Rapid Screening of Methicillin-Resistant <i>Staphylococcus aureus</i> Using MALDI-TOF MS and Machine Learning: A Randomized, Multicenter Study.

ABSTRACT: Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of healthcare-associated infections including bacteremia. The rapid detection of MRSA is essential for prompt treatment and improved outcomes. However, traditional MRSA screening and confirmatory tests based on bacterial cultures with antimicrobial susceptibility tests and/or molecular diagnostics are time-consuming (>2 days), labor-intensive, and costly. We report that AMRQuest software, which was developed using logistic regression-based machine learning and matrix-assisted laser desorption/ionization-time-of-flight spectra of S. aureus isolates, can be successfully implemented in clinical microbiology laboratories to screen MRSA and identify bacterial species simultaneously, with the cefoxitin disk diffusi

SUBMITTER: Yong D 

PROVIDER: S-EPMC12311893 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature