Abstract
To explore the diagnostic efficacy of the computed tomography (CT) attenuation value of renal pelvic urine in true bacteriuria secondary to renal and ureteral stones, and to construct a nomogram prediction model. This retrospective study analyzed data from patients with renal and ureteral stones. The participants were categorized into an infection group (n = 41) and a control group (n = 208) based on their urine culture. Risk factors were identified via logistic regression, and ROC analysis was used to evaluate the diagnostic performance. A risk prediction nomogram model was constructed and verified for risk factors. The infection group exhibited higher renal pelvis urine CT values (13.41 ± 5.11 vs. controls, P < 0.0001), with optimal diagnostic accuracy [area under the curve (AUC) = 0.867]. Logistic regression analysis showed that advanced age, positive urinary leukocyte esterase (LE) (+) levels, and increased CT values of the renal pelvis urine were risk factors. The AUC of the nomogram model was 0.94. The calibration curve and clinical decision curve analysis verified that this model had a good predictive performance. The CT value of renal pelvic urine can be used to predict the risk of bacteriuria secondary to renal and ureteral stones. An average CT value of renal pelvis urine >7.25 HU, age >57.5 years, and positive urine LE (≥1+) are risk factors. The nomogram prediction model incorporating these factors allowed for the rapid assessment of patients with urinary tract stones, demonstrating high predictive accuracy and significant clinical value.