JOURNAL ARTICLE

Assessment of co-resistance to antibiotics recommended for acute pyelonephritis among Escherichia coli clinical strains from community- and nursing home–acquired urinary tract infections.

  • Published In: Journal of Antimicrobial Chemotherapy (JAC), 2025, v. 80, n. 2. P. 472 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Leroy, Anne-Gaëlle; Lemenand, Olivier; Thibaut, Sonia; Coeffic, Thomas; Chauveau, Marie; Lesprit, Philippe; Caillon, Jocelyne; Boutoille, David; Birgand, Gabriel; Network, French Clinical Laboratories Nationwide 3 of 3

Abstract

This study focused on assessing co-resistance patterns to antibiotics recommended for acute pyelonephritis among Escherichia coli strains isolated from urinary tract infections (UTIs) in females living in community and nursing home (NH) settings in France during 2020. Analysis of 302,707 isolates revealed that over 99% of community-acquired and 98% of NH-acquired E. coli strains remained susceptible to at least one oral alternative to fluoroquinolones (FQs), despite varying rates of resistance to amoxicillin and other antibiotics. Resistance and co-resistance rates were higher among females aged 65 and older and those residing in nursing homes. The findings suggest that oral alternatives to FQs are generally available for treating acute pyelonephritis caused by E. coli, supporting antimicrobial stewardship efforts to limit FQ use and reduce associated adverse effects and ecological impacts.

Additional Information

  • Source:Journal of Antimicrobial Chemotherapy (JAC). 2025/02, Vol. 80, Issue 2, p472
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:0305-7453
  • DOI:10.1093/jac/dkae431
  • Accession Number:182905816
  • Copyright Statement:Copyright of Journal of Antimicrobial Chemotherapy (JAC) is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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