Publication Description
BACKGROUND: Investigators have attempted to derive tools that could provide clinicians with an easily-obtainable estimate of the chance of vaginal birth after cesarean (VBACr those who undertake trial of labor after cesarean (TOLAC). One tool that subsequently was validated externally was derived from data from the Maternal-Fetal Medicine Units (MFMU) Cesarean Registry. Concern has been raised, however, that this tool includes the socially-constructed variables of race and ethnicity. OBJECTIVE: To develop an accurate tool to predict VBAC, using data easily obtainable early in pregnancy, without the inclusion of race/ethnicity. STUDY DESIGN: This is a secondary analysis of the Cesarean Registry of the MFMU Network. The approach to the present analysis is similar to that of the analysis in which the prior VBAC prediction tool was derived. Specifically, individuals were included in this analysis if they were delivered on or after 37 0/7 weeks' gestation with a live singleton cephalic fetus at the time of labor and delivery admission, had a TOLAC, and had history of one prior low-transverse cesarean delivery. Information was only considered for inclusion in the model if it was ascertainable at an initial prenatal visit. Model selection and internal validation were performed using a cross-validation procedure, with the dataset randomly and equally divided into a training set and a test set. The training set was used to identify factors associated with VBAC and build the logistic regression predictive model using stepwise backward elimination. A final model was generated that included all variables found to be significant (phttps://mfmunetwork.bsc.gwu.edu/web/mfmunetwork/vaginal-birth-after-ces… ulator), which did not include race or ethnicity, for estimation of VBAC probability.