Rapid Direct Identification of Microbial Pathogens and Antimicrobial Resistance Genes in Positive Blood Cultures Using a Fully Automated Multiplex PCR Assay.
Keun Ju KimSeung Gyu YunYunjung ChoChang Kyu LeeMyung-Hyun NamPublished in: Journal of Korean medical science (2024)
This study assessed the performance of the BioFire Blood Culture Identification 2 (BCID2) panel in identifying microorganisms and antimicrobial resistance (AMR) profiles in positive blood cultures (BCs) and its influence on turnaround time (TAT) compared with conventional culture methods. We obtained 117 positive BCs, of these, 102 (87.2%) were correctly identified using BCID2. The discordance was due to off-panel pathogens detected by culture (n = 13), and additional pathogens identified by BCID2 (n = 2). On-panel pathogen concordance between the conventional culture and BCID2 methods was 98.1% (102/104). The conventional method detected 19 carbapenemase-producing organisms, 14 extended-spectrum beta-lactamase-producing Enterobacterales, 18 methicillin-resistant Staphylococcus spp., and four vancomycin-resistant Enterococcus faecium . BCID2 correctly predicted 53 (96.4%) of 55 phenotypic resistance patterns by detecting AMR genes. The TAT for BCID2 was significantly lower than that for the conventional method. BCID2 rapidly identifies pathogens and AMR genes in positive BCs.
Keyphrases
- antimicrobial resistance
- bioinformatics analysis
- genome wide
- gram negative
- staphylococcus aureus
- methicillin resistant staphylococcus aureus
- biofilm formation
- genome wide identification
- dna methylation
- deep learning
- microbial community
- multidrug resistant
- pseudomonas aeruginosa
- genome wide analysis
- klebsiella pneumoniae