Abstract: Objective To investigate the risk factors of positive urinary nitrite before urological stone lithotripsy and construct a nomogram prediction model.Methods Retrospective data collection was conducted on 400 patients undergoing lithotripsy for urinary tract stones admitted to our hospital between October 2023 and October 2025.Preoperative urinary nitrite positivity was analyzed using univariate and multivariate Logistic regression to identify risk factors.A cut-off point prediction model was constructed using R software, with predictive value assessed via receiver operating characteristic (ROC) curve analysis.Results The preoperative urinary nitrite positivity rate in this study was 13.25%.Bivariate Logistic regression analysis revealed that the female gender, diabetes mellitus, ureteral stone location, bilateral stones, stone size, severe hydronephrosis, and preoperative blood WBC count were all independent risk factors (P<0.05).ROC results showed that the AUC for predicting preoperative urinary nitrite positivity in urolithiasis using the Logistic regression model was 0.824 (95%CI: 0.767-0.880).Calibration curves closely approximated the standard curve.Decision curves indicated high net benefit for the model's predictions within a threshold probability range of 0.1-0.9.Paired differences in ROC curves revealed that the predictive model's AUC exceeded that of the single predictor (P<0.05).Conclusion Female gender, diabetes, ureteral stones, bilateral stones, stone size, severe hydronephrosis, and preoperative blood WBC were all independent risk factors for positive urinary nitrite prior to urolithotomy.The nomogram prediction model constructed based on these factors demonstrated excellent discrimination, calibration, and clinical utility.

Key words: urinary stone surgery; preoperative; urinary nitrite; positive; risk factors; nomogram; predictive model