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Conduct AMR analysis
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Predict antimicrobial resistance
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Data sets for download / own use
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Conduct principal component analysis for AMR
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Determine multi-drug resistance (MDR)
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Work with WHONET data
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Import data from SPSS/SAS/Stata
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Apply EUCAST rules
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Get properties of a microorganism
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Get properties of an antibiotic
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Other: benchmarks
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< h1 data-toc-skip > Welcome to the < code > AMR< / code > package< / h1 >
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< 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 >
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< div class = "hidden name" > < code > welcome_to_AMR.Rmd< / code > < / div >
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< p > Note: to keep the package size as small as possible, we only included
this vignette on CRAN. You can read more vignettes on our website about
how to conduct AMR data analysis, determine MDRO’
EUCAST rules, 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 > < code > AMR< / code > is a free, open-source and independent R package
(see < a href = "https://msberends.github.io/AMR/#copyright" > Copyright< / 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 antimicrobial resistance
data analysis, that can therefore empower epidemiological analyses to
continuously enable surveillance and treatment evaluation in any
setting.< / p >
< p > After installing this package, R knows ~71,000 distinct microbial
species and all ~570 antibiotic, antimycotic and antiviral drugs by name
and code (including ATC, EARS-Net, PubChem, LOINC and SNOMED CT), and
knows all about valid R/SI and MIC values. It supports any data format,
including WHONET/EARS-Net data.< / p >
< p > The < code > AMR< / code > package is available in Danish, Dutch, English,
French, German, Italian, Portuguese, Russian, Spanish and Swedish.
Antimicrobial drug (group) names and colloquial microorganism names are
provided in these languages.< / p >
< 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 Catalogue of Life and List
of Prokaryotic names with Standing in Nomenclature< / 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 >
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< 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
translate MIC values and disk diffusion diameters to R/SI< / 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, R/SI
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 > . This
R package 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 > ) but is actively and durably maintained (see
< a href = "https://msberends.github.io/AMR/news/index.html" > changelog)< / a > )
by two public healthcare organisations in the Netherlands.< / p >
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< p > Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.< / p >
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< p > Site built with < a href = "https://pkgdown.r-lib.org/" class = "external-link" > pkgdown< / a >
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