Determinants of Clostridium difficile Infection Incidence Across Diverse United States Geographic Locations

Details

• Alternative Title:
  Open Forum Infect Dis
• Personal Author:
  Lessa, Fernanda C. ; Mu, Yi ; Winston, Lisa G. ; Dumyati, Ghinwa K. ; Farley, Monica M. ; Beldavs, Zintars G. ; Kast, Kelly ; Holzbauer, Stacy M. ; Meek, James I. ; Cohen, Jessica ; McDonald, L. Clifford ; Fridkin, Scott K.
• Description:
  Background
  
   Clostridium difficile infection (CDI) is no longer restricted to hospital settings, and population-based incidence measures are needed. Understanding the determinants of CDI incidence will allow for more meaningful comparisons of rates and accurate national estimates.
  
  Methods
  
   Data from active population- and laboratory-based CDI surveillance in 7 US states were used to identify CDI cases (ie, residents with positive C difficile stool specimen without a positive test in the prior 8 weeks). Cases were classified as community-associated (CA) if stool was collected as outpatients or ≤3 days of admission and no overnight healthcare facility stay in the past 12 weeks; otherwise, cases were classified as healthcare-associated (HA). Two regression models, one for CA-CDI and another for HA-CDI, were built to evaluate predictors of high CDI incidence. Site-specific incidence was adjusted based on the regression models.
  
  Results
  
   Of 10 062 cases identified, 32% were CA. Crude incidence varied by geographic area; CA-CDI ranged from 28.2 to 79.1/100 000 and HA-CDI ranged from 45.7 to 155.9/100 000. Independent predictors of higher CA-CDI incidence were older age, white race, female gender, and nucleic acid amplification test (NAAT) use. For HA-CDI, older age and a greater number of inpatient-days were predictors. After adjusting for relevant predictors, the range of incidence narrowed greatly; CA-CDI rates ranged from 30.7 to 41.3/100 000 and HA-CDI rates ranged from 58.5 to 94.8/100 000.
  
  Conclusions
  
   Differences in CDI incidence across geographic areas can be partially explained by differences in NAAT use, age, race, sex, and inpatient-days. Variation in antimicrobial use may contribute to the remaining differences in incidence.
  
  
• Subjects:
  Major Articles
• Source:
  Open Forum Infect Dis. 2014; 1(2).
• Document Type:
  Journal Article
• Place as Subject:
  United States
• Volume:
  1
• Issue:
  2
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:705dd4f918c0962df31ff5eb3e6a01f995863eb2cc08bc7c53a19f2d1a17a3a5
• Download URL:
  https://stacks.cdc.gov/view/cdc/28184/cdc_28184_DS1.pdf
• File Type:
  [PDF - 332.64 KB ]