Development of a model for predicting success of trial of labor after cesarean delivery at term

Abstract

Objective To establish a suitable model for predicting the success of trial of labor after cesarean section (TOLAC) during the pregnancy at term. Methods Data for all deliveries at term with one cesarean delivery history in Shenzhen Maternity and Child healthcare hospital during 1 January 2012 to 31 December 2014 were reviewed. Variables associated with VBAC were identified and used to build a model to predict the outcome of TOLAC with multivariable logistic regression. Godness of fit and accuracy of the model were evaluated by ROC. Results A total of 531 women met inclusion criteria and underwent TOLAC. Of the women who underwent trial of labor, 448 (84.4%) had a successful VBAC, 83 failed, and 2 (0.38%) had uterine rupture. Multivariable logistic regression analysis showed that previous cesarean section (CS) time interval, neonatal birth weight (BW) and premature rupture of membranes (PROM) were independent factors affecting TOLAC outcome, and their Odds Ratios were 2.79, 1.002 and 0.244, respectively. The Logistic regression model was expressed as follows: P=1/[1+ exp (2.4×neonatal BW+ 1.03× previous CS time interval -1.41×PROM -10.24)]. The Hosmer-lemeshow test showed that the model fitted well (χ2=123.45, P=0.996), and the prediction accuracy of the model was 86.77%. The model performed well with an AUC of 0.794 (P=0.000). Conclusions A predictive model, which contains three variables (previous CS time interval, neonatal BW and PROM), has been developed and its prediction efficiency and accuracy are satisfactory. The larger birth weight, the longer time interval from previous CS, and the absence of PROM are more likely to be failed in TOLAC. Key words: Vaginal birth after cesarean; Logistic models; Forecasting