Methicillin-Resistant Staphylococcus aureus (MRSA) Nasal Real-Time PCR: A Predictive Tool for Contamination of the Hospital Environment

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2015-01
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American English
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Cambridge
Abstract

OBJECTIVE We sought to determine whether the bacterial burden in the nares, as determined by the cycle threshold (CT) value from real-time MRSA PCR, is predictive of environmental contamination with MRSA. METHODS Patients identified as MRSA nasal carriers per hospital protocol were enrolled within 72 hours of room admission. Patients were excluded if (1) nasal mupirocin or chlorhexidine body wash was used within the past month or (2) an active MRSA infection was suspected. Four environmental sites, 6 body sites and a wound, if present, were cultured with premoistened swabs. All nasal swabs were submitted for both a quantitative culture and real-time PCR (Roche Lightcycler, Indianapolis, IN). RESULTS At study enrollment, 82 patients had a positive MRSA-PCR. A negative correlation of moderate strength was observed between the CT value and the number of MRSA colonies in the nares (r=−0.61; P<0.01). Current antibiotic use was associated with lower levels of MRSA nasal colonization (CT value, 30.2 vs 27.7; P<0.01). Patients with concomitant environmental contamination had a higher median log MRSA nares count (3.9 vs 2.5, P=0.01) and lower CT values (28.0 vs 30.2; P<0.01). However, a ROC curve was unable to identify a threshold MRSA nares count that reliably excluded environmental contamination. CONCLUSIONS Patients with a higher burden of MRSA in their nares, based on the CT value, were more likely to contaminate their environment with MRSA. However, contamination of the environment cannot be predicted solely by the degree of MRSA nasal colonization.

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Livorsi, D. J., Arif, S., Garry, P., Kundu, M. G., Satola, S. W., Davis, T. H., … Kressel, A. B. (2015). Methicillin-Resistant Staphylococcus aureus (MRSA) Nasal Real-Time PCR: A Predictive Tool for Contamination of the Hospital Environment. Infection Control & Hospital Epidemiology, 36(01), 34–39. http://doi.org/10.1017/ice.2014.16
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Infection Control & Hospital Epidemiology
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