Analysis of multidrug resistance in Staphylococcus aureus with a machine learning generated antibiogram.

Analysis of multidrug resistance in Staphylococcus aureus with a machine learning generated antibiogram. Antimicrob Agents Chemother. 2021 Jan 11;: Authors: Cazer CL, Westblade LF, Simon MS, Magleby R, Castanheira M, Booth JG, Jenkins SG, Gröhn YT Abstract Multidrug resistance (MDR) surveillance consists of reporting MDR prevalence and MDR phenotypes. Detailed knowledge of the specific associations underlying MDR patterns can allow antimicrobial stewardship programs to accurately identify clinically relevant resistance patterns. We applied machine learning and graphical networks to quantify and visualize associations between resistance traits in a set of 1,091 Staphylococcus aureus isolates collected from one New York hospital between 2008 and 2018. Antimicrobial susceptibility testing was performed using reference broth microdilution. The isolates were analyzed by year, methicillin susceptibility, and infection site. Association mining was used to identify resistance patterns that consisted of two or more individual antimicrobial resistance (AMR) traits and quantify the association among the individual resistance traits in each pattern. The resistance patterns captured the majority of the most common MDR phenotypes and reflected previously identified pairwise relationships between AMR traits in S. aureus Associations between β-lactams and other antimicrobial classes (macrolides, lincosamides, and fluoroquinolones) were common, alt...
Source: Antimicrobial Agents and Chemotherapy - Category: Microbiology Authors: Tags: Antimicrob Agents Chemother Source Type: research