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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.0.0.9025</small>
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<a class="dropdown-item" href="../articles/AMR.html">
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Conduct AMR Analysis
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Get Properties of an Antibiotic Drug
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<main id="main" class="col-md-9"><div class="page-header">
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<img src="../logo.svg" class="logo" alt=""><h1>Welcome to the `AMR` 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="d-none name"><code>welcome_to_AMR.Rmd</code></div>
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</div>
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<p>Note: to keep the package size as small as possible, we only included
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this vignette on CRAN. You can read more vignettes on our website about
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how to conduct AMR data analysis, determine MDROs, find explanation of
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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>The <code>AMR</code> package is a <a href="https://msberends.github.io/AMR/#copyright">free and
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open-source</a> R package with <a href="https://en.wikipedia.org/wiki/Dependency_hell" class="external-link">zero
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dependencies</a> to simplify the analysis and prediction of
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Antimicrobial Resistance (AMR) and to work with microbial and
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antimicrobial data and properties, by using evidence-based methods.
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<strong>Our aim is to provide a standard</strong> for clean and
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reproducible AMR data analysis, that can therefore empower
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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
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researchers</a> from around the globe are continually helping us to make
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this a successful and durable project!</p>
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<p>This work was published in the Journal of Statistical Software
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(Volume 104(3); <a href="https://doi.org/10.18637/jss.v104.i03" class="external-link">DOI
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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
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10.33612/diss.177417131</a> and <a href="https://doi.org/10.33612/diss.192486375" class="external-link">DOI
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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
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years. It supports and can read any data format, including WHONET
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data.</p>
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<p>With the help of contributors from all corners of the world, the
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<code>AMR</code> package is available in English, Czech, Chinese,
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Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese,
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Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish,
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Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial
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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
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Windows, macOS and Linux with all versions of R since R-3.0 (April
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2013). <strong>It was designed to work in any setting, including those
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with very limited resources</strong>. Since its first public release in
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early 2018, this package has been downloaded from more than 175
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countries.</p>
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<p>This package can be used for:</p>
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<ul>
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<li>Reference for the taxonomy of microorganisms, since the package
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contains all microbial (sub)species from the List of Prokaryotic names
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with Standing in Nomenclature (LPSN) and the Global Biodiversity
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Information Facility (GBIF)</li>
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<li>Interpreting raw MIC and disk diffusion values, based on the latest
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CLSI or EUCAST guidelines</li>
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<li>Retrieving antimicrobial drug names, doses and forms of
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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
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organisms (MDRO)</li>
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<li>Calculating (empirical) susceptibility of both mono therapy and
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combination therapies</li>
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<li>Predicting future antimicrobial resistance using regression
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models</li>
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<li>Getting properties for any microorganism (like Gram stain, species,
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genus or family)</li>
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<li>Getting properties for any antibiotic (like name, code of
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EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)</li>
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<li>Plotting antimicrobial resistance</li>
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<li>Applying EUCAST expert rules</li>
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<li>Getting SNOMED codes of a microorganism, or getting properties of a
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microorganism based on a SNOMED code</li>
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<li>Getting LOINC codes of an antibiotic, or getting properties of an
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antibiotic based on a LOINC code</li>
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<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>
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</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
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publicly and freely available. We continually export our data sets to
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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>
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<p>This R package was created for both routine data analysis and
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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
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with non-profit organisations <a href="https://www.certe.nl" class="external-link">Certe
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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
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Netherlands.</p>
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<hr>
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<p><small> This AMR package for R is free, open-source software and
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licensed under the <a href="https://msberends.github.io/AMR/LICENSE-text.html">GNU General
|
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Public License v2.0 (GPL-2)</a>. These requirements are consequently
|
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legally binding: modifications must be released under the same license
|
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when distributing the package, changes made to the code must be
|
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documented, source code must be made available when the package is
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distributed, and a copy of the license and copyright notice must be
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included with the package. </small></p>
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</main>
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<footer><div class="pkgdown-footer-left">
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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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<p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/logos/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/logos/logo_umcg.svg" style="max-width: 150px;"></a></p>
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