Mayo Clinic, Department of Infectious Diseases, Rochester, MN.
Am J Infect Control. 2013 Nov;41(11):1043-7. doi: 10.1016/j.ajic.2013.02.013. Epub 2013 May 21.
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.
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.
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.
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.
耐甲氧西林金黄色葡萄球菌（MRSA）主动监测的最佳策略仍不清楚。我们试图确定一种风险因素评分，以预测入院时的 MRSA 定植。
分析了 9 个变量的数据，这些变量被报告为 MRSA 定植的危险因素，并使用多变量逻辑回归和接收者操作特征曲线分析生成了预测 MRSA 定植的风险因素评分。然后对该风险评分进行了前瞻性验证。
4 个危险因素（疗养院居住、糖尿病、过去一年住院和慢性皮肤状况/感染）与 MRSA 定植显著相关（c 统计量=0.846）。评分 8 分或以上将导致筛查 20%的入院患者，并可检测到 71%的 MRSA 定植患者。在前瞻性验证研究中，评分 8 分或以上需要筛查 21%的入院患者，并检测到 54%的 MRSA。疗养院居住是 MRSA 定植的最佳预测因素。
可以使用类似的基于风险因素的筛查策略来预测其他机构的 MRSA 定植。我们的数据支持对入院的疗养院患者进行常规筛查。
