Clostridium difficile associated risk of death score (CARDS): A novel severity score to predict mortality among hospitalised patients with C. difficile infection

Z. Kassam, C. Cribb Fabersunne, M. B. Smith, E. J. Alm, G. G. Kaplan, G. C. Nguyen, A. N. Ananthakrishnan

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)725-733
Number of pages9
JournalAlimentary Pharmacology and Therapeutics
Volume43
Issue number6
DOIs
StatePublished - Mar 1 2016
Externally publishedYes

Fingerprint

Clostridium Infections
Clostridium difficile
Mortality
Inpatients
Hospitalization
Logistic Models
Databases
Weights and Measures
International Classification of Diseases
Inflammatory Bowel Diseases
Acute Kidney Injury
Liver Diseases

ASJC Scopus subject areas

  • Pharmacology (medical)

Cite this

Clostridium difficile associated risk of death score (CARDS) : A novel severity score to predict mortality among hospitalised patients with C. difficile infection. / Kassam, Z.; Cribb Fabersunne, C.; Smith, M. B.; Alm, E. J.; Kaplan, G. G.; Nguyen, G. C.; Ananthakrishnan, A. N.

In: Alimentary Pharmacology and Therapeutics, Vol. 43, No. 6, 01.03.2016, p. 725-733.

Research output: Contribution to journalArticle

Kassam, Z. ; Cribb Fabersunne, C. ; Smith, M. B. ; Alm, E. J. ; Kaplan, G. G. ; Nguyen, G. C. ; Ananthakrishnan, A. N. / Clostridium difficile associated risk of death score (CARDS) : A novel severity score to predict mortality among hospitalised patients with C. difficile infection. In: Alimentary Pharmacology and Therapeutics. 2016 ; Vol. 43, No. 6. pp. 725-733.
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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.",
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T2 - A novel severity score to predict mortality among hospitalised patients with C. difficile infection

AU - Kassam, Z.

AU - Cribb Fabersunne, C.

AU - Smith, M. B.

AU - Alm, E. J.

AU - Kaplan, G. G.

AU - Nguyen, G. C.

AU - Ananthakrishnan, A. N.

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N2 - 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.

AB - 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.

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