1265. Are Previously Identified Risk Factors Truly Predictive of Healthcare-Associated Methicillin-Resistant Staphylococcus aureus Pneumonia?
Session: Poster Abstract Session: Clinical Infectious Diseases: Respiratory Infections
Friday, October 28, 2016
Room: Poster Hall

The proposed risk factors for multidrug resistant organisms in patients with pneumonia and healthcare-associated risk factors (HCAP) have never been unequivocally validated. Identifying individual patient risk for methicillin-resistant Staphylococcus aureus (MRSA) in particular can potentially eliminate the need for the empiric addition of a single antibiotic targeting MRSA in all patients presenting with HCAP.


This retrospective, multi-center, observational cohort study included patients admitted to the hospital from January 2013 to June 2015 for HCAP. Patients with pneumonia and at least one HCAP risk factor were included (n=100) and divided into two cohorts based on respiratory cultures: MRSA (n=50) and non-MRSA (n=50). A univariate and multivariate logistic regression were used to identify risk factors for MRSA HCAP.


Patients with MRSA HCAP were more likely to have 3 or more SIRS criteria on admission and to require ICU care and mechanical ventilation compared to those with non-MRSA HCAP. In addition, patients with MRSA were more likely to have received intravenous antibiotics, chemotherapy, or wound care within the previous 30 days. When controlling for confounding variables, none of the traditional HCAP risk factors were statistically significant. Only history of MRSA infection (OR 7.2 [2.0-25.3], p=0.002) significantly affected risk for MRSA pneumonia, while hospitalization in the previous 60 days trended towards increased MRSA risk but was not statistically significant (OR 5.1 [0.6-41.4], p=0.127).


When controlled for confounding variables, we found that prior history of MRSA infection alone was a significant risk factor for MRSA HCAP. Further evaluation may be needed to determine if different combinations of risk factors identified in univariate analysis are more predictive than when studied alone.

Hilary Gerwin, PharmD1, Siyun Liao, Pharm.D., PhD, BCPS2, Maria Guido, Pharm.D., BCPS2, Brittany Woolf, PharmD, BCPS1 and Madhuri Sopirala, MD, MPH3, (1)Pharmacy, University of Cincinnati Medical Center, Cincinnati, OH, (2)UC Health - University of Cincinnati Medical Center, Cincinnati, OH, (3)Infectious Diseases/Internal Medicine, University of Cincinnati, Cincinnati, OH


H. Gerwin, None

S. Liao, None

M. Guido, None

B. Woolf, None

M. Sopirala, None

Findings in the abstracts are embargoed until 12:01 a.m. CDT, Wednesday Oct. 26th with the exception of research findings presented at the IDWeek press conferences.