Predictors of methicillin-resistant Staphylococcus aureus colonization at hospital admission

Background The best strategy for active surveillance for methicillin-resistant Staphylococcus aureus (MRSA) remains unclear. We attempted to identify a risk factor score to predict MRSA colonization at hospital admission. Methods Data on 9 variables reported as risk factors for MRSA colonization were analyzed, and a risk factor score to predict MRSA colonization was generated using multivariable logistic regression and receiver operating characteristic curve analyses. This risk score was then prospectively validated. Results Four risk factors (nursing home residence, diabetes, hospitalization in the past year, and chronic skin condition/infection) were significantly associated with MRSA colonization (c-statistic = 0.846). A cut-off score of 8 or greater would result in screening 20% of admissions and would detect 71% of MRSA-colonized patients. In the prospective validation study, a cut-off score of 8 or greater required screening 21% of admissions and detected 54% of MRSA. Nursing home residence was the best predictor of MRSA colonization. Conclusion A similar risk factor-based screening strategy could be used to predict MRSA colonization in other institutions. Our data support routine screening of nursing home patients at hospital admission.