Prediction of ESBL-producing E coli for suspected urinary tract infection

Author:

Higuchi Hiroshi1,Nakamura Tsukasa23,Mashino Junji34,Imada Toshihiro5,Morimoto Takeshi36ORCID

Affiliation:

1. Department of Emergency Medicine, Shimane Prefectural Central Hospital, Izumo, Japan

2. Department of Infectious Diseases, Shimane Prefectural Central Hospital, Izumo, Japan

3. Clinical Education and Research Center, Shimane Prefectural Central Hospital, Izumo, Japan

4. Department of Community Medicine, Shimane Prefectural Central Hospital, Izumo, Japan

5. Department of General Medicine, Shimane Prefectural Central Hospital, Izumo, Japan

6. Department of Clinical Epidemiology, Hyogo College of Medicine, Nishinomiya, Japan

Abstract

Aim: The widespread existence of extended-spectrum β-lactamase (ESBL) producing Escherichia coli ( E. coli) has become a critical threat in developed countries. Prediction rule for ESBL producing E. coli is relevant to see patients with suspected urinary tract infection. Materials and methods: We collected clinical and laboratory data and constructed multivariate logistic regression models to develop a clinical prediction rule in the derivation cohort with 1185 patients with urine cultures and validated the rule in the validation cohort with 516 patients. Results: ESBL-producing E. coli was found in 185 patients (16%) in the derivation cohort. When assigning 14 points for being female (odds ratio (OR): 4.2), six points for CRP >5 mg/dl (OR: 1.87), and four points for a history of urinary tract infection (OR: 1.52), the area under the curve (AUC) had 0.67 (95% confidence interval (CI): 0.63–0.70) in the derivation cohort and 0.64 (95% CI: 0.59–0.69] in the validation cohort. Conclusions: The developed prediction rule had moderate accuracy to predict ESBL-producing E. coli in patients with suspected urinary tract infection.

Publisher

SAGE Publications

Subject

General Medicine

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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