A novel comprehensive predictive model for obstructive pyonephrosis patients with upper urinary tract stones.

BACKGROUND: Calculous pyonephrosis tended not to be accurately diagnosed before operations. It is mostly confirmed during percutaneous nephrolithotripsy or percutaneous nephrostomy. We aimed to evaluate the risk factors for predicting obstructive pyonephrosis patients with upper urinary tract stones. METHODS: Clinical data of 322 patients with upper urinary tract stones and obstructive hydronephrosis were retrospectively searched and analyzed in our study. The patients were divided into two groups; pyonephrosis and non-pyonephrosis groups. Both disease related factors and infection-associated indicators were analyzed. Univariate and multivariate logistic analyses were performed on preoperative variables. Accordingly, ROC curves were drawn, and a novel comprehensive model was constructed to predict the pyonephrosis. OUTCOMES: =0.009). Based on these risk factors, we constructed a novel comprehensive model and confirmed it was an effective method to predict pyonephrosis (AUC, 0.970). Bootstrapped calibration curves showed no untoward deviation in both training and validation dataset (mean absolute error of 0.027, 0.036). CONCLUSIONS: Hydronephrosis, CT value of hydronephrosis, blood neutrophils, urine leukocyte, and urine culture were independent risk factors to predict pyonephrosis. The novel comprehensive model was found to be an effective method to predict pyonephrosis and needed to be further confirmed in prospective studies.