JOURNAL ARTICLE
Advances in the clinical treatment of multidrug-resistant pathogens using polymyxins.
Published In: Journal of Antimicrobial Chemotherapy (JAC), 2024, v. 79, n. 12. P. 3210 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Huang, Yizhen; Liao, Mingrui; Hu, Xuzhi; Hu, Honghua; Gong, Haoning 3 of 3
Abstract
This article focuses on the properties, clinical applications, and recent advances in polymyxins, a class of antibiotics used as last-line therapy against carbapenem-resistant Gram-negative bacteria (CR-GNB). Polymyxins, primarily polymyxin B and polymyxin E (colistin), act by disrupting the lipopolysaccharide (LPS) structure of Gram-negative bacterial outer membranes, leading to bacterial death, but their clinical use is limited by nephrotoxicity. Various formulations and administration routes—including intravenous infusion, inhalation, and topical ointments—have demonstrated efficacy against CR-GNB infections, with polymyxin B preferred for bloodstream infections and colistimethate sodium (CMS) for urinary tract infections. Although combination therapies and novel delivery systems such as nanomedicine and microneedles are under investigation to improve efficacy and reduce toxicity, current clinical evidence shows mixed results regarding improved outcomes. Future research aims to optimize polymyxin pharmacokinetics/pharmacodynamics, minimize nephrotoxicity, and develop advanced formulations to enhance treatment of multidrug-resistant Gram-negative infections.
Additional Information
- Source:Journal of Antimicrobial Chemotherapy (JAC). 2024/12, Vol. 79, Issue 12, p3210
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2024
- ISSN:0305-7453
- DOI:10.1093/jac/dkae344
- Accession Number:181249513
- 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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