一家三级医疗中心进行了一项前瞻性观察研究，为期12个月（2018年1月至2018年12月），研究对象为前往产房的曾有一次剖宫产史且符合剖宫产术后试产（TOLAC）标准的孕妇。样本量为150例。使用一种新的预测模型为每位患者计算VBAC评分，该模型纳入了入院时可得的变量，如产妇年龄、孕周、 Bishop评分、体重指数、首次剖宫产指征以及临床估计胎儿体重。将VBAC评分结果与结局（即成功VBAC或失败VBAC）进行关联。采用卡方检验和学生t检验进行组间比较。对研究变量进行描述性分析和回归分析。
在150例TOLAC病例中，78%成功进行了VBAC，其余（22%）VBAC失败。VBAC评分为0 - 3分时成功VBAC的观察概率为34%，4 - 6分为68%，7 - 9分为90%，≥10分为97%。预测模型表现良好，受试者工作特征曲线下面积为0.77（95%CI：0.68至0.85）。
本研究表明，所提出的VBAC预测模型是预测TOLAC结局的良好工具，可用于为孕妇提供当前及后续妊娠分娩方式的咨询。需要对该模型以及其他具有不同变量排列组合的此类模型进行进一步研究。
