OBJECTIVES: Crohn's disease (CD) is a lifelong relapsing-remitting disease often requiring health-care contact, hospitalization, or surgery. General comorbidity indices were developed to predict mortality, which is rare in this population. There are limited tools to stratify these hospitalizations by severity. METHODS: We used data obtained from the Nationwide Inpatient Sample 2004 to identify all CD-related hospitalizations using discharge diagnosis codes (International Classification of Diseases, 9th edition, Clinical Modification, ICD-9-CM, 555.x). Independent predictors on multivariate regression were identified and used to construct a quantitative risk score to predict severe hospitalizations (defined as requiring nonelective bowel surgery or hospitalization longer than 7 days). The performance of our risk score was compared with the Elixhauser and Charlson comorbidity indices, and validated in an independent sample of CD hospitalizations from 2007. RESULTS: Our final study cohort consisted of 25,938 discharges, among which 6,169 were determined to be severe hospitalizations (23.8%). Independent predictors of disease severity included disease phenotype, anemia, malnutrition, and requirement for blood transfusion or total parenteral nutrition, as well as Clostridium difficile infection, admission to a teaching hospital, or inter-hospital transfer. The cumulative risk score ranged from 0 to 13 points, with scores >or=5 being considered to be of greater severity. A total of 15,330 (59.1%), 9,060 (34.9%), and 1,548 (6.0%) discharges were classified as being of low, intermediate, and high risk, respectively. An intermediate (odds ratio (OR) 2.63, 95% confidence interval (CI): 2.47-2.80) or high-risk score (OR 13.62, 95% CI: 12.12-15.33) was associated with a significantly higher adjusted risk of severe hospitalization. CONCLUSIONS: Using administrative data, we propose a simple quantitative risk score to measure the severity of CD hospitalizations.
OBJECTIVES:Crohn's disease (CD) is a lifelong relapsing-remitting disease often requiring health-care contact, hospitalization, or surgery. General comorbidity indices were developed to predict mortality, which is rare in this population. There are limited tools to stratify these hospitalizations by severity. METHODS: We used data obtained from the Nationwide Inpatient Sample 2004 to identify all CD-related hospitalizations using discharge diagnosis codes (International Classification of Diseases, 9th edition, Clinical Modification, ICD-9-CM, 555.x). Independent predictors on multivariate regression were identified and used to construct a quantitative risk score to predict severe hospitalizations (defined as requiring nonelective bowel surgery or hospitalization longer than 7 days). The performance of our risk score was compared with the Elixhauser and Charlson comorbidity indices, and validated in an independent sample of CD hospitalizations from 2007. RESULTS: Our final study cohort consisted of 25,938 discharges, among which 6,169 were determined to be severe hospitalizations (23.8%). Independent predictors of disease severity included disease phenotype, anemia, malnutrition, and requirement for blood transfusion or total parenteral nutrition, as well as Clostridium difficileinfection, admission to a teaching hospital, or inter-hospital transfer. The cumulative risk score ranged from 0 to 13 points, with scores >or=5 being considered to be of greater severity. A total of 15,330 (59.1%), 9,060 (34.9%), and 1,548 (6.0%) discharges were classified as being of low, intermediate, and high risk, respectively. An intermediate (odds ratio (OR) 2.63, 95% confidence interval (CI): 2.47-2.80) or high-risk score (OR 13.62, 95% CI: 12.12-15.33) was associated with a significantly higher adjusted risk of severe hospitalization. CONCLUSIONS: Using administrative data, we propose a simple quantitative risk score to measure the severity of CD hospitalizations.
Authors: Mahesh Gajendran; Chandraprakash Umapathy; Priyadarshini Loganathan; Jana G Hashash; Ioannis E Koutroubakis; David G Binion Journal: Dig Dis Sci Date: 2015-09-30 Impact factor: 3.199
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