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Multiple Site Surveillance Cultures as a Predictor of Methicillin-Resistant Staphylococcus aureus Infections
Benedict Lim Heng Sim MBBS MRCP, Emma McBryde MBBS FRACP PhD, Alan C. Street MBBS FRACP and Caroline Marshall MBBS FRACP PhD
Infection Control and Hospital Epidemiology
Vol. 34, No. 8 (August 2013), pp. 818-824
Published by: Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America
Stable URL: http://www.jstor.org/stable/10.1086/671273
Page Count: 7
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Objective. To determine the relationship between methicillin-resistant Staphylococcus aureus (MRSA) colonization density, colonization site, and probability of infection in a frequently screened cohort of intensive care unit (ICU) patients.Methods. Patients had swab samples tested for MRSA at admission to the ICU, discharge from the ICU, and twice weekly during their ICU stay, and they were followed up for development of MRSA infection. Swab test results were analyzed to determine the proportion of patients colonized and the proportion colonized at each screening site. Hazard of MRSA infection (rate of infection per day at risk) was calculated using a Cox proportional hazards analysis, and risk factors for MRSA infection, including presence of MRSA, degree of colonization, and pattern of colonization were determined.Results. Among the 4,194 patient episodes, 238 (5.7%) had screening results that were positive for MRSA, and there were 34 cases of MRSA infection. The hazard ratio (HR) for developing an infection increased as more sites were colonized (HR, 3.4 for being colonized at more than 1 site compared with colonization at 1 site [95% confidence interval, 1.2–9.9]). Colonization site was predictive of developing infection (HR for nose or throat colonization compared with no colonization, 168 [95% confidence interval, 69–407]).Conclusion. This study demonstrated that the hazard of developing an infection was higher when more sites were colonized and that certain sites were more predictive of infection than others. These results may be useful for predicting infection in ICU patients and may influence treatment.
© 2013 by The Society for Healthcare Epidemiology of America. All rights reserved.