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Updated: Jun 4, 2026

Biosensor for Detection of Antibiotic Resistant Staphylococcus Bacteria
Published on: May 8, 2013
Performance of various testing methodologies for detection of heteroresistant vancomycin-intermediate Staphylococcus
Sebastian J van Hal1, Michael C Wehrhahn, Thelma Barbagiannakos
1Department of Microbiology & Infectious Diseases, Liverpool Hospital, Locked Bag 7090, Liverpool BC, NSW 1871, Australia. Sebastian.vanHal@sswahs.nsw.gov.au
Abstract:
The best screening method for detecting heteroresistant vancomycin-intermediate Staphylococcus aureus (hVISA) remains unclear. Using population analysis profiling utilizing the area under the concentration-time curve (PAP-AUC) as the gold standard, we screened 458 consecutive methicillin-resistant S. aureus (MRSA) bloodstream isolates to determine the most accurate and cost-effective testing strategy to detect the presence of heteroresistance. All isolates were also tested using the macromethod Etest (MET) and glycopeptide resistance detection (GRD) Etest. The MIC was determined by several methods, including standard vancomycin Etest, vancomycin broth microdilution (BMD), and Vitek2 testing. Fifty-five (12%) hVISA and 4 (1%) VISA isolates were detected by PAP-AUC. Compared to PAP-AUC, the sensitivities and specificities of MET, GRD Etest, BMD (using a MIC cutoff of ≥ 2 mg/liter), and standard vancomycin Etest (using a MIC cutoff of ≥ 2 mg/liter) were 89 and 55%, 71 and 94%, 82 and 97%, and 71 and 94%, respectively. Combination testing increased the overall testing accuracy by reducing the number of false-positive results. Cost was determined predominately by the number of PAP-AUC runs required following a screening assay. The most cost-effective strategy was BMD (using a MIC cutoff of ≥ 2 μg/ml) as a standalone assay or in combination with PAP-AUC, provided that BMD testing was batched. GRD Etest remained an alternative, with 71% of hVISA isolates detected. Prevalence influenced both cost and test accuracy, with results remaining unchanged for hVISA prevalences of up to 25%. Implementation of any testing strategy would therefore be dependent on balancing cost with accuracy in a given population and clinical context.
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