Abstract

Objectives

This study aims to identify risk factors for acute kidney injury (AKI) in patients with ureterolithiasis and to develop a predictive model for early AKI detection in this population.

Methods

A retrospective analysis was conducted on data from 1,016 patients with ureterolithiasis who presented to our outpatient emergency department between January 2021 and December 2022. Using multifactorial logistic regression, we identified independent risk factors for AKI and constructed a nomogram to predict AKI risk. The predictive model’s efficacy was assessed through the area under the ROC curve, calibration curves, Hosmer-Lemeshow (HL) test, and decision curve analysis (DCA).

Results

AKI was diagnosed in 18.7% of the patients. Independent risk factors identified included age, fever, diabetes, hyperuricemia, bilateral calculi, functional solitary kidney, self-medication, and prehospital delay. The nomogram demonstrated excellent discriminatory capabilities, with AUCs of 0.818 (95% CI, 0.775–0.861) for the modeling set and 0.782 (95% CI, 0.708–0.856) for the validation set. Both calibration curve and HL test results confirmed strong concordance between the model’s predictions and actual observations. DCA highlighted the model’s significant clinical utility.

Conclusions

The predictive model developed in this study provides clinicians with a valuable tool for early identification and management of patients at high risk for AKI, thereby potentially enhancing patient outcomes.

Details

Title
Development and validation of a predictive model for acute kidney injury in patients with ureterolithiasis
Author
Jiang, Yufeng 1 ; Zhang, Jingcheng 2 ; Ainiwaer, Ailiyaer 2 ; Liu, Yuchao 2 ; Li, Jing 3 ; Zhou, Liuliu 4 ; Yang, Yan 5 ; Zhang, Haimin 3 

 School of Medicine, Tongji University, Shanghai, China; Department of Urology, Chongming Branch, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China 
 School of Medicine, Tongji University, Shanghai, China 
 Department of Urology, Chongming Branch, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China 
 Medical Department, Chongming Branch, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China 
 Department of Urology, Chongming Branch, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China; Department of Urology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China 
Publication year
2024
Publication date
Dec 2024
Publisher
Taylor & Francis Ltd.
ISSN
0886022X
e-ISSN
15256049
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3157380521
Copyright
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons  Attribution – Non-Commercial License http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.