Establishment of a new predictive model for the recurrence of upper urinary tract stones.

To construct a nomogram for evaluation of the recurrence risk of upper urinary tract stones in patients.

We retrospectively reviewed the clinical data of 657 patients with upper urinary tract stones and divided them into stone recurrence group and non-recurrence group. Blood routine, urine routine, biochemical, and urological CT examinations were searched from the electronic medical record, relevant clinical data were collected, including age, BMI, stones number and location, maximum diameter, hyperglycemia, hypertension, and relevant blood and urine parameters. The Wilcoxon rank-sum test, independent sample t test, and Chi-square test were used to preliminarily analyze the data of the two groups, then LASSO and logistic regression analysis were used to find out the significant difference indicators. Finally, R software was used to draw a nomogram to construct the model, and ROC curve was drawn to evaluate the sensitivity and specificity.

The results showed that multiple stones (OR: 1.832, 95% CI 1.240-2.706), bilateral stones (OR: 1.779, 95% CI 1.226-2.582), kidney stones (OR: 3.268, 95% CI 1.638-6.518), and kidney ureteral stones (OR: 3.375, 95% CI 1.649-6.906) were high risk factors. And the stone recurrence risk was positively correlated with creatinine (OR: 1.012, 95% CI 1.006-1.018), urine pH (OR: 1.967, 95% CI 1.343-2.883), Apo B (OR: 4.189, 95% CI 1.985-8.841) and negatively correlated with serum phosphorus (OR: 0.282, 95% CI 0.109-0.728). In addition, the sensitivity and specificity of the prediction model were 73.08% and 61.25%, diagnosis values were greater than any single variable.

The nomogram model can effectively evaluate the recurrence risk of upper urinary stones, especially suitable for stone postoperative patients, to help reduce the possibility of postoperative stone recurrence.

International urology and nephrology. 2023 Jul 12 [Epub ahead of print]

Kaiguo Xia, Yuexian Xu, Qiao Qi, Qingfeng Huang, Rui Yao, Junzhi Zhang, Zongyao Hao

Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China., Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China. .