Objective: This study evaluated the capability of a MALDI Biotyper system equipped with the newly introduced MBT STAR-BL module to simultaneously perform species identification and β-lactamase-mediated resistance detection in bacteremia -causing bacteria isolated from cultured isolates and patient-derived blood cultures (BCs). Methods: Two hundred retrospective cultured isolates and 153 prospective BCs containing Gram-negative rods (GNR) were collected and subjected to direct bacterial identification, followed by the measurement of β-lactamase activities against ampicillin, piperacillin, cefotaxime, ceftazidime and meropenem using the MBT STAR-BL module. The results and turnaround times were compared with those of routine microbiological processing. All strains were also characterized by beta-lactamase PCR and sequencing. Results: Using the saponin-based extraction method, MALDI-TOF MS correctly identified bacteria in 116/134 (86.6%) monomicrobial BCs. The detection sensitivities for β-lactamase activities against ampicillin, piperacillin, third-generation cephalosporin and meropenem were 91.3%, 100%, 97.9% and 100% for cultured isolates, and 80.4%, 100%, 68.8% and 40% for monomicrobial BCs (n=134) respectively. The overall specificities ranged from 91.5% to 100%. Furthermore, the MBT STAR-BL and conventional drug susceptibility test results were concordant in 14/19 (73.7%) polymicrobial cultures. Reducing the logRQ cut-off value from 0.4 to 0.2 increased the direct detection sensitivities for β-lactamase activities against ampicillin, cefotaxime and meropenem in BCs to 85.7%, 87.5% and 100% respectively. The MBT STAR-BL test enabled the reporting of β-lactamase-producing GNR at 14.16 and 47.64 h before the interim and final reports of routine BCs processing, respectively, were available. Conclusion: The MALDI Biotyper system equipped with the MBT STAR-BL module enables the simultaneous rapid identification of bacterial species and β-lactamase-mediated resistance from BCs and cultured isolates. Adjustment of the logRQ cut-off value to 0.2 significantly increased the detection sensitivities for clinically important drug-resistant pathogens.
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Lee et al. (2018) studied this question.
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