Objective  To investigate the risk factors for the formation of infectious stones among residents in western Fujian Province and construct a nomogram model for preoperative prediction of the risk of infectious stones.

Methods  Clinical data of 204 patients who received treatment for urinary tract stones at Longyan People′s Hospital Affiliated to Xiamen Medical University from October 2021 to November 2023 were analyzed. All patients underwent stone composition analysis. Univariate and multivariate Logistic regression analysis were used to screen independent risk factors for infectious stones, construct a nomogram model for predicting the risk of infectious stones, and the discriminative power and accuracy of the model was evaluated.

Results  Based on the results of stone composition analysis, 204 patients were divided into infectious stone group(56 cases) and non-infectious stone group(148 cases). Univariate and multivariate Logistic regression analysis showed that female (OR=2.602, 95%CI, 0.766 to 8.842, P=0.039), diabetes (OR=9.751, 95%CI, 2.547 to 17.332, P=0.001), long diameter of stones (OR=1.123, 95%CI, 1.046 to 4.207, P=0.031), moderate to severe hydronephrosis (OR=4.173, 95%CI, 1.256 to 13.865, P=0.020), high urine pH value (OR=6.078, 95%CI, 1.922 to 19.216, P=0.002), and positive urine culture (OR=6.060, 95%CI, 1.398 to 16.262, P=0.016) were independent risk factors for infectious stones. A nomogram model for predicting the risk of infectious stones was constructed based on independent risk factors. The area under the curve of this model for predicting infectious stones was 0.860, which was significantly larger than the area under the curve predicted by gender, diabetes, stone long diameter, degree of hydronephrosis, urine pH value, and urine culture results (P < 0.05). The model was validated by 1 000 internal resampling, with an average absolute error of 1.8%, indicating a high consistency between the predicted risk of infectious stones and the actual situation.

Conclusion  Female, diabetes, long diameter of stones, moderate to severe hydronephrosis, high urine pH value, and positive urine culture are independent risk factors for infectious stones among residents in western Fujian Province. The nomogram model constructed based on these factors can predict the risk of infectious stones preoperatively with high predictive efficiency.