AI Article Synopsis

  • Antimicrobial resistance (AMR) surveillance in veterinary mycoplasmas has faced challenges due to inconsistent testing methods and a lack of data, prompting the establishment of the "Vigimyc" clinical surveillance network.
  • Over a 2-year monitoring period, Vigimyc collected and analyzed mycoplasma samples, revealing stable prevalence patterns and providing a foundation for yearly antimicrobial susceptibility testing (AST).
  • The study resulted in findings that partly aligned with existing reference datasets, identified new AMR patterns, and proposed tentative epidemiological cut-off values (TECOFFs) for specific mycoplasma species and antimicrobials, aiming to improve monitoring efforts.

Article Abstract

Antimicrobial resistance (AMR) surveillance of mycoplasmas of veterinary importance has been held back for years due to lack of harmonized methods for antimicrobial susceptibility testing (AST) and interpretative criteria, resulting in a crucial shortage of data. To address AMR in ruminant mycoplasmas, we mobilized a long-established clinical surveillance network called "Vigimyc." Here we describe our surveillance strategy and detail the results obtained during a 2-year monitoring period. We also assess how far our system complies with current guidelines on AMR surveillance and how it could serve to build epidemiological cut-off values (ECOFFs), as a first attainable criterion to help harmonize monitoring efforts and move forward to clinical breakpoints. Clinical surveillance through Vigimyc enables continuous collection, identification and preservation of spp. isolates along with metadata. The most frequent pathogens, i.e., and species belonging to group, show stable clinicoepidemiological trends and were included for annual AST. In the absence of interpretative criteria for ruminant mycoplasmas, we compared yearly minimum inhibitory concentration (MIC) results against reference datasets. We also ran a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis on the overall service provided by our AMR surveillance strategy. Results of the 2018-2019 surveillance campaign were consistent with the reference datasets, with isolates showing high MIC values for all antimicrobial classes except fluoroquinolones, and species of the group showing predominantly low MIC values. A few new AMR patterns were detected, such as with lower spectinomycin MICs. Our reference dataset partially complied with European Committee on Antimicrobial Susceptibility Testing (EUCAST) requirements, and we were able to propose tentative epidemiological cut-off values (TECOFFs) for with tilmicosin and spectinomycin and for group with tilmicosin and lincomycin. These TECOFFs were consistent with other published data and the clinical breakpoints of , which are often used as surrogates for mycoplasmas. SWOT analysis highlighted the benefit of pairing clinical and antimicrobial resistance surveillance despite the AST method-related gaps that remain. The international community should now direct efforts toward AST method harmonization and clinical interpretation.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236625PMC
http://dx.doi.org/10.3389/fvets.2021.667175DOI Listing

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