An intrapartum calculator for predicting cesarean birth due to dystocia: Preliminary findings from a single‐center study in Korea

Previous calculators based on antepartum or pre-labor factors preclude intrapartum counseling. We aimed to develop a reliable, programmable, intrapartum calculator to predict the risk of cesarean birth (CB) due to dystocia and to increase the discriminatory accuracy of the predictive model.Data were obtained retrospectively for 1326 singleton term deliveries with cephalic presentation. Two predictive multivariable logistic regression analysis models were constructed using pre-active labor variables alone (model A) or with active labor variables (model B). The discriminatory accuracies and goodness-of-fit of the models were compared using receiver operating characteristic (ROC) curves or -2log-likelihood ratios, Akaike information criterion (AIC), and Bayesian information criterion (BIC), respectively. Both models were internally validated using a bootstrapping procedure.Model A yielded an area under the curve (AUC) of 0.859 and adequate goodness of fit (P = 0.970). Model B yielded a significantly higher AUC of 0.887 and adequate goodness of fit (P = 0.624), as well as a significantly lower AIC and BIC (P < 0.001). Internal validation revealed a minimal optimism of 0.0070491 and 0.0068976 for models A and B, respectively. Finally, the logistic regression equations were converted into programmable calculators to yield easy-to-understand basic (model A) and additional intrapartum CB calculators (model B).The programmable calculators developed herein can augment intrapartum counseling. Our findings suggest that the risk of CB due to dystocia during labor should be estimated using a calculator that corresponds to labor progression. Further studies should explore external validation of these statistical models before translation to a clinical setting.