A comparison of antenatal prediction models for vaginal birth after caesarean section

Abstract

Introduction: An antenatal scoring system for vaginal birth after caesarean section (VBAC) categorises patients into a low or high probability of successful vaginal delivery. It enables counselling and preparation before labour starts. The current study aims to evaluate the role of Grobman nomogram and the Kalok scoring system in predicting VBAC success in Singapore. Methods: This is a retrospective study on patients of gestational age 37 weeks 0 day to 41 weeks 0 day who underwent a trial of labour after 1 caesarean section between September 2016 and September 2017 was conducted. Two scoring systems were used to predict VBAC success, a nomogram by Grobman et al. in 2007 and an additive model by Kalok et al. in 2017. Results: A total of 190 patients underwent a trial of labour after caesarean section, of which 103 (54.2%) were successful. The Kalok scoring system (AUC [area under the curve] 0.740) was a better predictive model than Grobman nomogram (AUC 0.664). Patient’s age odds ratio [OR] 0.915, 95% CI [confidence interval] 0.844–0.992), body mass index at booking (OR 0.902, 95% CI 0.845–0.962), and history of successful VBAC (OR 4.755, 95% CI 1.248–18.120) were important factors in predicting VBAC. Conclusion: Neither scoring system was perfect in predicting VBAC among local women. Further customisation of the scoring system to replace ethnicity with the 4 races of Singapore can be made to improve its sensitivity. The factors identified in this study serve as a foundation for developing a population-specific antenatal scoring system for Singapore women who wish to have a trial of VBAC. Keywords: Antenatal scoring system, caesarean section, obstetrics and gynaecology, trial of labour after caesarean section, vaginal birth after caesarean section

External validation of vaginal birth after cesarean delivery calculator in Israeli cohort of parturients and construction of an improved model

“…Possible explanations for that gap include the absence of maternal ethnicity as a contributing variable, as all women in the study cohort were white. It coefficients, and overall prediction performance, [21][22][23][24] suggesting the need to develop a scoring system tailored for each specific population.…”

“…Despite the adoption and recommendation of one TOLAC calculator by the MFMU in the United States, other calculators were created inside and outside the United States with different variables, coefficients, and overall prediction performance, 21–24 suggesting the need to develop a scoring system tailored for each specific population.…”