title: Clostridium difficile associated risk of death score (CARDS): a novel severity score to predict mortality among hospitalised patients with C. difficile infection.
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.
  
  
  OBJECTIVE
  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.
  
  
  CONCLUSIONS
  Clostridium difficile associated risk of death score is a promising simple severity score to predict mortality among those hospitalised with C. difficile infection.
authors: Massachusetts Institute of Technology, Cambridge, MA, USA.|OpenBiome, Medford, MA, USA.
authors: Z
authors: Z
authors: Kassam
authors: Harvard Medical School, Boston, MA, USA.|Harvard School of Public Health, Boston, MA, USA.
authors: C
authors: C
authors: Cribb Fabersunne
authors: Massachusetts Institute of Technology, Cambridge, MA, USA.|OpenBiome, Medford, MA, USA.
authors: M B
authors: MB
authors: Smith
authors: Massachusetts Institute of Technology, Cambridge, MA, USA.
authors: E J
authors: EJ
authors: Alm
authors: University of Calgary, Calgary, AB, Canada.
authors: G G
authors: GG
authors: Kaplan
authors: Mount Sinai Hospital Centre for Inflammatory Bowel Disease, University of Toronto, Toronto, ON, Canada.
authors: G C
authors: GC
authors: Nguyen
authors: Harvard Medical School, Boston, MA, USA.|Massachusetts General Hospital, Boston, MA, USA.
authors: A N
authors: AN
authors: Ananthakrishnan
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D016360:Clostridioides difficile; D003015:Clostridium Infections / Q000401:mortality*; D015897:Comorbidity; D005260:Female; D006305:Health Status Indicators; D006760:Hospitalization; D006801:Humans; D007297:Inpatients; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D012959:Socioeconomic Factors; D014481:United States; D055815:Young Adult