S-611 Can we clinically predict methicillin-resistance in community-onset Staphylococcus aureus infection? = S-611 Can we clinically predict methicillin-resistance in community-onset Staphylococcus aureus infection?

다국어 초록 (Multilingual Abstract)

Background: Increasing methicillin-resistance among the community-onset Staphylococcus aureus infection is growing concern. We tried to identify demographic and clinical risk factors for methicillin-resistance in community-onset S. aureus bacteremia (CO-SAB) and developed a clinical risk score system. Methods: We reviewed the medical records of three multicenter, prospective cohort studies: the cohort from July, 2009 to June, 2011 at 9 hospitals, from May to December, 2012 at 16 hospitals, and from September, 2013 to March, 2015 at 13 hospitals. Using these data, we developed a risk score system. Point allocation in the methicillin-resistance was based on beta-coefficient in the final regression model. Results: We gathered a total of 1,802 cases of CO-SAB, 752 (41.7%) of which were methicillin-resistant S. aureus (MRSA) infections. MRSA bacteremia cases were significantly older, and more likely to have a history of MRSA infection or colonization within six months [Odds ratio(OR), 4.456; 95% confidence interval(CI), 2.974-6.677; 1.5 point], hospitalization or surgery (OR 2.050; 95% CI 1.640-2.563; 0.5 point), residence in a long term care facility (OR 1.679; 95% CI 1.297-2.173; 0.5 point) and dialysis (OR 1.475; 95% CI 1.075-2.024; 0.5 point) within the past year. On the other hand, they were less likely to have hematologic disease (OR 0.445; 95% CI 0.234-0.847; -1 point) and skin and soft tissue infection (OR 0.570; 95% CI 0.410-0.793; -0.5 point), bone and joint infection (OR 0.650; 95% CI 0.481-0.878; -0.5 point), or endovascular infection (OR 0.456; 95% CI 0.263-0.790; -1 point) as a primary site of infection. The area under the curve (AUC) was 0.684 and cut-off value was 0.75. The sensitivity, specificity, positive predictive value and negative predictive value were 0.543, 0.751, 0.610 and 0.696, respectively. Conclusions: We developed a clinical risk score system to predict methicillin-resistance in CO-SAB in this study. However, it was not possible to make a distinguishable system only based on demographic and clinical factors in spite of a large scale of cases. Other tools such as rapid microorganism identification technology will be necessary for early adequate antibiotic therapy in CO-SAB.