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• W2909953670 abstract "Antimicrobial resistance (AMR) threatens the prevention and treatment of infections caused by a large range of microorganisms. Leishmania is not an exception and treatment failure due to drug-resistant organisms is increasingly reported. Currently, no molecular methods and marker are validated to track drug-resistant organism and antimicrobial susceptibility tests are roughly not amenable to a clinical setting. Taking these facts into account, it is essential to reflect on ways to translate basic knowledge into methodologies aimed to diagnose leishmania drug resistance. As a matter of fact, a meta-analysis of the literature discloses the reliability of the promastigotes antimicrobial susceptibility tests (AST) to predict intracellular amastigotes susceptibility status. Promastigote cultures that are easy to perform, typically inexpensive and amenable to standardization should represent a candidate to diagnose resistance. Using AST performed on promastigote, we propose a way to improve leishmania drug resistance diagnosis in the framework of guidance and guideline of the bacterial drug resistance diagnosis. In this review, we highlight challenges that remained and discuss the definition of clinical breakpoints, including the epidemiological cutoff (ECOFF), to track drug-resistant isolates. Our analysis paves the ways to standardize and analyze anti-leishmania susceptibility tests output in order to guide the characterization of drug-resistant isolates, the clinical decision during treatment and the search for new molecular markers." @default.
• W2909953670 created "2019-01-25" @default.
• W2909953670 creator A5050209651 @default.
• W2909953670 creator A5054283969 @default.
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• W2909953670 date "2019-03-01" @default.
• W2909953670 modified "2023-10-14" @default.
• W2909953670 title "Meta-analysis and discussion on challenges to translate Leishmania drug resistance phenotyping into the clinic" @default.
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• W2909953670 doi "https://doi.org/10.1016/j.actatropica.2019.01.009" @default.
• W2909953670 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30639471" @default.
• W2909953670 hasPublicationYear "2019" @default.
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