Analysis of ESAC-Net/EARS-Net Data from 29 EEA Countries for Spatiotemporal Associations Between Antimicrobial Use and Resistance-Implications for Antimicrobial Stewardship?

对来自 29 个欧洲经济区国家的 ESAC-Net/EARS-Net 数据进行分析,以探究抗菌药物使用与耐药性之间的时空关联——这对抗菌药物管理有何启示?

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Abstract

BACKGROUND/OBJECTIVES: Antimicrobial resistance is one of the foremost global health concerns of today, and it could offset much of the progress accrued in healthcare over the last century. Excessive antibiotic use accelerates this problem, but it is recognised that specific agents differ in their capacity to promote resistance, a concept recently promoted by the World Health Organisation in the form of its Access, Watch, Reserve (AWaRe) schema. Which, if any, agents should be construed as having a high proclivity for selection of resistance has been contested. The European Antimicrobial Resistance Surveillance Network (EARS-NET) and European Surveillance of Antimicrobial Consumption Network (ESAC-NET) curate population level data over time and throughout the European Economic Area (EEA). EARS-NET monitors resistance to antimicrobials amongst invasive isolates of sentinel pathogens whereas ESAC-NET tracks usage of systemic antimicrobials. Together, data from these networks were interrogated to delineate correlations between antimicrobial consumption and resistance. METHODS: Using univariate and multivariate regression analyses, spatiotemporal associations between the use of specific antimicrobial classes and 14 key resistance phenotypes in five sentinel pathogens were assessed methodically for 29 EEA countries. RESULTS: Use of second and third generation cephalosporins, extended spectrum penicillin/β-lactamase inhibitor combinations, carbapenems, fluoroquinolones, nitroimidazoles and macrolides strongly correlated with key resistance phenotypes, as did overall antimicrobial consumption. CONCLUSIONS: The data obtained mostly support the WHO AWaRe schema with critical caveats. They have the potential to inform antimicrobial stewardship initiatives in the EEA, highlighting obstacles and shortcomings which may be modified in future to minimise positive selection for problematic resistance.

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