Formula for predicting the impaction of ureteral stones.

The purpose of the study was to investigate variables that may predict ureteral stone impaction and create a new model to predict more accurately stone impaction based on preoperative NCCT findings. Data of 238 patients who underwent URS were analyzed. Stone size, stone location, Hounsfield unit (HU) value of the stone, ureteral wall thickness (UWT) and grade of hydronephrosis were recorded. HU values of the ureter which are measured proximal and distal to the stone were recorded. Subsequently, we determined the factors that could predict the stone impaction in univariate and multivariate logistic regression analysis. After the AUC analysis for these factors, we created a new model to predict more accurately stone impaction. The formula was named Impacted Stone Formula (ISF). Stone impaction verified endoscopically. Predictors of impacted stones were evaluated using univariate and multivariate logistic regression analyses. Diagnostic value for the prediction of stone impaction was analyzed with receiver operating characteristic (ROC) incline. Overall, there were 196 patients included in the study. Multivariate regression analysis revealed that the HU below/above ratio, UWT, and grade of hydronephrosis were the crucial predictors of stone impaction (OR 20.53, p < 0.001; OR 10.55, p < 0.001; OR 5.95, p = 0.004, respectively). The ROC analysis revealed a cutoff value of 15.15 (AUC 0.958, p < 0.001, sensitivity 91.0%, specificity 97.7%) for the ISF. In conclusion, ISF is the most precise preoperative predictor of impacted stones in patients with ureteral stones. ISF could be used by the urologists before treatment to help preoperative planning and perioperative clinical course.