A nomogram for predicting the risk of residual stone fragments after ureteroscopy.

ABSTRACT:

Background

The residual stone fragment is a tremendous issue after ureteroscopic lithotripsy and requires urologists to evaluate the condition of patients comprehensively. Our study aimed to construct a nomogram to make a personalized prediction of postoperative residual stone rate (RSR).

Methods

We implemented a retrospective cohort study in the Department of Urology, Shanghai General Hospital. A total of 277 patients undergoing ureteroscopy (URS) were enrolled in our study. Among them, 186 patients were included in the training group and the remaining 91 patients comprised the testing group. We utilized stepwise forward algorithm and logistic regression analysis to build predictive models and selected the best model based on Akaike's information criterion (AIC). The model

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC10080353 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature