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J Am Coll Surg. 2008 Nov;207(5):683-9. doi: 10.1016/j.jamcollsurg.2008.05.023. Epub 2008 Jun 30.

A predictive model for identifying surgical patients at risk of methicillin-resistant Staphylococcus aureus carriage on admission.

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  • 1Infection Control Program, University of Geneva Hospitals and Medical Schools, Geneva, Switzerland.



Legislative mandates and current guidelines for control of nosocomial transmission of methicillin-resistant Staphylococcus aureus (MRSA) recommend screening of patients at risk of MRSA carriage on hospital admission. Indiscriminate application of these guidelines can result in a large number of unnecessary screening tests.


This study was conducted to develop and validate a prediction model to define surgical patients at risk of previously unknown MRSA carriage on admission. We used data from two prospective studies to derivate and validate predictors of previously unknown MRSA carriage on admission, using logistic regression analysis.


A total of 13,262 patients (derivation cohort, 3,069; validation cohort, 10,193) were admitted to the surgery department and screened for MRSA. Prevalence of MRSA carriage at time of admission increased from 3.2% in 2003 to 5.1% in the period 2004 to 2006, with a majority of newly identified MRSA carriers (64%). Three independent factors were correlated with previously unknown MRSA carriage: recent antibiotic treatment (adjusted odds ratio [OR]: 4.5; p < 0.001), history of hospitalization (adjusted OR: 2.7; p = 0.03), and age older than 75 years (adjusted OR: 1.9; p = 0.048). A score (range 0 to 9 points) calculated from these variables was developed. Probability of previously unknown MRSA carriage was 5% (8 of 152) in patients with a low score (< 2 points), 11% (19 of 166) in those with an intermediate score (2 to 6 points), and 34% (30 of 87) in those with a high score (> or = 7 points). Limiting screening to patients with all 3 risk factors (21% and 26% of patients in the derivation and validation cohort, respectively) would have correctly identified 53% and 37% of MRSA carriers in both cohorts.


A predictive model using three easily retrievable determinants might help to better target surgical patients at risk of MRSA carriage on admission.

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