Dynamic association of antimicrobial resistance in urinary isolates of Escherichia coli and Klebsiella pneumoniae between primary care and hospital settings in the Netherlands (2008–2020): a population-based studyResearch in context
Summary: Background: It is unclear whether changes in antimicrobial resistance (AMR) in primary care influence AMR in hospital settings. Therefore, we investigated the dynamic association of AMR between primary care and hospitals. Methods: We studied resistance percentages of Escherichia coli and K...
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2025-03-01
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Series: | The Lancet Regional Health. Europe |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666776224003661 |
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Summary: | Summary: Background: It is unclear whether changes in antimicrobial resistance (AMR) in primary care influence AMR in hospital settings. Therefore, we investigated the dynamic association of AMR between primary care and hospitals. Methods: We studied resistance percentages of Escherichia coli and Klebsiella pneumoniae isolates to co-amoxiclav, ciprofloxacin, fosfomycin, nitrofurantoin and trimethoprim submitted by primary care, hospital outpatient and hospital inpatient settings to the Dutch National AMR surveillance network (ISIS-AR) from 2008 to 2020. For each bacterium–antibiotic combination, we first conducted multivariable logistic regressions to calculate AMR odds ratios (ORs) by month and healthcare setting, adjusted for patient-related factors and a time term. Second, multiple time series analysis was done using vector autoregressive models including the (log) ORs for each bacterium–antibiotic combination. Models were interpreted by impulse response functions and Granger-causality tests. Findings: The main AMR association was unidirectional from primary care to hospital settings with Granger-causality p-values between <0.0001 and 0.029. Depending on the bacterium–antibiotic combination, a 1% increase of AMR in E. coli and K. pneumoniae in primary care leads to an increase of AMR in hospital settings ranging from 0.10% to 0.40%. For ciprofloxacin resistance in K. pneumoniae, we found significant bidirectional associations between all healthcare settings with Granger-causality p-values between <0.0001 and 0.0075. Interpretation: For the majority of bacterium–antibiotic combinations, the main AMR association was from primary care to hospital settings. These results underscore the importance of antibiotic stewardship at the community level. Funding: ISIS-AR is supported by the Ministry of Health, Welfare and Sport of the Netherlands and the first author by the Central University of Ecuador to follow a PhD program in Erasmus MC. |
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ISSN: | 2666-7762 |