A predictive nomogram for a failed trial of labor after cesarean: A retrospective cohort study. Issue 11 (2nd September 2022)

• Record Type: Journal Article
• Authors: Li, Hua; Sheng, Wen; Cai, Min; Chen, Qiuling; Lin, Beibei; Zhang, Weishe; Li, Wenxia
• Is Part Of: Journal of obstetrics and gynaecology research. Volume 48:Issue 11(2022)
• Page Start: 2798
• Page End: 2806
• Publication Date: 2022-09-02
• Subjects: cesarean section -- nomogram -- prediction -- trial of labor after a cesarean -- vaginal birth; Gynecology -- Periodicals; Obstetrics -- Periodicals; 618.1005
• DOI: 10.1111/jog.15398
• Languages: English
• ISSNs: 1341-8076

Abstract

Abstract: Aim: To validate risk factors and a nomogram prediction model for the failure of a trial of labor after cesarean section (TOLAC) in a Chinese population. Methods: We included women who tried TOLAC between January 2017 and May 2019, grouped according to the success/failure of TOLAC. The patients were randomized 3:1 into the development and validation sets. Multivariable logistic regression analyses were used to develop a nomogram prediction model for TOLAC failure. Results: In total, 535 (86.3%) of the women ( n = 620) aged 29–34 years had a successful vaginal birth after cesarean (VBAC). All women had a fully healed previous uterine incision. The univariable analyses showed that the cephalopelvic score ( p < 0.001), BMI ( p = 0.001), full engagement into the pelvis ( p < 0.001), Bishop cervical maturity score ( p < 0.001), and estimated fetal weight at admission ( p < 0.001) could enter the multivariable model. Furthermore, the multivariable analysis showed that the cephalopelvic score (OR = 0.42, 95%CI: 0.23–0.77, p = 0.005), full engagement in the pelvis (OR = 0.16, 95%CI: 0.08–0.33, p < 0.001), and Bishop cervical maturity score (OR = 0.46, 95%CI: 0.35–0.59, p < 0.001) were independent predictors of the failure of TOLAC. Conclusion: This study proposes a nomogram that can assess the risk of failure of TOLAC in Chinese pregnant women. The statistical model could help clinicians know the likelihood of successful TOLAC in the clinical setting.