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Effect of clinical versus administrative data definitions on the epidemiology of C. difficile among hospitalized individuals with IBD: a population-based cohort study

BACKGROUND: Hospitalization admissions and discharge databases (DAD) using the International Classification of Diseases (ICD) codes are often used to describe the epidemiology of Clostridioides difficile infections (CDI) among those with Inflammatory bowel disease (IBD), even though DAD CDI definiti...

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Detalles Bibliográficos
Autores principales: Shaffer, Seth R., Nugent, Zoann, Bernstein, Charles N., Walkty, Andrew, Singh, Harminder
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962161/
https://www.ncbi.nlm.nih.gov/pubmed/35346066
http://dx.doi.org/10.1186/s12876-022-02223-y
Descripción
Sumario:BACKGROUND: Hospitalization admissions and discharge databases (DAD) using the International Classification of Diseases (ICD) codes are often used to describe the epidemiology of Clostridioides difficile infections (CDI) among those with Inflammatory bowel disease (IBD), even though DAD CDI definition can miss many cases of CDI. There are no data comparing the assessment of the epidemiology of CDI among those with IBD by DAD versus laboratory diagnosis. We used a population-based dataset to determine the effect of using DAD versus laboratory CDI diagnosis on CDI assessment among those with IBD. METHODS: We linked the University of Manitoba IBD Epidemiology Database to the provincial CDI laboratory dataset for the years 2005–2014. Time trends of CDI were assessed using joinpoint analyses. We used stratified logistic regression analysis to assess factors associated with CDI among individuals with IBD. RESULTS: Time trends of CDI among hospitalized individuals with IBD were similar when using DAD or the laboratory CDI diagnosis. Prior hospital admission and antibiotic exposure were associated with CDI using either of the CDI definitions, 5-ASA use was associated with CDI using DAD but not laboratory diagnosis, whereas corticosteroid exposure was associated with laboratory-based CDI diagnosis. Using laboratory results as gold standard, DAD had a sensitivity and specificity of 75.4% and 99.6% for CDI among those with IBD. CONCLUSIONS: Using ICD codes in the DAD for CDI provides similar epidemiological time trend patterns as identifying CDI in the laboratory dataset. Hence, ICD codes are reliable to determine CDI epidemiology among hospitalized individuals with IBD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-022-02223-y.