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404.html
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@@ -31,7 +31,7 @@
<a class="navbar-brand me-2" href="https://amr-for-r.org/index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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CLAUDE.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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2
LICENSE-text.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

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articles/AMR.html
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -91,7 +91,7 @@
website update since they are based on randomly created values and the
page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
Markdown</a>. However, the methodology remains unchanged. This page was
generated on 20 August 2026.</p>
generated on 03 September 2026.</p>
<div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
@@ -147,21 +147,21 @@ make the structure of your data generally look like this:</p>
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2026-08-20</td>
<td align="center">2026-09-03</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="center">2026-08-20</td>
<td align="center">2026-09-03</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="center">2026-08-20</td>
<td align="center">2026-09-03</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>

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articles/AMR.md
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@@ -3,7 +3,7 @@
**Note:** values on this page will change with every website update
since they are based on randomly created values and the page was written
in [R Markdown](https://rmarkdown.rstudio.com/). However, the
methodology remains unchanged. This page was generated on 20 August
methodology remains unchanged. This page was generated on 03 September
2026.
## Introduction
@@ -52,9 +52,9 @@ structure of your data generally look like this:
| date | patient_id | mo | AMX | CIP |
|:----------:|:----------:|:----------------:|:---:|:---:|
| 2026-08-20 | abcd | Escherichia coli | S | S |
| 2026-08-20 | abcd | Escherichia coli | S | R |
| 2026-08-20 | efgh | Escherichia coli | R | S |
| 2026-09-03 | abcd | Escherichia coli | S | S |
| 2026-09-03 | abcd | Escherichia coli | S | R |
| 2026-09-03 | efgh | Escherichia coli | R | S |
### Needed R packages

2
articles/AMR_for_Python.html
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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2
articles/AMR_with_tidymodels.html
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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2
articles/EUCAST.html
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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2
articles/PCA.html
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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2
articles/WHONET.html
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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2
articles/WISCA.html
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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10
articles/datasets.html
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@@ -30,7 +30,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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@@ -80,7 +80,7 @@
<main id="main" class="col-md-9"><div class="page-header">
<img src="../logo.svg" class="logo" alt=""><h1>Download data sets for download / own use</h1>
<h4 data-toc-skip class="date">20 August 2026</h4>
<h4 data-toc-skip class="date">03 September 2026</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
<div class="d-none name"><code>datasets.Rmd</code></div>
@@ -893,11 +893,11 @@ DTA file</a> (82 kB)</li>
<code>intrinsic_resistant</code>: Intrinsic Bacterial
Resistance<a class="anchor" aria-label="anchor" href="#intrinsic_resistant-intrinsic-bacterial-resistance"></a>
</h2>
<p>A data set with 294 079 rows and 2 columns, containing the following
column names:<br><em>mo</em> and <em>ab</em>.</p>
<p>A data set with 294 079 rows and 3 columns, containing the following
column names:<br><em>mo</em>, <em>ab</em>, and <em>version</em>.</p>
<p>This data set is in R available as <code>intrinsic_resistant</code>,
after you load the <code>AMR</code> package.</p>
<p>It was last updated on 22 June 2026 23:38:13 UTC. Find more info
<p>It was last updated on 3 September 2026 10:14:25 UTC. Find more info
about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/intrinsic_resistant.html">data set
here</a>.</p>
<p><strong>Direct download links:</strong></p>

8
articles/datasets.md
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@@ -249,15 +249,15 @@ here](https://amr-for-r.org/reference/microorganisms.groups.html).
## `intrinsic_resistant`: Intrinsic Bacterial Resistance
A data set with 294 079 rows and 2 columns, containing the following
A data set with 294 079 rows and 3 columns, containing the following
column names:
*mo* and *ab*.
*mo*, *ab*, and *version*.
This data set is in R available as `intrinsic_resistant`, after you load
the `AMR` package.
It was last updated on 22 June 2026 23:38:13 UTC. Find more info about
the contents, (scientific) source, and structure of this [data set
It was last updated on 3 September 2026 10:14:25 UTC. Find more info
about the contents, (scientific) source, and structure of this [data set
here](https://amr-for-r.org/reference/intrinsic_resistant.html).
**Direct download links:**

2
articles/index.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
authors.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

84
index.html
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@@ -33,7 +33,7 @@
<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -113,7 +113,7 @@
</h2>
<p>The <code>AMR</code> package is a peer-reviewed, <a href="#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.</p>
<p><strong>Our aim has always been to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. We are a team of <a href="./authors.html">many different researchers</a> from around the globe to make this a successful and durable project! The <code>AMR</code> package was already cited <a href="https://scholar.google.com/citations?view_op=view_citation&amp;hl=en&amp;citation_for_view=sAoHvIgAAAAJ:0EnyYjriUFMC" class="external-link">over 100 times</a> in scientific research.</p>
<p>After installing this package, R knows <a href="./reference/microorganisms.html"><strong>~97 000 distinct microbial species</strong></a> (updated mei 2026) and all <a href="./reference/antimicrobials.html"><strong>~620 antimicrobial and antiviral drugs</strong></a> by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI 2011-2026 and EUCAST 2011-2026 are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package 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>. It 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> and the <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>.</p>
<p>After installing this package, R knows <a href="./reference/microorganisms.html"><strong>~97 000 distinct microbial species</strong></a> (updated May 2026) and all <a href="./reference/antimicrobials.html"><strong>~620 antimicrobial and antiviral drugs</strong></a> by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI 2011-2026 and EUCAST 2011-2026 are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package 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>. It 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> and the <a href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>.</p>
<div class="section level3">
<h3 id="used-in-over-175-countries-available-in-28-languages">Used in over 175 countries, available in 28 languages<a class="anchor" aria-label="anchor" href="#used-in-over-175-countries-available-in-28-languages"></a>
</h3>
@@ -146,13 +146,11 @@
<span><span class="co">#&gt; ℹ Using column mo as input for `mo_fullname()`</span></span>
<span><span class="co">#&gt; ℹ Using column mo as input for `mo_is_gram_negative()`</span></span>
<span><span class="co">#&gt; ℹ Using column mo as input for `mo_is_intrinsic_resistant()`</span></span>
<span><span class="co">#&gt; ℹ Determining intrinsic resistance based on 'EUCAST Expected</span></span>
<span><span class="co">#&gt; Resistant Phenotypes' v1.2 (2023). This note will be shown</span></span>
<span><span class="co">#&gt; once per session.</span></span>
<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB</span></span>
<span><span class="co">#&gt; (tobramycin), AMK (amikacin), and KAN (kanamycin)</span></span>
<span><span class="co">#&gt; ℹ For `carbapenems()` using columns IPM (imipenem) and MEM</span></span>
<span><span class="co">#&gt; (meropenem)</span></span>
<span><span class="co">#&gt; ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant Phenotypes' v1.2 (2023).</span></span>
<span><span class="co">#&gt; This note will be shown once per session.</span></span>
<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN</span></span>
<span><span class="co">#&gt; (kanamycin)</span></span>
<span><span class="co">#&gt; ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)</span></span>
<span><span class="co">#&gt; # A tibble: 35 × 7</span></span>
<span><span class="co">#&gt; bacteria GEN TOB AMK KAN IPM MEM </span></span>
<span><span class="co">#&gt; &lt;chr&gt; &lt;sir&gt; &lt;sir&gt; &lt;sir&gt; &lt;sir&gt; &lt;sir&gt; &lt;sir&gt;</span></span>
@@ -181,9 +179,9 @@
<span><span class="co">#&gt; Warning: invalid microorganism code, NA generated</span></span></code></pre></div>
<table class="table">
<colgroup>
<col width="24%">
<col width="37%">
<col width="37%">
<col width="33%">
<col width="33%">
<col width="33%">
</colgroup>
<thead><tr>
<th align="left">Piperacillin/tazobactam</th>
@@ -191,9 +189,9 @@
<th align="left">Piperacillin/tazobactam + Tobramycin</th>
</tr></thead>
<tbody><tr>
<td align="left">70% (64.8-75.1%)</td>
<td align="left">70.2% (64.6-75.4%)</td>
<td align="left">93.6% (92.1-95%)</td>
<td align="left">89.9% (86.9-92.3%)</td>
<td align="left">89.9% (87-92.5%)</td>
</tr></tbody>
</table>
<p>WISCA supports stratification by any clinical variable, so you can generate syndrome-specific or ward-specific coverage estimates:</p>
@@ -205,10 +203,10 @@
<span><span class="co">#&gt; Warning: invalid microorganism code, NA generated</span></span></code></pre></div>
<table class="table">
<colgroup>
<col width="14%">
<col width="21%">
<col width="32%">
<col width="32%">
<col width="25%">
<col width="25%">
<col width="25%">
<col width="25%">
</colgroup>
<thead><tr>
<th align="left">Syndromic Group</th>
@@ -219,21 +217,21 @@
<tbody>
<tr>
<td align="left">Clinical</td>
<td align="left">74.7% (69-80.3%)</td>
<td align="left">93.6% (92-95.2%)</td>
<td align="left">90.4% (86.8-93.1%)</td>
<td align="left">74.7% (68.9-80.8%)</td>
<td align="left">93.7% (92.1-95.2%)</td>
<td align="left">90.5% (87-93.2%)</td>
</tr>
<tr>
<td align="left">ICU</td>
<td align="left">56.9% (48.7-66%)</td>
<td align="left">86.8% (83.6-90%)</td>
<td align="left">82.8% (78.3-87.3%)</td>
<td align="left">57% (48.2-65.7%)</td>
<td align="left">86.8% (83.4-89.8%)</td>
<td align="left">83% (78-87.6%)</td>
</tr>
<tr>
<td align="left">Outpatient</td>
<td align="left">57.2% (46-68.2%)</td>
<td align="left">76.5% (70.3-82.2%)</td>
<td align="left">67.7% (57.3-77.2%)</td>
<td align="left">57.2% (46.2-68.9%)</td>
<td align="left">76.6% (70.1-82.1%)</td>
<td align="left">67.7% (57.6-77.5%)</td>
</tr>
</tbody>
</table>
@@ -242,15 +240,14 @@
<code class="sourceCode R"><span><span class="fu"><a href="reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
<span> mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>,</span>
<span> antimicrobials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"AMC"</span>, <span class="fu"><a href="reference/antimicrobial_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span>, <span class="st">"TZP"</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ For `carbapenems()` using columns IPM (imipenem) and MEM</span></span>
<span><span class="co">#&gt; (meropenem)</span></span></code></pre></div>
<span><span class="co">#&gt; ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)</span></span></code></pre></div>
<table class="table">
<colgroup>
<col width="13%">
<col width="25%">
<col width="18%">
<col width="19%">
<col width="22%">
<col width="20%">
<col width="20%">
<col width="20%">
<col width="20%">
<col width="20%">
</colgroup>
<thead><tr>
<th align="left">Pathogen</th>
@@ -283,10 +280,10 @@
<span> antimicrobials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"TZP"</span>, <span class="st">"TZP+TOB"</span>, <span class="st">"TZP+GEN"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<table class="table">
<colgroup>
<col width="12%">
<col width="21%">
<col width="32%">
<col width="32%">
<col width="25%">
<col width="25%">
<col width="25%">
<col width="25%">
</colgroup>
<thead><tr>
<th align="left">Pathogen</th>
@@ -408,16 +405,15 @@
<span> <span class="co"># calculate AMR using resistance(), over all aminoglycosides and polymyxins:</span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="reference/antimicrobial_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="reference/antimicrobial_selectors.html">polymyxins</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>,</span>
<span> <span class="va">resistance</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB</span></span>
<span><span class="co">#&gt; (tobramycin), AMK (amikacin), and KAN (kanamycin)</span></span>
<span><span class="co">#&gt; ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN</span></span>
<span><span class="co">#&gt; (kanamycin)</span></span>
<span><span class="co">#&gt; ℹ For `polymyxins()` using column COL (colistin)</span></span>
<span><span class="co">#&gt; Warning: There was 1 warning in `summarise()`.</span></span>
<span><span class="co">#&gt; ℹ In argument: `across(c(aminoglycosides(), polymyxins()),</span></span>
<span><span class="co">#&gt; resistance)`.</span></span>
<span><span class="co">#&gt; ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.</span></span>
<span><span class="co">#&gt; ℹ In group 3: `ward = "Outpatient"`.</span></span>
<span><span class="co">#&gt; Caused by warning:</span></span>
<span><span class="co">#&gt; ! Introducing NA: only 23 results available for KAN in group:</span></span>
<span><span class="co">#&gt; ward = "Outpatient" (whilst `minimum = 30`).</span></span>
<span><span class="co">#&gt; ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" (whilst `minimum =</span></span>
<span><span class="co">#&gt; 30`).</span></span>
<span><span class="va">out</span></span>
<span><span class="co">#&gt; # A tibble: 3 × 6</span></span>
<span><span class="co">#&gt; ward GEN TOB AMK KAN COL</span></span>

36
index.md
View File

@@ -50,7 +50,7 @@ in scientific research.
After installing this package, R knows [**~97 000 distinct microbial
species**](https://amr-for-r.org/reference/microorganisms.md) (updated
mei 2026) and all [**~620 antimicrobial and antiviral
May 2026) and all [**~620 antimicrobial and antiviral
drugs**](https://amr-for-r.org/reference/antimicrobials.md) by name and
code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED
CT), and knows all about valid SIR and MIC values. The integral clinical
@@ -116,13 +116,11 @@ example_isolates %>%
#> ℹ Using column mo as input for `mo_fullname()`
#> ℹ Using column mo as input for `mo_is_gram_negative()`
#> ℹ Using column mo as input for `mo_is_intrinsic_resistant()`
#> ℹ Determining intrinsic resistance based on 'EUCAST Expected
#> Resistant Phenotypes' v1.2 (2023). This note will be shown
#> once per session.
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
#> (tobramycin), AMK (amikacin), and KAN (kanamycin)
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
#> (meropenem)
#> ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant Phenotypes' v1.2 (2023).
#> This note will be shown once per session.
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN
#> (kanamycin)
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
#> # A tibble: 35 × 7
#> bacteria GEN TOB AMK KAN IPM MEM
#> <chr> <sir> <sir> <sir> <sir> <sir> <sir>
@@ -181,7 +179,7 @@ wisca(example_isolates,
| Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:---|:---|:---|
| 70% (64.8-75.1%) | 93.6% (92.1-95%) | 89.9% (86.9-92.3%) |
| 70.2% (64.6-75.4%) | 93.6% (92.1-95%) | 89.9% (87-92.5%) |
WISCA supports stratification by any clinical variable, so you can
generate syndrome-specific or ward-specific coverage estimates:
@@ -197,9 +195,9 @@ wisca(example_isolates,
| Syndromic Group | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:---|:---|:---|:---|
| Clinical | 74.7% (69-80.3%) | 93.6% (92-95.2%) | 90.4% (86.8-93.1%) |
| ICU | 56.9% (48.7-66%) | 86.8% (83.6-90%) | 82.8% (78.3-87.3%) |
| Outpatient | 57.2% (46-68.2%) | 76.5% (70.3-82.2%) | 67.7% (57.3-77.2%) |
| Clinical | 74.7% (68.9-80.8%) | 93.7% (92.1-95.2%) | 90.5% (87-93.2%) |
| ICU | 57% (48.2-65.7%) | 86.8% (83.4-89.8%) | 83% (78-87.6%) |
| Outpatient | 57.2% (46.2-68.9%) | 76.6% (70.1-82.1%) | 67.7% (57.6-77.5%) |
**For AMR surveillance**, traditional antibiograms remain the right tool
for tracking resistance per species over time:
@@ -209,8 +207,7 @@ for tracking resistance per species over time:
antibiogram(example_isolates,
mo_transform = "gramstain",
antimicrobials = c("AMC", carbapenems(), "TZP"))
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
#> (meropenem)
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
```
| Pathogen | Amoxicillin/clavulanic acid | Imipenem | Meropenem | Piperacillin/tazobactam |
@@ -331,16 +328,15 @@ out <- example_isolates %>%
# calculate AMR using resistance(), over all aminoglycosides and polymyxins:
summarise(across(c(aminoglycosides(), polymyxins()),
resistance))
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
#> (tobramycin), AMK (amikacin), and KAN (kanamycin)
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN
#> (kanamycin)
#> ℹ For `polymyxins()` using column COL (colistin)
#> Warning: There was 1 warning in `summarise()`.
#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()),
#> resistance)`.
#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.
#> ℹ In group 3: `ward = "Outpatient"`.
#> Caused by warning:
#> ! Introducing NA: only 23 results available for KAN in group:
#> ward = "Outpatient" (whilst `minimum = 30`).
#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" (whilst `minimum =
#> 30`).
out
#> # A tibble: 3 × 6
#> ward GEN TOB AMK KAN COL

36
llms.txt
View File

@@ -50,7 +50,7 @@ in scientific research.
After installing this package, R knows [**~97 000 distinct microbial
species**](https://amr-for-r.org/reference/microorganisms.md) (updated
mei 2026) and all [**~620 antimicrobial and antiviral
May 2026) and all [**~620 antimicrobial and antiviral
drugs**](https://amr-for-r.org/reference/antimicrobials.md) by name and
code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED
CT), and knows all about valid SIR and MIC values. The integral clinical
@@ -116,13 +116,11 @@ example_isolates %>%
#> ℹ Using column mo as input for `mo_fullname()`
#> ℹ Using column mo as input for `mo_is_gram_negative()`
#> ℹ Using column mo as input for `mo_is_intrinsic_resistant()`
#> ℹ Determining intrinsic resistance based on 'EUCAST Expected
#> Resistant Phenotypes' v1.2 (2023). This note will be shown
#> once per session.
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
#> (tobramycin), AMK (amikacin), and KAN (kanamycin)
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
#> (meropenem)
#> ℹ Determining intrinsic resistance based on 'EUCAST Expected Resistant Phenotypes' v1.2 (2023).
#> This note will be shown once per session.
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN
#> (kanamycin)
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
#> # A tibble: 35 × 7
#> bacteria GEN TOB AMK KAN IPM MEM
#> <chr> <sir> <sir> <sir> <sir> <sir> <sir>
@@ -181,7 +179,7 @@ wisca(example_isolates,
| Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:---|:---|:---|
| 70% (64.8-75.1%) | 93.6% (92.1-95%) | 89.9% (86.9-92.3%) |
| 70.2% (64.6-75.4%) | 93.6% (92.1-95%) | 89.9% (87-92.5%) |
WISCA supports stratification by any clinical variable, so you can
generate syndrome-specific or ward-specific coverage estimates:
@@ -197,9 +195,9 @@ wisca(example_isolates,
| Syndromic Group | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:---|:---|:---|:---|
| Clinical | 74.7% (69-80.3%) | 93.6% (92-95.2%) | 90.4% (86.8-93.1%) |
| ICU | 56.9% (48.7-66%) | 86.8% (83.6-90%) | 82.8% (78.3-87.3%) |
| Outpatient | 57.2% (46-68.2%) | 76.5% (70.3-82.2%) | 67.7% (57.3-77.2%) |
| Clinical | 74.7% (68.9-80.8%) | 93.7% (92.1-95.2%) | 90.5% (87-93.2%) |
| ICU | 57% (48.2-65.7%) | 86.8% (83.4-89.8%) | 83% (78-87.6%) |
| Outpatient | 57.2% (46.2-68.9%) | 76.6% (70.1-82.1%) | 67.7% (57.6-77.5%) |
**For AMR surveillance**, traditional antibiograms remain the right tool
for tracking resistance per species over time:
@@ -209,8 +207,7 @@ for tracking resistance per species over time:
antibiogram(example_isolates,
mo_transform = "gramstain",
antimicrobials = c("AMC", carbapenems(), "TZP"))
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM
#> (meropenem)
#> ℹ For `carbapenems()` using columns IPM (imipenem) and MEM (meropenem)
```
| Pathogen | Amoxicillin/clavulanic acid | Imipenem | Meropenem | Piperacillin/tazobactam |
@@ -331,16 +328,15 @@ out <- example_isolates %>%
# calculate AMR using resistance(), over all aminoglycosides and polymyxins:
summarise(across(c(aminoglycosides(), polymyxins()),
resistance))
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB
#> (tobramycin), AMK (amikacin), and KAN (kanamycin)
#> ℹ For `aminoglycosides()` using columns GEN (gentamicin), TOB (tobramycin), AMK (amikacin), and KAN
#> (kanamycin)
#> ℹ For `polymyxins()` using column COL (colistin)
#> Warning: There was 1 warning in `summarise()`.
#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()),
#> resistance)`.
#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.
#> ℹ In group 3: `ward = "Outpatient"`.
#> Caused by warning:
#> ! Introducing NA: only 23 results available for KAN in group:
#> ward = "Outpatient" (whilst `minimum = 30`).
#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" (whilst `minimum =
#> 30`).
out
#> # A tibble: 3 × 6
#> ward GEN TOB AMK KAN COL

12
news/index.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -49,10 +49,10 @@
</div>
<div class="section level2">
<h2 class="pkg-version" data-toc-text="3.0.1.9087" id="amr-3019087">AMR 3.0.1.9087<a class="anchor" aria-label="anchor" href="#amr-3019087"></a></h2>
<h2 class="pkg-version" data-toc-text="3.0.1.9088" id="amr-3019088">AMR 3.0.1.9088<a class="anchor" aria-label="anchor" href="#amr-3019088"></a></h2>
<p>Planned as v3.1.0, end of September 2026.</p>
<div class="section level4">
<h4 id="breaking-changes-3-0-1-9087">Breaking Changes<a class="anchor" aria-label="anchor" href="#breaking-changes-3-0-1-9087"></a></h4>
<h4 id="breaking-changes-3-0-1-9088">Breaking Changes<a class="anchor" aria-label="anchor" href="#breaking-changes-3-0-1-9088"></a></h4>
<ul><li>
<p>The former <em>kingdoms</em> Bacteria and Archaea are now each divided into four kingdoms with new top-level <em>domains</em> ‘Bacteria’ and ‘Archaea’ (Göker and Oren, 2024, DOI: 10.1099/ijsem.0.006242). Following this, a new <code>domain</code> column in the <code>microorganisms</code> data set was added, and more importantly, <code><a href="../reference/mo_property.html">mo_kingdom()</a></code> now returns the formal kingdom (e.g. <code>"Pseudomonadati"</code> instead of <code>"Bacteria"</code>). Use <code><a href="../reference/mo_property.html">mo_domain()</a></code> for the old behaviour. For non-prokaryotic kingdoms (Fungi, Protozoa, etc.), <code>kingdom</code> and <code>domain</code> are identical.</p>
<table class="table"><colgroup><col width="33%"><col width="29%"><col width="37%"></colgroup><thead><tr><th>
@@ -105,7 +105,7 @@
<li><p>Faster parallel computing via the <code>future</code> package for <code><a href="../reference/as.sir.html">as.sir()</a></code> and <code><a href="../reference/antibiogram.html">wisca()</a></code>: a non-sequential plan (e.g. <code>future::plan(future::multisession)</code>) must be active before using <code>parallel = TRUE</code>.</p></li>
</ul></div>
<div class="section level4">
<h4 id="new-3-0-1-9087">New<a class="anchor" aria-label="anchor" href="#new-3-0-1-9087"></a></h4>
<h4 id="new-3-0-1-9088">New<a class="anchor" aria-label="anchor" href="#new-3-0-1-9088"></a></h4>
<ul><li>EUCAST 2026 and CLSI 2026 breakpoints: over 5,700 new breakpoints added to the <code>clinical_breakpoints</code> data set; EUCAST 2026 is now the default for all MIC and disk diffusion interpretations</li>
<li>Wildtype/Non-wildtype (WT/NWT) output when using ECOFF-based interpretation, by setting <code>breakpoint_type = "ECOFF"</code> in <code><a href="../reference/as.sir.html">as.sir()</a></code>; WT/NWT results are fully supported in all resistance/susceptibility functions and plots (<a href="https://github.com/msberends/AMR/issues/254" class="external-link">#254</a>)</li>
<li>
@@ -122,7 +122,7 @@
<li>New <code><a href="../reference/antibiogram.html">wisca_plot()</a></code> to assess the susceptibility and incidence distributions from the Monte Carlo simulations</li>
</ul></div>
<div class="section level4">
<h4 id="fixed-3-0-1-9087">Fixed<a class="anchor" aria-label="anchor" href="#fixed-3-0-1-9087"></a></h4>
<h4 id="fixed-3-0-1-9088">Fixed<a class="anchor" aria-label="anchor" href="#fixed-3-0-1-9088"></a></h4>
<ul><li>Setting <code>options(AMR_guideline = "EUCAST 2012")</code> or any year-qualified value no longer causes errors or silent wrong behaviour in <code><a href="../reference/interpretive_rules.html">interpretive_rules()</a></code>, <code><a href="../reference/proportion.html">resistance()</a></code>, <code><a href="../reference/proportion.html">susceptibility()</a></code>, <code><a href="../reference/count.html">count_resistant()</a></code>, <code><a href="../reference/count.html">count_susceptible()</a></code>, and SIR plotting/printing functions (<a href="https://github.com/msberends/AMR/issues/298" class="external-link">#298</a>)</li>
<li>
<code><a href="../reference/as.sir.html">as.sir()</a></code>
@@ -151,7 +151,7 @@
</li>
</ul></div>
<div class="section level4">
<h4 id="updated-3-0-1-9087">Updated<a class="anchor" aria-label="anchor" href="#updated-3-0-1-9087"></a></h4>
<h4 id="updated-3-0-1-9088">Updated<a class="anchor" aria-label="anchor" href="#updated-3-0-1-9088"></a></h4>
<ul><li>
<code><a href="../reference/top_n_microorganisms.html">top_n_microorganisms()</a></code>: new <code>property_for_each</code> argument for sub-grouping within top <em>n</em> groups; rank ordering enforced (only lower taxonomic ranks allowed); fixed <code>property = NULL</code> not being accepted; inner filter now tracks original row indices to prevent cross-group contamination</li>
<li>Taxonomic update for all microorganisms, now updated to June 2026</li>

2
news/index.md
View File

@@ -1,6 +1,6 @@
# Changelog
## AMR 3.0.1.9087
## AMR 3.0.1.9088
Planned as v3.1.0, end of September 2026.

2
pkgdown.yml
View File

@@ -10,7 +10,7 @@ articles:
PCA: PCA.html
WHONET: WHONET.html
WISCA: WISCA.html
last_built: 2026-08-20T12:32Z
last_built: 2026-09-03T12:29Z
urls:
reference: https://amr-for-r.org/reference
article: https://amr-for-r.org/articles

2
reference/AMR-deprecated.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/AMR-options.html
View File

@@ -9,7 +9,7 @@ options(AMR_guideline = "CLSI")'><meta property="og:image" content="https://amr-
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

5
reference/AMR.html
View File

@@ -21,7 +21,7 @@ The AMR package is available in English, Arabic, Bengali, Chinese, Czech, Danish
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -112,7 +112,8 @@ The AMR package is available in English, Arabic, Bengali, Chinese, Czech, Danish
<div class="section level2">
<h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a></h2>
<p><strong>Maintainer</strong>: Matthijs S. Berends <a href="mailto:m.s.berends@umcg.nl">m.s.berends@umcg.nl</a> (<a href="https://orcid.org/0000-0001-7620-1800" class="external-link">ORCID</a>)</p>
<p>Authors:</p><ul><li><p>Dennis Souverein (<a href="https://orcid.org/0000-0003-0455-0336" class="external-link">ORCID</a>) [contributor]</p></li>
<p>Authors:</p><ul><li><p>Matthijs S. Berends <a href="mailto:m.s.berends@umcg.nl">m.s.berends@umcg.nl</a> (<a href="https://orcid.org/0000-0001-7620-1800" class="external-link">ORCID</a>)</p></li>
<li><p>Dennis Souverein (<a href="https://orcid.org/0000-0003-0455-0336" class="external-link">ORCID</a>) [contributor]</p></li>
<li><p>Erwin E. A. Hassing [contributor]</p></li>
</ul><p>Other contributors:</p><ul><li><p>Aislinn Cook (<a href="https://orcid.org/0000-0002-9189-7815" class="external-link">ORCID</a>) [contributor]</p></li>
<li><p>Andrew P. Norgan (<a href="https://orcid.org/0000-0002-2955-2066" class="external-link">ORCID</a>) [contributor]</p></li>

3
reference/AMR.md
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@@ -102,6 +102,9 @@ Useful links:
Authors:
- Matthijs S. Berends <m.s.berends@umcg.nl>
([ORCID](https://orcid.org/0000-0001-7620-1800))
- Dennis Souverein ([ORCID](https://orcid.org/0000-0003-0455-0336))
\[contributor\]

2
reference/WHOCC.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/WHONET.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">

2
reference/ab_from_text.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9088</small>
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2
reference/ab_property.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/add_custom_antimicrobials.html
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@@ -7,7 +7,7 @@
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2
reference/add_custom_microorganisms.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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22
reference/age.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@@ -112,16 +112,16 @@
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">df</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> birth_date age age_exact age_at_y2k</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 1999-06-30 27 27.13973 0</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1968-01-29 58 58.55616 31</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1965-12-05 60 60.70685 34</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1980-03-01 46 46.47123 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1949-11-01 76 76.80000 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1947-02-14 79 79.51233 52</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1940-02-19 86 86.49863 59</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1988-01-10 38 38.60822 11</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1997-08-27 28 28.98082 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1978-01-26 48 48.56438 21</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 1999-06-30 27 27.17808 0</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1968-01-29 58 58.59452 31</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1965-12-05 60 60.74521 34</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1980-03-01 46 46.50959 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1949-11-01 76 76.83836 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1947-02-14 79 79.55068 52</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1940-02-19 86 86.53699 59</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1988-01-10 38 38.64658 11</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1997-08-27 29 29.01918 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1978-01-26 48 48.60274 21</span>
</code></pre></div>
</div>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>

20
reference/age.md
View File

@@ -81,14 +81,14 @@ df$age_at_y2k <- age(df$birth_date, "2000-01-01")
df
#> birth_date age age_exact age_at_y2k
#> 1 1999-06-30 27 27.13973 0
#> 2 1968-01-29 58 58.55616 31
#> 3 1965-12-05 60 60.70685 34
#> 4 1980-03-01 46 46.47123 19
#> 5 1949-11-01 76 76.80000 50
#> 6 1947-02-14 79 79.51233 52
#> 7 1940-02-19 86 86.49863 59
#> 8 1988-01-10 38 38.60822 11
#> 9 1997-08-27 28 28.98082 2
#> 10 1978-01-26 48 48.56438 21
#> 1 1999-06-30 27 27.17808 0
#> 2 1968-01-29 58 58.59452 31
#> 3 1965-12-05 60 60.74521 34
#> 4 1980-03-01 46 46.50959 19
#> 5 1949-11-01 76 76.83836 50
#> 6 1947-02-14 79 79.55068 52
#> 7 1940-02-19 86 86.53699 59
#> 8 1988-01-10 38 38.64658 11
#> 9 1997-08-27 29 29.01918 2
#> 10 1978-01-26 48 48.60274 21
```

2
reference/age_groups.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
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reference/amr-tidymodels.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@@ -202,10 +202,10 @@ may affect the computations for subsequent operations.</p></dd>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">broom </span> 1.0.13 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">rsample </span> 1.3.2 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">dials </span> 1.4.4 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tailor </span> 0.1.0 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">infer </span> 1.1.0 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tidyr </span> 1.3.2 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">modeldata </span> 1.5.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tune </span> 2.1.0 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">modeldata </span> 1.6.0 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tune </span> 2.1.0 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">parsnip </span> 1.6.0 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">workflows </span> 1.3.0 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">purrr </span> 1.2.2 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">workflowsets</span> 1.1.1 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">recipes </span> 1.3.3 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">yardstick </span> 1.4.0 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">recipes </span> 1.4.0 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">yardstick </span> 1.4.0 </span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> ── <span style="font-weight: bold;">Conflicts</span> ───────────────────────────────────────── tidymodels_conflicts() ──</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">purrr</span>::<span style="color: #00BB00;">discard()</span> masks <span style="color: #0000BB;">scales</span>::discard()</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">dplyr</span>::<span style="color: #00BB00;">filter()</span> masks <span style="color: #0000BB;">stats</span>::filter()</span>

4
reference/amr-tidymodels.md
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@@ -181,10 +181,10 @@ if (require("tidymodels")) {
#> ✔ broom 1.0.13 ✔ rsample 1.3.2
#> ✔ dials 1.4.4 ✔ tailor 0.1.0
#> ✔ infer 1.1.0 ✔ tidyr 1.3.2
#> ✔ modeldata 1.5.1 ✔ tune 2.1.0
#> ✔ modeldata 1.6.0 ✔ tune 2.1.0
#> ✔ parsnip 1.6.0 ✔ workflows 1.3.0
#> ✔ purrr 1.2.2 ✔ workflowsets 1.1.1
#> ✔ recipes 1.3.3 ✔ yardstick 1.4.0
#> ✔ recipes 1.4.0 ✔ yardstick 1.4.0
#> ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
#> ✖ purrr::discard() masks scales::discard()
#> ✖ dplyr::filter() masks stats::filter()

2
reference/amr_course.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
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2
reference/antibiogram.html
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@@ -13,7 +13,7 @@ All antibiogram types adhere to previously described approaches (see Source), an
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/antimicrobial_selectors.html
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@@ -17,7 +17,7 @@ my_data_with_all_these_columns %&amp;gt;%
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/antimicrobials.html
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@@ -9,7 +9,7 @@ The antibiotics data set has been renamed to antimicrobials. The old name will b
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/as.ab.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/as.av.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
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6
reference/as.disk.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@@ -62,10 +62,6 @@
<span><span class="fu">is.disk</span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span></code></pre></div>
</div>
<div class="section level2">
<h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
<p>An object of class <code>disk</code> (inherits from <code>integer</code>) of length 1.</p>
</div>
<div class="section level2">
<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>

4
reference/as.disk.md
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@@ -14,10 +14,6 @@ NA_disk_
is.disk(x)
```
## Format
An object of class `disk` (inherits from `integer`) of length 1.
## Arguments
- x:

2
reference/as.mic.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/as.mo.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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10
reference/as.sir.html
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@@ -9,7 +9,7 @@ Breakpoints are currently implemented from EUCAST 2011-2026 and CLSI 2011-2026,
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@@ -462,10 +462,10 @@ Breakpoints are currently implemented from EUCAST 2011-2026 and CLSI 2011-2026,
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 4 × 18</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> datetime index method ab_given mo_given host_given input_given</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2026-08-20 <span style="color: #949494;">12:34:53</span> 1 MIC amoxicillin Escherich… human 8 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2026-08-20 <span style="color: #949494;">12:34:53</span> 1 MIC cipro Escherich… human 0.256 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> 2026-08-20 <span style="color: #949494;">12:34:53</span> 1 DISK tobra Escherich… human 16 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> 2026-08-20 <span style="color: #949494;">12:34:53</span> 1 DISK genta Escherich… human 18 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2026-09-03 <span style="color: #949494;">12:31:42</span> 1 MIC amoxicillin Escherich… human 8 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2026-09-03 <span style="color: #949494;">12:31:42</span> 1 MIC cipro Escherich… human 0.256 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> 2026-09-03 <span style="color: #949494;">12:31:42</span> 1 DISK tobra Escherich… human 16 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> 2026-09-03 <span style="color: #949494;">12:31:43</span> 1 DISK genta Escherich… human 18 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 11 more variables: ab &lt;ab&gt;, mo &lt;mo&gt;, host &lt;chr&gt;, input &lt;chr&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># outcome &lt;sir&gt;, notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># breakpoint_S_R &lt;chr&gt;, site &lt;chr&gt;</span></span>

8
reference/as.sir.md
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@@ -712,10 +712,10 @@ sir_interpretation_history()
#> # A tibble: 4 × 18
#> datetime index method ab_given mo_given host_given input_given
#> <dttm> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 2026-08-20 12:34:53 1 MIC amoxicillin Escherich… human 8
#> 2 2026-08-20 12:34:53 1 MIC cipro Escherich… human 0.256
#> 3 2026-08-20 12:34:53 1 DISK tobra Escherich… human 16
#> 4 2026-08-20 12:34:53 1 DISK genta Escherich… human 18
#> 1 2026-09-03 12:31:42 1 MIC amoxicillin Escherich… human 8
#> 2 2026-09-03 12:31:42 1 MIC cipro Escherich… human 0.256
#> 3 2026-09-03 12:31:42 1 DISK tobra Escherich… human 16
#> 4 2026-09-03 12:31:43 1 DISK genta Escherich… human 18
#> # ℹ 11 more variables: ab <ab>, mo <mo>, host <chr>, input <chr>,
#> # outcome <sir>, notes <chr>, guideline <chr>, ref_table <chr>, uti <lgl>,
#> # breakpoint_S_R <chr>, site <chr>

2
reference/atc_online.html
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@@ -7,7 +7,7 @@
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reference/av_from_text.html
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@@ -7,7 +7,7 @@
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@@ -7,7 +7,7 @@
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reference/availability.html
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@@ -7,7 +7,7 @@
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reference/bug_drug_combinations.html
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@@ -7,7 +7,7 @@
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7
reference/clinical_breakpoints.html
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@@ -21,7 +21,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@@ -108,7 +108,10 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
<h3 id="imported-from-whonet">Imported From WHONET<a class="anchor" aria-label="anchor" href="#imported-from-whonet"></a></h3>
<p>Clinical breakpoints in this package were validated through and imported from <a href="https://whonet.org" class="external-link">WHONET</a>, a free desktop Windows application developed and supported by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance. More can be read on <a href="https://whonet.org" class="external-link">their website</a>. The developers of WHONET and this <code>AMR</code> package have been in contact about sharing their work. We highly appreciate their great development on the WHONET software.</p>
<p>Some breakpoints in this package were validated through and imported from <a href="https://whonet.org" class="external-link">WHONET</a>, a free desktop Windows application developed and supported by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance. More can be read on <a href="https://whonet.org" class="external-link">their website</a>. The developers of WHONET and this <code>AMR</code> package have been in contact about sharing their work. We highly appreciate their great development on the WHONET software.</p>
<p>From WHONET, imported were:</p><ul><li><p>All CLSI breakpoints, including ECOFF</p></li>
<li><p>EUCAST breakpoints between 2011 and 2018</p></li>
</ul><p>EUCAST breakpoints from 2019 onwards, were retrieved directly from <a href="https://www.eucast.org" class="external-link">https://www.eucast.org</a>.</p>
<p>Our import and reproduction script can be found here: <a href="https://github.com/msberends/AMR/blob/main/data-raw/_reproduction_scripts/reproduction_of_clinical_breakpoints.R" class="external-link">https://github.com/msberends/AMR/blob/main/data-raw/_reproduction_scripts/reproduction_of_clinical_breakpoints.R</a>.</p>
</div>

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reference/clinical_breakpoints.md
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@@ -100,7 +100,7 @@ to interpret raw data using a specific breakpoint type, e.g.
### Imported From WHONET
Clinical breakpoints in this package were validated through and imported
Some breakpoints in this package were validated through and imported
from [WHONET](https://whonet.org), a free desktop Windows application
developed and supported by the WHO Collaborating Centre for Surveillance
of Antimicrobial Resistance. More can be read on [their
@@ -108,6 +108,15 @@ website](https://whonet.org). The developers of WHONET and this `AMR`
package have been in contact about sharing their work. We highly
appreciate their great development on the WHONET software.
From WHONET, imported were:
- All CLSI breakpoints, including ECOFF
- EUCAST breakpoints between 2011 and 2018
EUCAST breakpoints from 2019 onwards, were retrieved directly from
<https://www.eucast.org>.
Our import and reproduction script can be found here:
<https://github.com/msberends/AMR/blob/main/data-raw/_reproduction_scripts/reproduction_of_clinical_breakpoints.R>.

2
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@@ -9,7 +9,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/custom_interpretive_rules.html
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@@ -7,7 +7,7 @@
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@@ -7,7 +7,7 @@
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reference/dosage.html
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@@ -7,7 +7,7 @@
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reference/esbl_isolates.html
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@@ -7,7 +7,7 @@
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reference/example_isolates.html
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@@ -7,7 +7,7 @@
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@@ -7,7 +7,7 @@
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@@ -7,7 +7,7 @@
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reference/first_isolate.html
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@@ -9,7 +9,7 @@
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reference/g.test.html
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@@ -7,7 +7,7 @@
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reference/get_episode.html
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@@ -7,7 +7,7 @@
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reference/ggplot_pca.html
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@@ -7,7 +7,7 @@
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reference/ggplot_sir.html
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@@ -7,7 +7,7 @@
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reference/guess_ab_col.html
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@@ -7,7 +7,7 @@
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2
reference/index.html
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@@ -7,7 +7,7 @@
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reference/interpretive_rules.html
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@@ -9,7 +9,7 @@ To improve the interpretation of the antibiogram before CLSI/EUCAST interpretive
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33
reference/intrinsic_resistant.html
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@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
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@@ -60,12 +60,13 @@
<div class="section level2">
<h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
<p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 294 079 observations and 2 variables:</p><ul><li><p><code>mo</code><br> Microorganism ID which occurs in <code><a href="microorganisms.html">microorganisms$mo</a></code>. Names can be retrieved using <code><a href="mo_property.html">mo_name()</a></code>.</p></li>
<p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 294 079 observations and 3 variables:</p><ul><li><p><code>mo</code><br> Microorganism ID which occurs in <code><a href="microorganisms.html">microorganisms$mo</a></code>. Names can be retrieved using <code><a href="mo_property.html">mo_name()</a></code>.</p></li>
<li><p><code>ab</code><br> Antimicrobial ID which occurs in <code><a href="antimicrobials.html">antimicrobials$ab</a></code>. Names can be retrieved using <code><a href="ab_property.html">ab_name()</a></code>.</p></li>
<li><p><code>version</code><br> Guideline name and version.</p></li>
</ul></div>
<div class="section level2">
<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
<p>This data set is currently based on <a href="https://www.eucast.org/bacteria/important-additional-information/expert-rules/" class="external-link">'EUCAST Expected Resistant Phenotypes' v1.2</a> (2023).</p>
<p>This data set is currently strictly follows <a href="https://www.eucast.org/bacteria/important-additional-information/expert-rules/" class="external-link">'EUCAST Expected Resistant Phenotypes' v1.2</a> (2023). The</p>
<p>This data set is internally used by:</p><ul><li><p><code><a href="antimicrobial_selectors.html">not_intrinsic_resistant()</a></code> (an <a href="antimicrobial_selectors.html">antimicrobial selector</a>)</p></li>
<li><p><code><a href="mo_property.html">mo_is_intrinsic_resistant()</a></code></p></li>
<li><p><code><a href="antibiogram.html">wisca()</a></code> to model \(\beta(1, 9999)\) for resistant bug-drug combinations, per <a href="https://doi.org/10.1093/jac/dkv397" class="external-link">doi:10.1093/jac/dkv397</a></p></li>
@@ -82,19 +83,19 @@
<div class="section level2">
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">intrinsic_resistant</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 294,079 × 2</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> mo ab </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> <span style="color: #949494; font-style: italic;">&lt;ab&gt;</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> <span style="color: #949494;">B_</span>GRAMP ATM </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> <span style="color: #949494;">B_</span>GRAMP COL </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> <span style="color: #949494;">B_</span>GRAMP NAL </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> <span style="color: #949494;">B_</span>GRAMP PLB </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> <span style="color: #949494;">B_</span>GRAMP TEM </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> <span style="color: #949494;">B_</span>ANAER-POS ATM </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> <span style="color: #949494;">B_</span>ANAER-POS COL </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> <span style="color: #949494;">B_</span>ANAER-POS NAL </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> <span style="color: #949494;">B_</span>ANAER-POS PLB </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> <span style="color: #949494;">B_</span>ANAER-POS TEM </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 294,079 × 3</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> mo ab version </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> <span style="color: #949494; font-style: italic;">&lt;ab&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> <span style="color: #949494;">B_</span>GRAMP ATM 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> <span style="color: #949494;">B_</span>GRAMP COL 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> <span style="color: #949494;">B_</span>GRAMP NAL 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> <span style="color: #949494;">B_</span>GRAMP PLB 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> <span style="color: #949494;">B_</span>GRAMP TEM 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> <span style="color: #949494;">B_</span>ANAER-POS ATM 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> <span style="color: #949494;">B_</span>ANAER-POS COL 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> <span style="color: #949494;">B_</span>ANAER-POS NAL 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> <span style="color: #949494;">B_</span>ANAER-POS PLB 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> <span style="color: #949494;">B_</span>ANAER-POS TEM 'EUCAST Expected Resistant Phenotypes' v1.2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 294,069 more rows</span></span>
</code></pre></div>
</div>

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@@ -15,7 +15,7 @@ intrinsic_resistant
## Format
A [tibble](https://tibble.tidyverse.org/reference/tibble.html) with 294
079 observations and 2 variables:
079 observations and 3 variables:
- `mo`
Microorganism ID which occurs in
@@ -29,12 +29,15 @@ A [tibble](https://tibble.tidyverse.org/reference/tibble.html) with 294
Names can be retrieved using
[`ab_name()`](https://amr-for-r.org/reference/ab_property.md).
- `version`
Guideline name and version.
## Details
This data set is currently based on ['EUCAST Expected Resistant
This data set is currently strictly follows ['EUCAST Expected Resistant
Phenotypes'
v1.2](https://www.eucast.org/bacteria/important-additional-information/expert-rules/)
(2023).
(2023). The
This data set is internally used by:
@@ -68,18 +71,18 @@ repository](https://github.com/msberends/AMR/tree/main/data-raw/datasets).
``` r
intrinsic_resistant
#> # A tibble: 294,079 × 2
#> mo ab
#> <mo> <ab>
#> 1 B_GRAMP ATM
#> 2 B_GRAMP COL
#> 3 B_GRAMP NAL
#> 4 B_GRAMP PLB
#> 5 B_GRAMP TEM
#> 6 B_ANAER-POS ATM
#> 7 B_ANAER-POS COL
#> 8 B_ANAER-POS NAL
#> 9 B_ANAER-POS PLB
#> 10 B_ANAER-POS TEM
#> # A tibble: 294,079 × 3
#> mo ab version
#> <mo> <ab> <chr>
#> 1 B_GRAMP ATM 'EUCAST Expected Resistant Phenotypes' v1.2
#> 2 B_GRAMP COL 'EUCAST Expected Resistant Phenotypes' v1.2
#> 3 B_GRAMP NAL 'EUCAST Expected Resistant Phenotypes' v1.2
#> 4 B_GRAMP PLB 'EUCAST Expected Resistant Phenotypes' v1.2
#> 5 B_GRAMP TEM 'EUCAST Expected Resistant Phenotypes' v1.2
#> 6 B_ANAER-POS ATM 'EUCAST Expected Resistant Phenotypes' v1.2
#> 7 B_ANAER-POS COL 'EUCAST Expected Resistant Phenotypes' v1.2
#> 8 B_ANAER-POS NAL 'EUCAST Expected Resistant Phenotypes' v1.2
#> 9 B_ANAER-POS PLB 'EUCAST Expected Resistant Phenotypes' v1.2
#> 10 B_ANAER-POS TEM 'EUCAST Expected Resistant Phenotypes' v1.2
#> # ℹ 294,069 more rows
```

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@@ -375,15 +375,15 @@
<li><p><code>mo_ref("Enterobacter aerogenes")</code> will return <code>"Tindall et al., 2017"</code> (with a note about the renaming)</p></li>
<li><p><code>mo_ref("Enterobacter aerogenes", keep_synonyms = TRUE)</code> will return <code>"Hormaeche et al., 1960"</code> (with a once-per-session warning that the name is outdated)</p></li>
</ul><p><code>mo_ref()</code> returns the abbreviated authority of the nomenclatural act that created the queried name combination. When <code>keep_synonyms = FALSE</code> (default), this is the authority of the currently accepted name. When <code>keep_synonyms = TRUE</code>, this is the authority under which the queried (possibly outdated) name was published. Emendations (changes to the species description without a name change) are not reflected; only the combination or original description authority is returned.</p>
<p>The short name (<code>mo_shortname()</code>) returns the first character of the genus and the full species, such as <code>"E. coli"</code>, for species and subspecies. Exceptions are abbreviations of staphylococci (such as <em>"CoNS"</em>, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as <em>"GBS"</em>, Group B Streptococci). Please bear in mind that e.g. <em>E. coli</em> could mean <em>Escherichia coli</em> (kingdom of Bacteria) as well as <em>Entamoeba coli</em> (kingdom of Protozoa). Returning to the full name will be done using <code><a href="as.mo.html">as.mo()</a></code> internally, giving priority to bacteria and human pathogens, i.e. <code>"E. coli"</code> will always be considered <em>Escherichia coli</em>. As a result, <code>mo_fullname(mo_shortname("Entamoeba coli"))</code> returns <code>"Escherichia coli"</code>.</p>
<p>The short name (<code>mo_shortname()</code>) returns the first character of the genus and the full species, such as <code>"E. coli"</code>, for species and subspecies. Exceptions are abbreviations of staphylococci (such as <em>"CoNS"</em>, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as <em>"GBS"</em>, Group B Streptococci). Please bear in mind that e.g. <em>E. coli</em> could mean <em>Escherichia coli</em> (domain of Bacteria) as well as <em>Entamoeba coli</em> (domain of Protozoa). Returning to the full name will be done using <code><a href="as.mo.html">as.mo()</a></code> internally, giving priority to bacteria and human pathogens, i.e. <code>"E. coli"</code> will always be considered <em>Escherichia coli</em>. As a result, <code>mo_fullname(mo_shortname("Entamoeba coli"))</code> returns <code>"Escherichia coli"</code>.</p>
<p>Following the formal introduction of the new kingdom rank into prokaryotic nomenclature in 2024 (<a href="https://doi.org/10.1099/ijsem.0.006242" class="external-link">doi:10.1099/ijsem.0.006242</a>
), <code>mo_kingdom()</code> and <code>mo_domain()</code> return different results for bacteria and archaea: <code>mo_kingdom()</code> returns the new formal kingdom (e.g. "Pseudomonadati", "Bacillati"), while <code>mo_domain()</code> returns the new domain (e.g. "Bacteria", "Archaea"). For non-prokaryotic organisms, both functions return identical results.</p>
<p>Determination of human pathogenicity (<code>mo_pathogenicity()</code>) is strongly based on Bartlett <em>et al.</em> (2022, <a href="https://doi.org/10.1099/mic.0.001269" class="external-link">doi:10.1099/mic.0.001269</a>
). This function returns a <a href="https://rdrr.io/pkg/data.table/man/fctr.html" class="external-link">factor</a> with the levels <em>Pathogenic</em>, <em>Potentially pathogenic</em>, <em>Non-pathogenic</em>, and <em>Unknown</em>.</p>
<p>Determination of the Gram stain (<code>mo_gramstain()</code> is based on the taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, <a href="https://pubmed.ncbi.nlm.nih.gov/11837318/" class="external-link">PMID 11837318</a>), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were later renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, <a href="https://pubmed.ncbi.nlm.nih.gov/34694987/" class="external-link">PMID 34694987</a>). Bacteria in these phyla are considered Gram-positive in this <code>AMR</code> package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value <code>NA</code>. Functions <code>mo_is_gram_negative()</code> and <code>mo_is_gram_positive()</code> always return <code>TRUE</code> or <code>FALSE</code> (or <code>NA</code> when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>), thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p>
<p>Determination of yeasts (<code>mo_is_yeast()</code>) is based on the taxonomic kingdom and class. <em>Budding yeasts</em> are yeasts that reproduce asexually through a process called budding, where a new cell develops from a small protrusion on the parent cell. Taxonomically, these are members of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes) or Pichiomycetes. <em>True yeasts</em> quite specifically refers to yeasts in the underlying order Saccharomycetales (such as <em>Saccharomyces cerevisiae</em>). Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes or Pichiomycetes, the function will return <code>TRUE</code>. It returns <code>FALSE</code> otherwise (or <code>NA</code> when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>).</p>
<p>Determination of the Gram stain (<code>mo_gramstain()</code> is based on the taxonomic domain and phylum. Originally, Cavalier-Smith defined the so-called subkingdoms Negibacteria and Posibacteria (2002, <a href="https://pubmed.ncbi.nlm.nih.gov/11837318/" class="external-link">PMID 11837318</a>), and only considered these phyla as Posibacteria: Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes. These phyla were later renamed to Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota (2021, <a href="https://pubmed.ncbi.nlm.nih.gov/34694987/" class="external-link">PMID 34694987</a>). Bacteria in these phyla are considered Gram-positive in this <code>AMR</code> package, except for members of the class Negativicutes (within phylum Bacillota) which are Gram-negative. All other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value <code>NA</code>. Functions <code>mo_is_gram_negative()</code> and <code>mo_is_gram_positive()</code> always return <code>TRUE</code> or <code>FALSE</code> (or <code>NA</code> when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>), thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p>
<p>Determination of yeasts (<code>mo_is_yeast()</code>) is based on the taxonomic domain and class. <em>Budding yeasts</em> are yeasts that reproduce asexually through a process called budding, where a new cell develops from a small protrusion on the parent cell. Taxonomically, these are members of the phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes) or Pichiomycetes. <em>True yeasts</em> quite specifically refers to yeasts in the underlying order Saccharomycetales (such as <em>Saccharomyces cerevisiae</em>). Thus, for all microorganisms that are member of the taxonomic class Saccharomycetes or Pichiomycetes, the function will return <code>TRUE</code>. It returns <code>FALSE</code> otherwise (or <code>NA</code> when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>).</p>
<p>Determination of intrinsic resistance (<code>mo_is_intrinsic_resistant()</code>) is based on the <a href="intrinsic_resistant.html">intrinsic_resistant</a> data set, which is based on <a href="https://www.eucast.org/bacteria/important-additional-information/expert-rules/" class="external-link">'EUCAST Expected Resistant Phenotypes' v1.2</a> (2023). The <code>mo_is_intrinsic_resistant()</code> function can be vectorised over both argument <code>x</code> (input for microorganisms) and <code>ab</code> (input for antimicrobials).</p>
<p>Determination of both bacterial oxygen tolerance (<code>mo_oxygen_tolerance()</code>) and morphology (<code>mo_morphology()</code>) are based on BacDive, see <em>Source</em>. The function <code>mo_is_anaerobic()</code> only returns <code>TRUE</code> if the oxygen tolerance is <code>"anaerobe"</code>, indicating an obligate anaerobic species or genus. It always returns <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p>
<p>Determination of both bacterial oxygen tolerance (<code>mo_oxygen_tolerance()</code>) and morphology (<code>mo_morphology()</code>) are based on BacDive, see <em>Source</em>. The function <code>mo_is_anaerobic()</code> only returns <code>TRUE</code> if the oxygen tolerance is <code>"anaerobe"</code>, indicating an obligate anaerobic species or genus. It always returns <code>FALSE</code> for species outside the taxonomic domain of Bacteria.</p>
<p>The function <code>mo_url()</code> will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species. <a href="https://www.mycobank.org" class="external-link">This MycoBank URL</a> is used for fungi wherever available , <a href="https://www.mycobank.org" class="external-link">this LPSN URL</a> for bacteria wherever available, and <a href="https://www.gbif.org" class="external-link">this GBIF link</a> otherwise.</p>
<p>SNOMED codes (<code>mo_snomed()</code>) was last updated on 16th of July, 2024. See <em>Source</em> and the <a href="microorganisms.html">microorganisms</a> data set for more info.</p>
<p>Old taxonomic names (so-called 'synonyms') can be retrieved with <code>mo_synonyms()</code> (which will have the scientific reference as <a href="https://rdrr.io/r/base/names.html" class="external-link">name</a>), the current taxonomic name can be retrieved with <code>mo_current()</code>. Both functions return full names.</p>

12
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@@ -400,9 +400,9 @@ genus and the full species, such as `"E. coli"`, for species and
subspecies. Exceptions are abbreviations of staphylococci (such as
*"CoNS"*, Coagulase-Negative Staphylococci) and beta-haemolytic
streptococci (such as *"GBS"*, Group B Streptococci). Please bear in
mind that e.g. *E. coli* could mean *Escherichia coli* (kingdom of
Bacteria) as well as *Entamoeba coli* (kingdom of Protozoa). Returning
to the full name will be done using
mind that e.g. *E. coli* could mean *Escherichia coli* (domain of
Bacteria) as well as *Entamoeba coli* (domain of Protozoa). Returning to
the full name will be done using
[`as.mo()`](https://amr-for-r.org/reference/as.mo.md) internally, giving
priority to bacteria and human pathogens, i.e. `"E. coli"` will always
be considered *Escherichia coli*. As a result,
@@ -426,7 +426,7 @@ function returns a
*Pathogenic*, *Potentially pathogenic*, *Non-pathogenic*, and *Unknown*.
Determination of the Gram stain (`mo_gramstain()` is based on the
taxonomic kingdom and phylum. Originally, Cavalier-Smith defined the
taxonomic domain and phylum. Originally, Cavalier-Smith defined the
so-called subkingdoms Negibacteria and Posibacteria (2002, [PMID
11837318](https://pubmed.ncbi.nlm.nih.gov/11837318/)), and only
considered these phyla as Posibacteria: Actinobacteria, Chloroflexi,
@@ -443,7 +443,7 @@ is `UNKNOWN`), thus always return `FALSE` for species outside the
taxonomic kingdom of Bacteria.
Determination of yeasts (`mo_is_yeast()`) is based on the taxonomic
kingdom and class. *Budding yeasts* are yeasts that reproduce asexually
domain and class. *Budding yeasts* are yeasts that reproduce asexually
through a process called budding, where a new cell develops from a small
protrusion on the parent cell. Taxonomically, these are members of the
phylum Ascomycota, class Saccharomycetes (also called Hemiascomycetes)
@@ -468,7 +468,7 @@ Determination of both bacterial oxygen tolerance
on BacDive, see *Source*. The function `mo_is_anaerobic()` only returns
`TRUE` if the oxygen tolerance is `"anaerobe"`, indicating an obligate
anaerobic species or genus. It always returns `FALSE` for species
outside the taxonomic kingdom of Bacteria.
outside the taxonomic domain of Bacteria.
The function `mo_url()` will return the direct URL to the online
database entry, which also shows the scientific reference of the

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@@ -9,7 +9,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
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@@ -9,7 +9,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
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@@ -9,7 +9,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
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@@ -9,7 +9,7 @@ NOTE: These functions are deprecated and will be removed in a future version. Us
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reference/skewness.html
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@@ -9,7 +9,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
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reference/top_n_microorganisms.html
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@@ -7,7 +7,7 @@
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
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reference/translate.html
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@@ -7,7 +7,7 @@
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9087</small>
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search.json
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