Development and validation of a predictive model for double-J stent encrustation after upper urinary tract calculi surgery

Abstract

Abstract The study is aimed to establish a predictive model of double-J stent encrustation after upper urinary tract calculi surgery. We collected the clinical data of 561 patients with indwelling double J tubes admitted to a hospital in Shandong Province from January 2019 to December 2020 as the modeling group and 241 cases of indwelling double J tubes from January 2021 to January 2022 as the verification group. Univariate and binary logistic regression analysis were used to explore risk factors, the risk prediction equation was established and the receiver operating characteristic (ROC) curve analysis model was used for prediction. In this study, 104 of the 561 patients developed double-J stent encrustation, with an incidence rate of 18.5%. We finally screened out BMI > 23.9 (OR = 1.648), Preoperative urine routine white blood cell quantification (OR = 1.149), double J tube insertion time (OR = 0.566), postoperative water consumption did not reach 2000ml/d (OR = 8.514) a total of 4 Factors build a risk prediction model. From the ROC curve analysis, the area under the curve (AUC) was 0.844, and the maximum Oden index was 0.579. At this time, the sensitivity was 0.735, and the specificity was 0.844. The research established in this study has a high predictive value for the occurrence of double-J stent encrustation in the double-J tube after upper urinary tract stone surgery, which provides a basis for the prevention and treatment of double-J stent encrustation.