Establishment and validation of a predictive model for renal injury caused by unilateral upper urinary tract stone...

This study aimed to develop and validate a predictive model for assessing the risk of renal impairment due to unilateral upper urinary tract stone obstruction, leveraging easily accessible clinical indicators to overcome the limitations of traditional renal function markers and the impracticality of Dynamic Renal Scintigraphy (DRS) in routine clinical practice.

A multicenter, retrospective cohort study was conducted with 370 patients who had unilateral upper urinary tract stones and underwent DRS. Patients were split into training (n = 259) and validation (n = 111) groups. Initial screening of 16 candidate variables led to the identification of five key predictors via LASSO regression: age, asymptomatic status, maximum stone cross-sectional area, urine white blood cell count, and hydronephrosis Society for Fetal Urology (SFU) grade. A nomogram was developed to visualize the model, and its performance was assessed using ROC curves, calibration plots, and decision curve analysis (DCA).

The model demonstrated robust discrimination, with AUC values of 0.742 (95% CI: 0.61-0.82) in the training set and 0.793 (95% CI: 0.675-0.911) in the validation set. Calibration curves confirmed high accuracy, and DCA highlighted significant clinical value. Older age, asymptomatic presentation, larger stone size, elevated urine white blood cells, and higher SFU grade were independently linked to a higher risk of renal impairment.

The proposed nomogram offers a practical, non-invasive method for early identification of patients at high risk of renal impairment from unilateral upper urinary tract stone obstruction, enabling timely intervention and optimized resource utilization. This model is particularly beneficial in primary care settings where DRS is unavailable, providing a cost-effective alternative to mitigate irreversible renal damage.