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2015-2019 年加拿大肠病原体病例抗生素处方相关风险因素。

Risk factors associated with antibiotic prescriptions for cases of enteric pathogens in Canada, 2015-2019.

机构信息

Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.

Centre for Food-Borne, Environmental & Zoonotic Infectious Diseases, Food-Borne Disease and Antimicrobial Resistance Surveillance Division, Public Health Agency of Canada, Guelph, ON, Canada.

出版信息

Epidemiol Infect. 2024 Oct 23;152:e131. doi: 10.1017/S0950268824001365.

Abstract

Inappropriate antibiotic use is a key driver of antibiotic resistance and one that can be mitigated through stewardship. A better understanding of current prescribing practices is needed to develop successful stewardship efforts. This study aims to identify factors that are associated with human cases of enteric illness receiving an antibiotic prescription. Cases of laboratory-confirmed enteric illness reported to the FoodNet Canada surveillance system between 2015 and 2019 were the subjects of this study. Laboratory data were combined with self-reported data collected from an enhanced case questionnaire that included demographic data, illness duration and symptoms, and antibiotic prescribing. The data were used to build univariable logistic regression models and a multivariable logistic regression model to explore what factors were associated with a case receiving an antibiotic prescription. The final multivariable model identified several factors as being significantly associated with cases being prescribed an antibiotic. Some of the identified associations indicate that current antibiotic prescribing practices include a substantial level of inappropriate use. This study provides evidence that antibiotic stewardship initiatives targeting infectious diarrhoea are needed to optimize antibiotic use and combat the rise of antibiotic resistance.

摘要

不合理使用抗生素是抗生素耐药性的一个主要驱动因素,可以通过管理来减轻其影响。为了制定成功的管理措施,需要更好地了解当前的处方实践情况。本研究旨在确定与接受抗生素处方的肠道疾病人类病例相关的因素。本研究的对象是 2015 年至 2019 年向加拿大食品网监测系统报告的实验室确诊肠道疾病病例。实验室数据与从增强型病例调查问卷中收集的自我报告数据相结合,该调查问卷包括人口统计学数据、疾病持续时间和症状以及抗生素处方。数据用于构建单变量逻辑回归模型和多变量逻辑回归模型,以探讨哪些因素与病例接受抗生素处方有关。最终的多变量模型确定了几个与病例开抗生素处方显著相关的因素。一些确定的关联表明,目前的抗生素处方实践包括大量不合理的使用。本研究提供了证据,表明需要针对传染性腹泻的抗生素管理措施来优化抗生素的使用并对抗抗生素耐药性的上升。

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