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Conduct AMR Analysis
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Get Properties of an Antiviral Drug
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< img src = "../logo.svg" class = "logo" alt = "" > < h1 > Welcome to the `AMR` package< / h1 >
< small class = "dont-index" > Source: < a href = "https://github.com/msberends/AMR/blob/HEAD/vignettes/welcome_to_AMR.Rmd" class = "external-link" > < code > vignettes/welcome_to_AMR.Rmd< / code > < / a > < / small >
< div class = "d-none name" > < code > welcome_to_AMR.Rmd< / code > < / div >
< / div >
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< p > Note: to keep the package size as small as possible, we only include
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this vignette on CRAN. You can read more vignettes on our website about
how to conduct AMR data analysis, determine MDROs, find explanation of
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EUCAST and CLSI breakpoints, and much more: < a href = "https://msberends.github.io/AMR/articles/" class = "uri" > https://msberends.github.io/AMR/articles/< / a > .< / p >
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< hr >
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< p > The < code > AMR< / code > package is a < a href = "https://msberends.github.io/AMR/#copyright" > free and
open-source< / a > R package with < a href = "https://en.wikipedia.org/wiki/Dependency_hell" class = "external-link" > zero
dependencies< / a > to simplify the analysis and prediction of
Antimicrobial Resistance (AMR) and to work with microbial and
antimicrobial data and properties, by using evidence-based methods.
< strong > Our aim is to provide a standard< / strong > for clean and
reproducible AMR data analysis, that can therefore empower
epidemiological analyses to continuously enable surveillance and
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treatment evaluation in any setting. < a href = "https://msberends.github.io/AMR/authors.html" > Many different
researchers< / a > from around the globe are continually helping us to make
this a successful and durable project!< / p >
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< p > This work was published in the Journal of Statistical Software
(Volume 104(3); < a href = "https://doi.org/10.18637/jss.v104.i03" class = "external-link" > DOI
10.18637/jss.v104.i03< / a > ) and formed the basis of two PhD theses (< a href = "https://doi.org/10.33612/diss.177417131" class = "external-link" > DOI
10.33612/diss.177417131< / a > and < a href = "https://doi.org/10.33612/diss.192486375" class = "external-link" > DOI
10.33612/diss.192486375< / a > ).< / p >
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< p > After installing this package, R knows ~52 000 distinct microbial
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species and all ~600 antibiotic, antimycotic and antiviral drugs by name
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and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED
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CT), and knows all about valid SIR and MIC values. The integral
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breakpoint guidelines from CLSI and EUCAST are included from the last 10
years. It supports and can read any data format, including WHONET
data.< / p >
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< p > With the help of contributors from all corners of the world, the
< code > AMR< / code > package is available in English, Czech, Chinese,
Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese,
Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish,
Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial
microorganism names are provided in these languages.< / p >
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< p > This package is fully independent of any other R package and works on
Windows, macOS and Linux with all versions of R since R-3.0 (April
2013). < strong > It was designed to work in any setting, including those
with very limited resources< / strong > . Since its first public release in
early 2018, this package has been downloaded from more than 175
countries.< / p >
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< p > This package can be used for:< / p >
< ul >
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< li > Reference for the taxonomy of microorganisms, since the package
contains all microbial (sub)species from the List of Prokaryotic names
with Standing in Nomenclature (LPSN) and the Global Biodiversity
Information Facility (GBIF)< / li >
< li > Interpreting raw MIC and disk diffusion values, based on the latest
CLSI or EUCAST guidelines< / li >
< li > Retrieving antimicrobial drug names, doses and forms of
administration from clinical health care records< / li >
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< li > Determining first isolates to be used for AMR data analysis< / li >
< li > Calculating antimicrobial resistance< / li >
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< li > Determining multi-drug resistance (MDR) / multi-drug resistant
organisms (MDRO)< / li >
< li > Calculating (empirical) susceptibility of both mono therapy and
combination therapies< / li >
< li > Predicting future antimicrobial resistance using regression
models< / li >
< li > Getting properties for any microorganism (like Gram stain, species,
genus or family)< / li >
< li > Getting properties for any antibiotic (like name, code of
EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)< / li >
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< li > Plotting antimicrobial resistance< / li >
< li > Applying EUCAST expert rules< / li >
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< li > Getting SNOMED codes of a microorganism, or getting properties of a
microorganism based on a SNOMED code< / li >
< li > Getting LOINC codes of an antibiotic, or getting properties of an
antibiotic based on a LOINC code< / li >
< li > Machine reading the EUCAST and CLSI guidelines from 2011-2020 to
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translate MIC values and disk diffusion diameters to SIR< / li >
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< li > Principal component analysis for AMR< / li >
< / ul >
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< p > All reference data sets (about microorganisms, antibiotics, SIR
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interpretation, EUCAST rules, etc.) in this < code > AMR< / code > package are
publicly and freely available. We continually export our data sets to
formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat
files that are machine-readable and suitable for input in any software
program, such as laboratory information systems. Please find < a href = "https://msberends.github.io/AMR/articles/datasets.html" > all
download links on our website< / a > , which is automatically updated with
every code change.< / p >
< p > This R package was created for both routine data analysis and
academic research at the Faculty of Medical Sciences of the < a href = "https://www.rug.nl" class = "external-link" > University of Groningen< / a > , in collaboration
with non-profit organisations < a href = "https://www.certe.nl" class = "external-link" > Certe
Medical Diagnostics and Advice Foundation< / a > and < a href = "https://www.umcg.nl" class = "external-link" > University Medical Center Groningen< / a > , and
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is being < a href = "https://msberends.github.io/AMR/news/" > actively and
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durably maintained< / a > by two public healthcare organisations in the
Netherlands.< / p >
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< hr >
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< p > < small > This AMR package for R is free, open-source software and
licensed under the < a href = "https://msberends.github.io/AMR/LICENSE-text.html" > GNU General
Public License v2.0 (GPL-2)< / a > . These requirements are consequently
legally binding: modifications must be released under the same license
when distributing the package, changes made to the code must be
documented, source code must be made available when the package is
distributed, and a copy of the license and copyright notice must be
included with the package. < / small > < / p >
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< p > < / p >
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< p > < code > AMR< / code > (for R). Free and open-source, licenced under the < a target = "_blank" href = "https://github.com/msberends/AMR/blob/main/LICENSE" class = "external-link" > GNU General Public License version 2.0 (GPL-2)< / a > .< br > Developed at the < a target = "_blank" href = "https://www.rug.nl" class = "external-link" > University of Groningen< / a > and < a target = "_blank" href = "https://www.umcg.nl" class = "external-link" > University Medical Center Groningen< / a > in The Netherlands.< / p >
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