Clinical characteristics and nomogram model for predicting the risk of recurrence of complicated urinary tract infection in pediatric patients

Author:

Jiang Jing1,Chen Xiu-Ying1,Guo Hui1

Affiliation:

1. West China Second University Hospital of Sichuan University

Abstract

Abstract

Complicated urinary tract infection (cUTI) has higher incidences of antibiotic resistance, recurrence, chronicity, and progression. However, there has been no prediction model for cUTI recurrence in pediatric patients for targeted interventions. This study aimed to establish a nomogram to p`redict the risk of cUTI recurrence for better prevention and treatment of cUTI in pediatric patients. The nomogram was developed based on a retrospective cohort that included 421 pediatric patients with cUTI at West China Second University Hospital from January 2020 to August 2023. The patients were randomly divided into a training set and a validation set in a 3:1 ratio. Logistic regression analysis was used to identify risk factors and construct the nomogram for predicting the risk of cUTI recurrence, followed by validation and performance analysis. Of the 421 children with cUTI, the recurrence rate of cUTI was 68.4% (288 cases) during an average follow-up duration of 22.9 months. The nomogram comprised female gender, history of urinary tract surgery, Escherichia coli in urine culture, renal dysfunction, and vesicoureteral reflux as predictors of cUTI recurrence in pediatric patients. The model showed favorable performance with a C-index of 0.735 in the training dataset and a C-index of 0.750 in the validation dataset. The clinical decision curves revealed that the nomogram was clinically useful. The first reliable nomogram was constructed for predicting the risk of cUTI recurrence in pediatric patients, which would be beneficial for clinicians to identify children with high risks of cUTI recurrence for targeted interventions.

Publisher

Springer Science and Business Media LLC

Reference34 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3