Evaluation of the VITEK 2 Advanced Expert System performance for predicting resistance mechanisms in Enterobacterales acquired from a hospital-based screening program.


Journal

Pathology
ISSN: 1465-3931
Titre abrégé: Pathology
Pays: England
ID NLM: 0175411

Informations de publication

Date de publication:
Oct 2021
Historique:
received: 16 04 2020
revised: 31 12 2020
accepted: 11 01 2021
pubmed: 8 5 2021
medline: 1 2 2022
entrez: 7 5 2021
Statut: ppublish

Résumé

There is limited literature examining the accuracy of the VITEK 2 Advanced Expert System (AES) in characterisation of β-lactamase resistance patterns. We present a prospective single centre study to better ascertain the performance characteristics of this program. The VITEK 2 AES interpretation was compared to established laboratory phenotypic methods. The overall sensitivity for detection of broad-spectrum β-lactamase by the AES was 95%, with a specificity of 78%. One or more discrepancies were noted in 36% of samples, with the majority of these (87/100) due to incorrect 'overcall' of a resistance mechanism. AES characterisation of AmpC resistance mechanisms was excellent. In contrast, the AES had poor specificity in classifying extended spectrum β-lactamases (ESBLs). As a screening aid, the AES can be a valuable tool. However, optimal use requires an adequate working knowledge of resistance mechanisms in order to correctly interpret and accept the result output.

Identifiants

pubmed: 33958177
pii: S0031-3025(21)00092-1
doi: 10.1016/j.pathol.2021.01.009
pii:
doi:

Substances chimiques

Anti-Bacterial Agents 0
Bacterial Proteins 0
beta-Lactamases EC 3.5.2.6

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

763-767

Informations de copyright

Copyright © 2021 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.

Auteurs

Eddie Chan (E)

Department of Microbiology, Austin Health, Heidelberg, Vic, Australia; Department of Infectious Diseases, Austin Health, Heidelberg, Vic, Australia. Electronic address: eddie.chan@svha.org.au.

Marcel Leroi (M)

Department of Microbiology, Austin Health, Heidelberg, Vic, Australia; Department of Infectious Diseases, Austin Health, Heidelberg, Vic, Australia.

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Classifications MeSH