Davies, K, Davis, G orcid.org/0000-0002-2826-0897, Barbut, F et al. (9 more authors) (2020) Factors affecting reported Clostridioides difficile infection rates; the more you look the more you find, but should you believe what you see? Anaerobe, 62. 102178. ISSN 1075-9964
Abstract
Reported rates of C. difficile infection (CDI) have increased in many settings; however, these can be affected by factors including testing density (test-density) and diagnostic methods. We aimed to describe the impact of multiple factors on CDI rates.
Hospitals (n = 182) across five countries (France, Germany, Italy, Spain, and UK) provided data on; size and type of institution, CDI testing methodology, number of tests/month and patient-bed-days (pbds)/month over one year. Incidence rates were compared between countries, different sized institutions, types of institutions and testing method.
After univariate analyses, the highest CDI rates were observed in Italy (average 11.8/10,000pbds/hospital/month), acute/primary hospitals (12.3/10,000pbds/hospital/month), small hospitals (16.7/10,000pbds/hospital/month), and hospitals using methods that do not detect toxin (NO-TOXIN) (e.g. GDH/NAAT or standalone NAAT) (10.7/10,000pbds/hospital/month). After adjusting for test-density, highest incidence rates were still in Italy, acute/primary hospitals and those using NO-TOXIN. The relative rate in long-term healthcare facilities (LTHCFs) increased, but size of institution no longer influenced the CDI rate.
Test-density appears to have the largest effect on reported CDI rates. NO-TOXIN testing still influences CDI rates, even after adjusting for test-density, which is consistent with tests that ‘overcall’ true CDI. Low test-density can mask the true burden of CDI, e.g. in LTHCFs, highlighting the importance of good quality surveillance.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Anaerobe. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Clostridium difficile infection; Diagnosis; Epidemiology; Testing algorithms |
Dates: |
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Institution: | The University of Leeds |
Funding Information: | Funder Grant number Sanofi Pasteur LUCLID 5 |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Mar 2020 11:34 |
Last Modified: | 28 Jun 2022 10:50 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.anaerobe.2020.102178 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157986 |
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