JOURNAL ARTICLE
Surveillance of Clostridioides difficile on hospital admission and outpatient antibiotic use in Germany—a 9 year ecological analysis.
Published In: Journal of Antimicrobial Chemotherapy (JAC), 2025, v. 80, n. 3. P. 817 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Saydan, Selin; Schwab, Frank; Holstiege, Jakob; Bätzing, Jörg; Behnke, Michael; Schneider, Sandra; Clausmeyer, Jörg; Gastmeier, Petra; Geffers, Christine; Maechler, Friederike 3 of 3
Abstract
This article examines the association between outpatient antibiotic prescriptions under statutory health insurance (SHI) and the prevalence of Clostridioides difficile infection (CDI) on hospital admission in Germany from 2011 to 2019. Using data from the hospital infection surveillance system (Krankenhaus-Infektions-Surveillance-System; KISS) and regional antibiotic consumption records, the study found that reductions in outpatient use of basic penicillins and cephalosporins correlated with a nearly 45% decrease in CDI admission prevalence, while use of nitrofurantoin, fosfomycin, and sulphonamides/trimethoprim was associated with lower CDI risk. The analysis suggests that rational outpatient antibiotic stewardship may contribute to reducing community-acquired CDI requiring hospitalization, though limitations include ecological study design and lack of individual patient data. These findings support targeted antimicrobial stewardship interventions in outpatient settings to mitigate CDI incidence.
Additional Information
- Source:Journal of Antimicrobial Chemotherapy (JAC). 2025/03, Vol. 80, Issue 3, p817
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2025
- ISSN:0305-7453
- DOI:10.1093/jac/dkae483
- Accession Number:184040000
- Copyright Statement:Copyright of Journal of Antimicrobial Chemotherapy (JAC) is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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