Prediction Score for Identification of ESBL Producers in Urinary Infections Overestimates Risk in High-ESBL-Prevalence Setting

在ESBL高流行地区,用于识别尿路感染中ESBL产生菌的预测评分会高估风险。

阅读:2

Abstract

Background/Objectives: Urinary tract infections (UTIs) caused by extended-spectrum beta-lactamase (ESBL) Enterobacterales have become more frequent. Therefore, strategies for assessing the risks posed by ESBL-producing infections have been developed, creating the need for local validation. The aim of this study was to validate the scoring system designed by Tumbarello et al. to identify ESBL producers in patients with a UTI that require hospital care in a region with a high prevalence of ESBL Escherichia coli. Methods: A retrospective cohort study was conducted in a third-level hospital in Bogotá (Colombia) between 2013 and 2020.The study included 817 patients, who were hospitalized due to pyelonephritis and treated with cefuroxime (the first-line antibiotic according to local guidelines), with an ESBL frequency of 9.68%. Diagnostic performances were estimated for a modified version of Tumbarello's score (omitting admission from another healthcare facility) evaluating the area under the curve (AUC) for ESBL presence with respect to resistance to second- and third-generation cephalosporins. Results: With an index cut-off of ≥6, the score showed a sensitivity of 18% and a specificity of 83%. The AUC for this cut-off was 0.47. This threshold index could not efficiently predict either third- (AUC = 0.49) or second-generation cephalosporin resistance (AUC = 0.51). Conclusions: In Colombia, a region with a high prevalence of ESBL E. coli producers, as the use of the Tumbarello index would result in excessive utilization of wide-spectrum antibiotics, it is not recommended in this specific scenario for UTIs. Further studies are required in order to develop accurate tools to assess the risk of ESBL producers in high-prevalence settings.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。