2000
DOI: 10.1128/jcm.38.2.570-574.2000
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Ability of the VITEK 2 Advanced Expert System To Identify β-Lactam Phenotypes in Isolates of Enterobacteriaceae and Pseudomonas aeruginosa

Abstract: The Advanced Expert System (AES) was used in conjunction with the VITEK 2 automated antimicrobial susceptibility test system to ascertain the β-lactam phenotypes of 196 isolates of the familyEnterobacteriaceae and the species Pseudomonas aeruginosa. These isolates represented a panel of strains that had been collected from laboratories worldwide and whose β-lactam phenotypes had been characterized by biochemical and molecular techniques. The antimicrobial susceptibility of each isolate was determined with the … Show more

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Cited by 64 publications
(15 citation statements)
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“…Enterobacterales were categorised as ESBL-PE according to the Vitek 21 Advanced Expert System (AES) interpretation of the AST GN-N255 card. This categorisation is based solely on the pattern of susceptibility and resistance to different cephalosporins as the card lacks wells containing cephalosporins combined with a beta-lactamase inhibitor [48].…”
Section: Plos Onementioning
confidence: 99%
“…Enterobacterales were categorised as ESBL-PE according to the Vitek 21 Advanced Expert System (AES) interpretation of the AST GN-N255 card. This categorisation is based solely on the pattern of susceptibility and resistance to different cephalosporins as the card lacks wells containing cephalosporins combined with a beta-lactamase inhibitor [48].…”
Section: Plos Onementioning
confidence: 99%
“…Several automated systems are available for the identification and susceptibility testing of the most clinically important bacteria (Stager & Davis, 1992). These systems are able to decrease the in-laboratory turnaround time required for standardized methods and to provide physicians with susceptibility profiles to help them select the most appropriate antimicrobial therapy (Felmingham & Brown, 2001;Sanders et al, 2000). The reporting errors by any test systems can have serious implications for the clinical outcome for patients (Micek et al, 2005).…”
Section: Introductionmentioning
confidence: 99%
“…The software then compares the input to the knowledge database by using the inference engine, and the system then outputs the appropriate susceptible, intermediate, or resistant (SIR) interpretation. Expert systems can also be used to infer the mechanism of antimicrobial resistance by comparing a clinical isolate's MIC values to a curated database of strains which have had their MIC values and mechanism(s) of resistance characterized (45). In addition to having the antimicrobial breakpoints in its database, the expert system also has rules which check to see if some drug results need to be reported as resistant even though the organism might test as sensitive.…”
Section: Utility Of Expert Systems In Antimicrobial Susceptibility Tementioning
confidence: 99%