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Aliment Pharmacol Ther ; 43(6): 725-33, 2016 Mar.
Article in English | MEDLINE | ID: mdl-26849527

ABSTRACT

BACKGROUND: Clostridium difficile infection (CDI) is a public health threat and associated with significant mortality. However, there is a paucity of objectively derived CDI severity scoring systems to predict mortality. AIM: To develop a novel CDI risk score to predict mortality entitled: Clostridium difficile associated risk of death score (CARDS). METHODS: We obtained data from the United States 2011 Nationwide Inpatient Sample (NIS) database. All CDI-associated hospitalisations were identified using discharge codes (ICD-9-CM, 008.45). Multivariate logistic regression was utilised to identify independent predictors of mortality. Clostridium difficile associated risk of death score was calculated by assigning a numeric weight to each parameter based on their odds ratio in the final logistic model. Predictive properties of model discrimination were assessed using the c-statistic and validated in an independent sample using the 2010 NIS database. RESULTS: We identified 77 776 hospitalisations, yielding an estimate of 374 747 cases with an associated diagnosis of CDI in the US, 8% of whom died in the hospital. The eight severity score predictors were identified on multivariate analysis: age, cardiopulmonary disease, malignancy, diabetes, inflammatory bowel disease, acute renal failure, liver disease and 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 1.2% with a CARDS of 0 compared to 100% with CARDS of 18. The model performed equally well in our validation cohort. CONCLUSION: Clostridium difficile associated risk of death score is a promising simple severity score to predict mortality among those hospitalised with C. difficile infection.


Subject(s)
Clostridioides difficile , Clostridium Infections/mortality , Health Status Indicators , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Comorbidity , Female , Hospitalization , Humans , Inpatients , Logistic Models , Male , Middle Aged , Multivariate Analysis , Odds Ratio , Socioeconomic Factors , United States , Young Adult
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