Can Double J stent encrustation be predicted by risk analysis and nomogram?: A retrospective case–control study

Author:

Liu Zicheng1,Yan Minbo1,Naji Yaser1,Qiu Junliang1,Wang Haojie1,Lin Yuteng1,Dai Yingbo1ORCID

Affiliation:

1. Department of Urology, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China.

Abstract

To explore the risk factors and develop a nomogram to predict Double J stent encrustation incidence. The general demographic characteristics and underlying risk factors of 248 patients with upper urinary tract calculus who underwent endoscopic lithotripsy and Double J stenting at the Fifth Affiliated Hospital of Sun Yat-Sen University between January 1st, 2018 and January 1st, 2023 were retrospectively analyzed. Among them,173 patients were randomly selected to form the development cohort. A multivariate logistic regression model was employed to identify the independent risk factors associated with Double J stent encrustation, and a nomogram was developed for predicting its occurrence. Additionally, 75 patients were randomly selected to form the validation cohort to validate the nomogram. Multivariate logistic regression analysis revealed that several factors were significantly associated with Double J stent encrustation: indwelling time (odds ratio [OR]1.051; 95% confidence interval [CI] 1.030–1.073, P < .001), urine PH (OR 2.198; 95% CI 1.061–4.539, P = .033), fasting blood glucose (OR 1.590; 95% CI 1.300–1.943, P < .001), and total cholesterol (OR 2.676; 95% CI 1.551–4618, P < .001).Based on these findings, A nomogram was developed to predict the occurrence of Double J stent encrustation. The nomogram demonstrated good performance with an area under the curve of 0.870 and 0.862 in the development and validation cohorts, respectively. Furthermore, the calibration curve indicated a well-fitted model. We constructed and validated an accessible nomogram to assist urologists in evaluating the risk factors associated with Double J stent encrustation and predicting its likelihood.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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