Development and Validation of a Clinical Prediction Rule to Predict Transmission of Methicillin-Resistant Staphylococcus aureus in Nursing Homes

Abstract

The 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.

Trial registration: ClinicalTrials.gov NCT01350479.

Figure 1.

Calibration curves for a clinical rule predicting transmission of methicillin-resistant Staphylococcus aureus (MRSA) to health-care workers’ gowns in a community-based nursing home cohort (the “development cohort”; 2012–2014) (A) and a Department of Veterans Affairs nursing home cohort (the “validation cohort”; 2012–2016) (B), United States, 2012–2016. The graph shows the observed proportion of MRSA transmission plotted on the y-axis against the risk of MRSA transmission predicted by the model on the x-axis. The triangles represent the observed proportion in each model-defined decile of risk, the vertical lines show the 95% confidence intervals, and the dotted line is the locally weighted scatterplot smoothing (LOESS) smooth regression line. The dashed 45-degree line represents perfect model calibration.

Figure 2.

Decision curve showing the net benefit of use of Contact Precautions for the prevention of methicillin-resistant Staphylococcus aureus (MRSA) transmission in nursing homes at varying threshold probabilities, United States, 2012–2016. A) Development cohort (a community-based nursing home cohort; 2012–2014); B) validation cohort (a Department of Veterans Affairs nursing home cohort; 2012–2016). Threshold probabilities: 1) none (heavy black line)—the net benefit of putting no resident on Contact Precautions (current policy), which is set at 0; 2) all (gray line)—putting all nursing home residents on Contact Precautions; 3) prediction rule (dashed line)—putting residents who meet a specified threshold of risk according to the prediction rule on Contact Precautions; or 4) MRSA-positive nares culture (light black line)—putting all MRSA nares culture-positive residents on Contact Precautions.