A predictive nomogram for a failed trial of labor after cesarean: A retrospective cohort study

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.