Kuzmenkov Alexey Y, Trushin Ivan V, Vinogradova Alina G, Avramenko Andrey A, Sukhorukova Marina V, Malhotra-Kumar Surbhi, Dekhnich Andrey V, Edelstein Mikhail V, Kozlov Roman S
Institute of Antimicrobial Chemotherapy, Smolensk State Medical University of the Ministry of Health of the Russian Federation, Smolensk, Russia.
Department of Medical Microbiology, University of Antwerp, Antwerp, Belgium.
Front Microbiol. 2021 Mar 12;12:620002. doi: 10.3389/fmicb.2021.620002. eCollection 2021.
Surveillance of antimicrobial resistance (AMR) is crucial for identifying trends in resistance and developing strategies for prevention and treatment of infections. Globally, AMR surveillance systems differ in terms of organizational principles, comprehensiveness, accessibility, and usability of data presentation. Until recently, the data on AMR in Russia were scarcely available, especially to international community, despite the fact that the large prospective multicenter surveillance in Russia was conducted and data were accumulated for over 20 years. We describe the source of data, structure, and functionality of a new-generation web platform, called AMRmap (https://amrmap.net/), for analysis of AMR surveillance data in Russia. The developed platform currently comprises susceptibility data of >40,000 clinical isolates, and the data on abundance of key resistance determinants, including acquired carbapenemases in gram-negatives, are updated annually with information on >5,000 new isolates. The AMRmap allows smart data filtration by multiple parameters and provides interactive data analysis and visualization tools: MIC and S/I/R distribution plots, time-trends and regression plots, associated resistance plots, prevalence maps, statistical significance graphs, and tables.
抗菌药物耐药性(AMR)监测对于识别耐药趋势以及制定感染预防和治疗策略至关重要。在全球范围内,AMR监测系统在组织原则、全面性、数据可获取性以及数据呈现的可用性方面存在差异。直到最近,俄罗斯的AMR数据几乎无法获取,尤其是对国际社会而言,尽管俄罗斯进行了大规模前瞻性多中心监测并积累了20多年的数据。我们描述了一个名为AMRmap(https://amrmap.net/)的新一代网络平台的数据源、结构和功能,该平台用于分析俄罗斯的AMR监测数据。目前开发的平台包含超过40,000株临床分离株的药敏数据,关于关键耐药决定因素丰度的数据,包括革兰氏阴性菌中获得性碳青霉烯酶的数据,每年都会更新超过5,000株新分离株的信息。AMRmap允许通过多个参数进行智能数据筛选,并提供交互式数据分析和可视化工具:最低抑菌浓度(MIC)和敏感/中介/耐药(S/I/R)分布图、时间趋势和回归图、相关耐药图、流行率地图、统计显著性图以及表格。