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dc.contributor.authorJackson, S.S.
dc.contributor.authorLydecker, A.D.
dc.contributor.authorMagder, Laurence S.
dc.date.accessioned2019-03-29T14:42:00Z
dc.date.available2019-03-29T14:42:00Z
dc.date.issued2019
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85059495608&doi=10.1093%2faje%2fkwy220&partnerID=40&md5=ea344b4574fc524189e60fd4194e80bb
dc.identifier.urihttp://hdl.handle.net/10713/8569
dc.description.abstractThe prevalence of methicillin-resistant Staphylococcus aureus (MRSA) colonization among nursing home residents is high. Health-care workers (HCWs) often serve as a vector in MRSA transmission. The ability to identify residents who are likely to transmit MRSA to HCWs' hands and clothing during clinical care is important so that infection control measures, such as Contact Precautions, can be employed. Using data on demographic and clinical characteristics collected from residents of community nursing homes in Maryland and Michigan between 2012 and 2014, we developed a clinical prediction rule predicting the probability of MRSA transmission to HCWs' gowns. We externally validated this model in a cohort of Department of Veterans Affairs nursing home residents from 7 states between 2012 and 2016. The prediction model, which included sex, race, resident dependency on HCWs for care, the presence of any medical device, diabetes mellitus, and chronic skin breakdown, showed good performance (C statistic = 0.70; sensitivity = 76%, specificity = 49%) in the development set. The decision curve analysis indicated that this model has greater clinical utility than use of a nares surveillance culture for MRSA colonization, which is current clinical practice for placing hospital inpatients on Contact Precautions. The prediction rule demonstrated less utility in the validation cohort, suggesting that a separate rule should be developed for residents of Veterans Affairs nursing homes.en_US
dc.description.urihttps://dx.doi.org/10.1093/aje/kwy220en_US
dc.language.isoen_USen_US
dc.publisherOxford University Pressen_US
dc.relation.ispartofAmerican journal of epidemiology
dc.subjectdecision curve analysisen_US
dc.subjectexternal validationen_US
dc.subjectprediction ruleen_US
dc.subject.meshDecision Support Techniquesen_US
dc.subject.meshInfectious Disease Transmission, Patient-to-Professional--prevention & controlen_US
dc.subject.meshMethicillan-Resistant Staphylococcus aureusen_US
dc.subject.meshNursing Homesen_US
dc.titleDevelopment and Validation of a Clinical Prediction Rule to Predict Transmission of Methicillin-Resistant Staphylococcus aureus in Nursing Homesen_US
dc.typeArticleen_US
dc.identifier.doi10.1093/aje/kwy220
dc.identifier.pmid30351349


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