Performance of automated antimicrobial susceptibility testing for the detection of antimicrobial resistance in gram‐negative bacteria: a NordicAST study

Author:

Leegaard Truls M.12ORCID,Justesen Ulrik S.3ORCID,Matuschek Erika4ORCID,Giske Christian G.5ORCID,

Affiliation:

1. Department of Microbiology and Infection Control Akershus University Hospital Lørenskog Norway

2. Division of Medicine and Laboratory Sciences University of Oslo Oslo Norway

3. Department of Clinical Microbiology Odense University Hospital Odense Denmark

4. EUCAST Development Laboratory Växjö Sweden

5. Department of Clinical Microbiology MTC ‐ Karolinska Institutet, Karolinska University Hospital Stockholm Sweden

Abstract

Automated testing of antimicrobial susceptibility is common in clinical microbiology laboratories but their ability to detect low‐level resistance has been questioned. This Nordic multicentre study aimed to evaluate the performance of commercially available automated AST systems. A phenotypically well‐characterised collection of gram‐negative bacilli (Escherichia coli (n = 7), Klebsiella pneumoniae (n = 6) and Pseudomonas aeruginosa (n = 7)) with and without resistance mechanisms was examined by Danish (n = 1), Finnish (n = 6), Norwegian (n = 16) and Swedish (n = 5) laboratories. Minimum inhibitory concentrations (MICs) were determined for 12 antimicrobials with automated systems and compared with MICs obtained with gold standard broth microdilution. The automated systems used were VITEK 2 (n = 23), Phoenix (n = 4), MicroScan (n = 1), and ARIS (n = 1). Very major errors were identified for six antimicrobials; cefotaxime (6.9%), meropenem (0.4%), ciprofloxacin (0.7%), ertapenem (4.3%), amikacin (3.4%) and colistin (6.4%). Categorical agreement of MIC for the automated systems compared to broth microdilution ranged from 83% for imipenem to 100% for ampicillin and trimethoprim‐sulfamethoxazole. The analysis revealed several important antimicrobials where resistance was underestimated, potentially with significant consequences in patient treatment. The results cast doubt on the use of automated AST in the management of patients with serious infections and suggests that more work is needed to define their limitations.

Publisher

Wiley

Subject

Microbiology (medical),General Medicine,Immunology and Allergy,Pathology and Forensic Medicine

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