Increased mortality with accessory gene regulator (agr) dysfunction in Staphylococcus aureus among bacteremic patients.

Schweizer ML, Furuno JP, Sakoulas G, Johnson JK, Harris AD, Shardell MD, McGregor JC, Thom KA, Perencevich EN. Increased mortality with accessory gene regulator (agr) dysfunction in Staphylococcus aureus among bacteremic patients. Antimicrobial agents and chemotherapy. 2011 Mar 1; 55(3):1082-7.

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Abstract:

Accessory gene regulator (agr) dysfunction in Staphylococcus aureus has been associated with a longer duration of bacteremia. We aimed to assess the independent association between agr dysfunction in S. aureus bacteremia and 30-day in-hospital mortality. This retrospective cohort study included all adult inpatients with S. aureus bacteremia admitted between 1 January 2003 and 30 June 2007. Severity of illness prior to culture collection was measured using the modified acute physiology score (APS). agr dysfunction in S. aureus was identified semiquantitatively by using a -hemolysin production assay. Cox proportional hazard models were used to measure the association between agr dysfunction and 30-day in-hospital mortality, statistically adjusting for patient and pathogen characteristics. Among 814 patient admissions complicated by S. aureus bacteremia, 181 (22%) patients were infected with S. aureus isolates with agr dysfunction. Overall, 18% of patients with agr dysfunction in S. aureus died, compared to 12% of those with functional agr in S. aureus (P = 0.03). There was a trend toward higher mortality among patients with S. aureus with agr dysfunction (adjusted hazard ratio [HR], 1.34; 95% confidence interval [CI], 0.87 to 2.06). Among patients with the highest APS (scores of > 28), agr dysfunction in S. aureus was significantly associated with mortality (adjusted HR, 1.82; 95% CI, 1.03 to 3.21). This is the first study to demonstrate an independent association between agr dysfunction and mortality among severely ill patients. The -hemolysin assay examining agr function may be a simple and inexpensive approach to predicting patient outcomes and potentially optimizing antibiotic therapy.