Development and Validation of a Clostridium difficile Infection Risk Prediction Model
Development and Validation of a Clostridium difficile Infection Risk Prediction Model
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DOI：
10.1086/658944
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发表时间：
2011-04-01
影响因子：
4.5
通讯作者：
Fraser, Victoria J.
中科院分区：
文献类型：
--
作者：
Dubberke, Erik R.;Yan, Yan;Fraser, Victoria J.
OBJECTIVE.建立并验证一个风险预测模型，该模型可以在艰难梭菌感染（CDI）的高危患者发病前识别出他们。三级医疗中心的回顾性队列研究。2003年期间住院至少48小时的患者。从医院的医学信息学数据库中以电子方式收集数据，并采用逻辑回归分析来确定最能预测患者发生CDI风险的变量。计算了模型判别和校正。该模型被引导500次，以验证预测的准确性。计算受试者工作特征曲线以评估潜在风险临界值。共有35，350名住院患者接受了研究，其中包括329名CDI患者。风险预测模型中的变量包括年龄、CDI压力、过去60天内入院的次数、改良急性生理学评分、高危抗生素治疗天数、白蛋白水平是否低、是否入住重症监护室以及是否接受过泻药、胃酸抑制剂或抗蠕动药物。模型的校正和区分度均为非常好至极好（C指数，0.88; Brier评分，0.009）。CDI风险预测模型表现良好。还需要进一步的研究来确定它是否可以在临床环境中使用，以防止CDI相关的结果和降低成本。感染控制医院流行病学2011;32（4）：360-366
OBJECTIVE. To develop and validate a risk prediction model that could identify patients at high risk for Clostridium difficile infection (CDI) before they develop disease.DESIGN AND SETTING. Retrospective cohort study in a tertiary care medical center.PATIENTS. Patients admitted to the hospital for at least 48 hours during the calendar year 2003.METHODS. Data were collected electronically from the hospital's Medical Informatics database and analyzed with logistic regression to determine variables that best predicted patients' risk for development of CDI. Model discrimination and calibration were calculated. The model was bootstrapped 500 times to validate the predictive accuracy. A receiver operating characteristic curve was calculated to evaluate potential risk cutoffs.RESULTS. A total of 35,350 admitted patients, including 329 with CDI, were studied. Variables in the risk prediction model were age, CDI pressure, times admitted to hospital in the previous 60 days, modified Acute Physiology Score, days of treatment with high-risk antibiotics, whether albumin level was low, admission to an intensive care unit, and receipt of laxatives, gastric acid suppressors, or antimotility drugs. The calibration and discrimination of the model were very good to excellent (C index, 0.88; Brier score, 0.009).CONCLUSIONS. The CDI risk prediction model performed well. Further study is needed to determine whether it could be used in a clinical setting to prevent CDI-associated outcomes and reduce costs. Infect Control Hosp Epidemiol 2011;32(4):360-366