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Predictors of agr dysfunction in methicillin-resistant Staphylococcus aureus (MRSA) isolates among patients with MRSA bloodstream infections
Authors:Butterfield Jill M  Tsuji Brian T  Brown Jack  Ashley Elizabeth Dodds  Hardy Dwight  Brown Kristen  Forrest Alan  Lodise Thomas P
Affiliation:Albany College of Pharmacy and Health Sciences, Albany, New York 12208, USA.
Abstract:Despite emerging evidence that dysfunction in the accessory gene regulator (agr) locus is associated with deleterious outcomes among patients treated with vancomycin for methicillin-resistant Staphylococcus aureus (MRSA) infections, factors predictive of agr dysfunction have not been evaluated. This study describes the epidemiology of agr dysfunction, identifies predictors of agr dysfunction in MRSA isolates among those with MRSA bloodstream infections, and describes the relationship between agr dysfunction and other microbiologic phenotypes. A cross-sectional study of patients with MRSA bloodstream infections at two institutions in upstate New York was performed. Clinical data on demographics, comorbidities, disease severity, hospitalization history, and antibiotic history were collected. Microbiologic phenotypes, including agr dysfunction, MIC values by broth microdilution (BMD) and Etest, and vancomycin heteroresistance (hVISA) were tested. Multivariable analyses were performed to identify factors predictive of agr dysfunction. Among 200 patients with an MRSA bloodstream infection, the proportion of strains with agr dysfunction was 31.5%. The distribution of MICs determined by both BMD and Etest were equivalent across agr groups, and there was no association between agr dysfunction and the presence of hVISA. Severity of illness, comorbidities, and hospitalization history were comparable between agr groups. In the multivariate analysis, prior antibiotic exposure was the only factor of variables studied found to be predictive of agr dysfunction. This relationship was predominantly driven by prior beta-lactam and fluoroquinolone administration in the bivariate analysis. Identifying these institution-specific risk factors can be used to develop a process to assess the risk of agr dysfunction and guide empirical antibiotic therapy decisions.
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