Risk factors and nomogram for predicting urinary tract infection in patients with ureterolithiasis complicated with hydronephrosis.

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-09-30 Epub Date: 2024-09-26 DOI:10.21037/tau-24-217
Qiao Qi, Yongtao Hu, Bingbing Hou, Kaiguo Xia, Yuexian Xu, Chaozhao Liang, Zongyao Hao
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Abstract

Background: Urinary tract infection (UTI) is a common disease in urology and often occurs in patients with urolithiasis. This study aimed to identify the risk factors for UTI in patients with ureterolithiasis complicated with hydronephrosis, and to construct a simple and practical nomogram to predict the incidence of UTI for patients.

Methods: A total of 383 patients were enrolled from September 2019 to June 2022. The results from univariate and multivariate logistic regression showed the risk factors for predicting UTI and a prediction model was constructed. Subsequently, the differentiation, calibration, and clinical applicability of the model were estimated by receiver operating characteristic (ROC) curve analysis, calibration curve, and decision curve analysis (DCA), respectively.

Results: The study included 72 (18.80%) patients with UTI. Multivariate logistic regression showed that tissue rim sign (P=0.04), positive urinary nitrite (P<0.001), and positive urinary leukocyte esterase (P=0.005) were independent predictive indexes of UTI for patients with ureterolithiasis complicated with hydronephrosis, and a nomogram was constructed in accordance with these indicators. The area under the ROC curve was 0.773, which indicated good prediction ability. The Hosmer-Lemeshow test (P=0.97) indicated that the model fitted well. The calibration curve and DCA showed good consistency and clinical applicability, respectively.

Conclusions: The prediction model constructed with the risk factors including tissue rim sign, positive urinary nitrite, and positive urinary leukocyte esterase can better detect patients with UTI early and take timely intervention measures.

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预测输尿管结石并发肾积水患者尿路感染的风险因素和提名图。
背景:尿路感染(UTI)是泌尿外科的常见疾病,通常发生在输尿管结石患者身上。本研究旨在确定输尿管结石并发肾积水患者发生UTI的风险因素,并构建一个简单实用的提名图来预测患者的UTI发生率:方法:从2019年9月至2022年6月,共纳入383例患者。单变量和多变量逻辑回归结果显示了预测 UTI 的风险因素,并构建了预测模型。随后,分别通过接收者操作特征曲线(ROC)分析、校准曲线和决策曲线分析(DCA)估算了模型的区分度、校准度和临床适用性:研究共纳入 72 例(18.80%)UTI 患者。多变量逻辑回归显示,组织边缘征(P=0.04)、尿亚硝酸盐阳性(PConclusions:利用组织边缘征、尿亚硝酸盐阳性和尿白细胞酯酶阳性等危险因素构建的预测模型能更好地早期发现尿毒症患者,并及时采取干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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