C. difficile-Associated Risk of Death Score (CARDS): A Novel Risk Score to Predict Mortality Among Hospitalized Patients With C. difficile Infection: ACG Fellow Award

Introduction:C. difficile infection (CDI) is the leading health care-associated infection in the United States with significant associated mortality. Existing treatments for CDI vary in their absolute and relative efficacy based on severity of underlying disease; yet there are few objectively derived severity scores. Furthermore, development of an accurate scoring system to define severity across large administrative databases additionally allows for important comparisons in outcomes across populations and over time. Our aim was to develop a novel CDI risk score to predict mortality for clinicians and epidemiologists entitled: C. difficile associated risk of death score (CARDS). Methods: We obtained data from the 2011 nationwide inpatient sample (NIS) database, the largest source of all-payer hospital discharge information in the United States capturing data from 1,049 hospitals within 46 states. Standard international classification of disease, 9th Edition (ICD-9) was used to identify all patients with CDI (008.45). Multivariate logistic regression was utilized to identify independent predictors of mortality in patients with CDI. A risk score was calculated by assigning a numeric weight to each parameter based on their odds ratio (OR). Predictive properties of model discrimination were assessed using the c-statistic and CARDS compared to standard models. Results: We identified 343,982 hospitalizations with an associated diagnosis of CDI, 8% of whom died in the hospital. The 8 CARDS predictors identified on multivariate analysis were age, cardiopulmonary disease, malignancy, diabetes, inflammatory bowel disease, acute renal failure, liver disease, and intensive care admission (ICU) admission, with weights ranging from -1 (for diabetes) to 5 (for ICU admission). The overall risk score in the cohort ranged from 0 to 18. Mortality increased significantly as CARDS increased. CDI-associated mortality was 1% with CARDS=0; 4% with CARDS=5; 20% with CARDS=10; 47% with CARDS=15 and 100% with CARDS=18. The predictive test characteristic for CARDS was robust (c-statistic=0.77). CARDS performed better than age, sex, and Charlson co-morbidity index model (c-statistic=0.64) or age, sex, Charlson co-morbidity index, and ICU admission model (c-statistic= 0.73) in predicting CDI-associated mortality in hospitalized patients. Conclusion: CARDS is a promising risk score to predict mortality among hospitalized with CDI. It may be useful to stratify CDI severity and compare outcomes over time and across settings using administrative data. Disclosure - Dr. Ananthakrishnan - Scientific advisory board of Cubist Pharmaceuticals.

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