4.4 Article

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

Journal

OPEN FORUM INFECTIOUS DISEASES
Volume 1, Issue 2, Pages -

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/ofid/ofu048

Keywords

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Funding

  1. Emerging Infections Program Cooperative Agreement between the 7 EIP sites
  2. Centers for Disease Control and Prevention

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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 CACDI incidence were older age, white race, female gender, and nucleic acid amplification test (NAAT) use. For HACDI, 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.

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