Artificial Intelligence Can Guide Antibiotic Choice in Recurrent UTIs and Become an Important Aid to Improve Antimicrobial Stewardship

人工智能可指导复发性尿路感染的抗生素选择,并成为改善抗菌药物管理的重要辅助手段

阅读:8
作者:Tommaso Cai, Umberto Anceschi, Francesco Prata, Lucia Collini, Anna Brugnolli, Serena Migno, Michele Rizzo, Giovanni Liguori, Luca Gallelli, Florian M E Wagenlehner, Truls E Bjerklund Johansen, Luca Montanari, Alessandro Palmieri, Carlo Tascini3

Background

A correct approach to recurrent urinary tract infections (rUTIs) is an important pillar of antimicrobial stewardship. We

Conclusions

ANNs seem to be an interesting tool to guide the antimicrobial choice in the management of rUTIs at the point of care.

Methods

We extracted clinical and microbiological data from 1043 women. We trained an ANN on 725 patients and validated it on 318.

Results

The ANN showed a sensitivity of 87.8% and specificity of 97.3% in predicting the clinical efficacy of empirical therapy. The previous use of fluoroquinolones (HR = 4.23; p = 0.008) and cephalosporins (HR = 2.81; p = 0.003) as well as the presence of Escherichia coli with resistance against cotrimoxazole (HR = 3.54; p = 0.001) have been identified as the most important variables affecting the ANN output decision predicting the fluoroquinolones-based therapy failure. A previous isolation of Escherichia coli with resistance against fosfomycin (HR = 2.67; p = 0.001) and amoxicillin-clavulanic acid (HR = 1.94; p = 0.001) seems to be the most influential variable affecting the output decision predicting the cephalosporins- and cotrimoxazole-based therapy failure. The previously mentioned Escherichia coli with resistance against cotrimoxazole (HR = 2.35; p < 0.001) and amoxicillin-clavulanic acid (HR = 3.41; p = 0.007) seems to be the most influential variable affecting the output decision predicting the fosfomycin-based therapy failure. Conclusions: ANNs seem to be an interesting tool to guide the antimicrobial choice in the management of rUTIs at the point of care.

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。