A. Kuzmenkov, A. G. Vinogradova, I. V. Trushin, M. Edelstein, A. A. Avramenko, A. Dekhnich, R. Kozlov
{"title":"AMRmap -抗生素耐药性监测系统在俄罗斯","authors":"A. Kuzmenkov, A. G. Vinogradova, I. V. Trushin, M. Edelstein, A. A. Avramenko, A. Dekhnich, R. Kozlov","doi":"10.36488/cmac.2021.2.198-204","DOIUrl":null,"url":null,"abstract":"Objective. To review the basic principles and functionality of the AMRmap online resource. Materials and Methods. The AMRmap platform was developed using the R programming language and various downloadable modules – packages. The current annually updated version of EUCAST clinical breakpoints was applied for determination of categories of susceptibility to antimicrobial agents. Descriptive analysis includes calculation of absolute and relative frequencies, median values, and confidence intervals using the Wilson method. Categorical variables are compared using Fisher’s exact test and Holm correction method for multiple comparisons. The algorithms are used to visualize multiple comparisons, kernel regression for trend analysis, and algorithms for finding associative rules. Results. The developed surveillance system includes modules for filtering, analyzing and visualizing antibiotic resistance data. The filters allow creating a sample of data with a specific list of parameters. A tab-based separation of analysis and visualization options ensure efficient stepwise evaluation of results. Data saving and sharing functions are also provided. Conclusions. This web-based informatics system provides a convenient way to AMR data from prospective microbiological surveillance studies in Russia. AMRmap can be accessed at https://amrmap.ru.","PeriodicalId":53392,"journal":{"name":"Klinicheskaia mikrobiologiia i antimikrobnaia khimioterapiia","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"AMRmap – antibiotic resistance surveillance system in Russia\",\"authors\":\"A. Kuzmenkov, A. G. Vinogradova, I. V. Trushin, M. Edelstein, A. A. Avramenko, A. Dekhnich, R. Kozlov\",\"doi\":\"10.36488/cmac.2021.2.198-204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objective. To review the basic principles and functionality of the AMRmap online resource. Materials and Methods. The AMRmap platform was developed using the R programming language and various downloadable modules – packages. The current annually updated version of EUCAST clinical breakpoints was applied for determination of categories of susceptibility to antimicrobial agents. Descriptive analysis includes calculation of absolute and relative frequencies, median values, and confidence intervals using the Wilson method. Categorical variables are compared using Fisher’s exact test and Holm correction method for multiple comparisons. The algorithms are used to visualize multiple comparisons, kernel regression for trend analysis, and algorithms for finding associative rules. Results. The developed surveillance system includes modules for filtering, analyzing and visualizing antibiotic resistance data. The filters allow creating a sample of data with a specific list of parameters. A tab-based separation of analysis and visualization options ensure efficient stepwise evaluation of results. Data saving and sharing functions are also provided. Conclusions. This web-based informatics system provides a convenient way to AMR data from prospective microbiological surveillance studies in Russia. AMRmap can be accessed at https://amrmap.ru.\",\"PeriodicalId\":53392,\"journal\":{\"name\":\"Klinicheskaia mikrobiologiia i antimikrobnaia khimioterapiia\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Klinicheskaia mikrobiologiia i antimikrobnaia khimioterapiia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36488/cmac.2021.2.198-204\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Klinicheskaia mikrobiologiia i antimikrobnaia khimioterapiia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36488/cmac.2021.2.198-204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
AMRmap – antibiotic resistance surveillance system in Russia
Objective. To review the basic principles and functionality of the AMRmap online resource. Materials and Methods. The AMRmap platform was developed using the R programming language and various downloadable modules – packages. The current annually updated version of EUCAST clinical breakpoints was applied for determination of categories of susceptibility to antimicrobial agents. Descriptive analysis includes calculation of absolute and relative frequencies, median values, and confidence intervals using the Wilson method. Categorical variables are compared using Fisher’s exact test and Holm correction method for multiple comparisons. The algorithms are used to visualize multiple comparisons, kernel regression for trend analysis, and algorithms for finding associative rules. Results. The developed surveillance system includes modules for filtering, analyzing and visualizing antibiotic resistance data. The filters allow creating a sample of data with a specific list of parameters. A tab-based separation of analysis and visualization options ensure efficient stepwise evaluation of results. Data saving and sharing functions are also provided. Conclusions. This web-based informatics system provides a convenient way to AMR data from prospective microbiological surveillance studies in Russia. AMRmap can be accessed at https://amrmap.ru.