Data_Sheet_1_Employing MIC Data for Mink Pathogens to Propose Tentative Epidemiological Cut-Off Values: A Step Toward Rationalizing Antimicrobial Use .PDF (543.6 kB)
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Data_Sheet_1_Employing MIC Data for Mink Pathogens to Propose Tentative Epidemiological Cut-Off Values: A Step Toward Rationalizing Antimicrobial Use in Mink.PDF

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posted on 21.10.2020, 04:09 by Nanett Kvist Nikolaisen, Amir Atabak Ronaghinia, Desiree Corvera Kløve Lassen, Chaza Nazih Chehabi, Mikkel Lindegaard, Tina Struve, Mariann Chriél, Peter Damborg, Gunnar Kahlmeter, Lars Bogø Jensen, Karl Pedersen

Optimizing antimicrobial dosage regimens and development of breakpoints for antimicrobial susceptibility testing are important prerequisites for rational antimicrobial use. The objectives of the study were (1) to produce MIC data for four mink pathogens and (2) to employ these MIC data to support the development of tentative epidemiological cut-off values (TECOFFs), which may be used for future development of mink-specific antimicrobial dosages and breakpoints. Broth microdilution was used to establish MIC distributions for 322 mink bacterial isolates of clinical origin from six European mink-producing countries. The included species were E. coli (n = 162), S. delphini (n = 63), S. canis (n = 42), and P. aeruginosa (n = 55). Sixty-four E. coli isolates and 34 S. delphini isolates were whole-genome sequenced and analyzed for antimicrobial resistance genes. No EUCAST MIC data are available on S. delphini and S. canis, hence tentative ECOFFs were suggested for the majority of the tested antimicrobials. For E. coli and P. aeruginosa, the wildtype distributions were in accordance with EUCAST data. Overall, the genotypes of the sequenced isolates were in concordance with the phenotypes. These data constitute an important piece in the puzzle of developing antimicrobial dosages and clinical breakpoints for mink. Until pharmacokinetic and clinical data become available, the (tentative) ECOFFs can be used for monitoring resistance development and as surrogates for clinical breakpoints.

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