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@@ -49,141 +39,41 @@
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How to
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<span class="fa fa-directions"></span>
Conduct AMR Analysis
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Generate Antibiogram (Trad./Syndromic/WISCA)
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Conduct Principal Component Analysis for AMR
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Determine Multi-Drug Resistance (MDR)
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<li><a class="dropdown-item" href="../articles/AMR.html"><span class="fa fa-directions"></span> Conduct AMR Analysis</a></li>
<li><a class="dropdown-item" href="../reference/antibiogram.html"><span class="fa fa-file-prescription"></span> Generate Antibiogram (Trad./Syndromic/WISCA)</a></li>
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<li><a class="dropdown-item" href="../reference/av_property.html"><span class="fa fa-capsules"></span> Get Properties of an Antiviral Drug</a></li>
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AMR &amp; data.table
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AMR &amp; tidymodels
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<li><a class="dropdown-item" href="../articles/other_pkg.html"><span class="fa fa-layer-group"></span> AMR &amp; dplyr/tidyverse</a></li>
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@@ -195,7 +85,7 @@
<img src="../logo.svg" class="logo" alt=""><h1>How to conduct AMR data analysis</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/AMR.Rmd" class="external-link"><code>vignettes/AMR.Rmd</code></a></small>
<div class="d-none name"><code>AMR.Rmd</code></div>
</div>
@@ -205,7 +95,7 @@
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 23 June 2024.</p>
generated on 16 July 2024.</p>
<div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
@@ -261,21 +151,21 @@ make the structure of your data generally look like this:</p>
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2024-06-23</td>
<td align="center">2024-07-16</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">2024-06-23</td>
<td align="center">2024-07-16</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">2024-06-23</td>
<td align="center">2024-07-16</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@@ -318,9 +208,8 @@ have extracted from their laboratory systems:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> M3 A 2015-10-25 E. coli R S S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> J3 A 2019-06-19 E. coli S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> G6 A 2015-04-27 S. aureus S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,990 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,990 more rows</span></span></span>
<span></span>
<span><span class="co"># we will use 'our_data' as the data set name for this tutorial</span></span>
<span><span class="va">our_data</span> <span class="op">&lt;-</span> <span class="va">example_isolates_unclean</span></span></code></pre></div>
<p>For AMR data analysis, we would like the microorganism column to
@@ -333,24 +222,21 @@ cleaned as SIR values as well.</p>
<p>With <code><a href="../reference/as.mo.html">as.mo()</a></code>, users can transform arbitrary
microorganism names or codes to current taxonomy. The <code>AMR</code>
package contains up-to-date taxonomic data. To be specific, currently
included data were retrieved on 11 Dec 2022.</p>
included data were retrieved on 24 Jun 2024.</p>
<p>The codes of the AMR packages that come from <code><a href="../reference/as.mo.html">as.mo()</a></code> are
short, but still human readable. More importantly, <code><a href="../reference/as.mo.html">as.mo()</a></code>
supports all kinds of input:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; Class 'mo'</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span>
<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; Class 'mo'</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLEPNE"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span>
<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLEPNE"</span><span class="op">)</span></span>
<span><span class="co">#&gt; Class 'mo'</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLPN"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span>
<span><span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"KLPN"</span><span class="op">)</span></span>
<span><span class="co">#&gt; Class 'mo'</span></span>
<span><span class="co">#&gt; [1] B_KLBSL_PNMN</span></span></code></pre></div>
<p>The first character in above codes denote their taxonomic kingdom,
@@ -360,58 +246,53 @@ retrieve taxonomic properties, such as the name, genus, species, family,
order, and even Gram-stain. They all start with <code>mo_</code> and
they use <code><a href="../reference/as.mo.html">as.mo()</a></code> internally, so that still any arbitrary
user input can be used:</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_family</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Enterobacteriaceae"</span></span></code></pre></div>
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Klebsiella"</span></span></code></pre></div>
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "pneumoniae"</span></span></code></pre></div>
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; [1] "Enterobacteriaceae"</span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Klebsiella"</span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_species</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "pneumoniae"</span></span>
<span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_gramstain</a></span><span class="op">(</span><span class="st">"Klebsiella pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Gram-negative"</span></span></code></pre></div>
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; [1] "Gram-negative"</span></span>
<span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_ref</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "Trevisan, 1887"</span></span></code></pre></div>
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; [1] "Trevisan, 1887"</span></span>
<span></span>
<span><span class="fu"><a href="../reference/mo_property.html">mo_snomed</a></span><span class="op">(</span><span class="st">"K. pneumoniae"</span><span class="op">)</span></span>
<span><span class="co">#&gt; [[1]]</span></span>
<span><span class="co">#&gt; [1] "1098101000112102" "446870005" "1098201000112108" "409801009" </span></span>
<span><span class="co">#&gt; [5] "56415008" "714315002" "713926009"</span></span></code></pre></div>
<p>Now we can thus clean our data:</p>
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data</span><span class="op">$</span><span class="va">bacteria</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/as.mo.html">as.mo</a></span><span class="op">(</span><span class="va">our_data</span><span class="op">$</span><span class="va">bacteria</span>, info <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ Microorganism translation was uncertain for four microorganisms. Run</span></span>
<span><span class="co">#&gt; mo_uncertainties() to review these uncertainties, or use</span></span>
<span><span class="co">#&gt; add_custom_microorganisms() to add custom entries.</span></span></code></pre></div>
<p>Apparently, there was some uncertainty about the translation to
taxonomic codes. Let’s check this:</p>
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/as.mo.html">mo_uncertainties</a></span><span class="op">(</span><span class="op">)</span></span>
<span><span class="co">#&gt; Matching scores are based on the resemblance between the input and the full</span></span>
<span><span class="co">#&gt; taxonomic name, and the pathogenicity in humans. See ?mo_matching_score.</span></span>
<span><span class="co">#&gt; </span></span>
<span><span class="co">#&gt; --------------------------------------------------------------------------------</span></span>
<span><span class="co">#&gt; "E. coli" -&gt; Escherichia coli (B_ESCHR_COLI, 0.688)</span></span>
<span><span class="co">#&gt; Also matched: Enterobacter cowanii (0.600), Eubacterium combesii</span></span>
<span><span class="co">#&gt; Also matched: Escherichia coli coli (0.643), Escherichia coli</span></span>
<span><span class="co">#&gt; expressing (0.611), Enterobacter cowanii (0.600), Eubacterium combesii</span></span>
<span><span class="co">#&gt; (0.600), Eggerthia catenaformis (0.591), Eubacterium callanderi</span></span>
<span><span class="co">#&gt; (0.591), Enterocloster citroniae (0.587), Eubacterium cylindroides</span></span>
<span><span class="co">#&gt; (0.583), Enterococcus casseliflavus (0.577), Enterobacter cloacae</span></span>
<span><span class="co">#&gt; cloacae (0.571), Enterobacter cloacae complex (0.571), and Ehrlichia</span></span>
<span><span class="co">#&gt; canis (0.567)</span></span>
<span><span class="co">#&gt; (0.583), Enterococcus casseliflavus (0.577), and Enterobacter cloacae</span></span>
<span><span class="co">#&gt; cloacae (0.571)</span></span>
<span><span class="co">#&gt; --------------------------------------------------------------------------------</span></span>
<span><span class="co">#&gt; "K. pneumoniae" -&gt; Klebsiella pneumoniae (B_KLBSL_PNMN, 0.786)</span></span>
<span><span class="co">#&gt; Also matched: Klebsiella pneumoniae ozaenae (0.707), Klebsiella</span></span>
<span><span class="co">#&gt; pneumoniae pneumoniae (0.688), Klebsiella pneumoniae rhinoscleromatis</span></span>
<span><span class="co">#&gt; (0.658), Klebsiella pasteurii (0.500), Klebsiella planticola (0.500),</span></span>
<span><span class="co">#&gt; Kingella potus (0.400), Kosakonia pseudosacchari (0.361), Kaistella</span></span>
<span><span class="co">#&gt; palustris (0.333), Kocuria palustris (0.333), and Kocuria pelophila</span></span>
<span><span class="co">#&gt; (0.333)</span></span>
<span><span class="co">#&gt; Kingella potus (0.400), Kluyveromyces pseudotropicale (0.386),</span></span>
<span><span class="co">#&gt; Kluyveromyces pseudotropicalis (0.363), Kosakonia pseudosacchari</span></span>
<span><span class="co">#&gt; (0.361), and Kluyveromyces pseudotropicalis pseudotropicalis (0.361)</span></span>
<span><span class="co">#&gt; --------------------------------------------------------------------------------</span></span>
<span><span class="co">#&gt; "S. aureus" -&gt; Staphylococcus aureus (B_STPHY_AURS, 0.690)</span></span>
<span><span class="co">#&gt; Also matched: Staphylococcus aureus aureus (0.643), Staphylococcus</span></span>
@@ -448,7 +329,7 @@ diffusion values, read more about that on the <code><a href="../reference/as.sir
page.</p>
<p>For now, we will just clean the SIR columns in our data using
dplyr:</p>
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># method 1, be explicit about the columns:</span></span>
<span><span class="va">our_data</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate_all.html" class="external-link">mutate_at</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/vars.html" class="external-link">vars</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">:</span><span class="va">GEN</span><span class="op">)</span>, <span class="va">as.sir</span><span class="op">)</span></span>
@@ -516,7 +397,7 @@ analysis, but the default phenotype-based method is in any case the
method to properly correct for most duplicate isolates. Read more about
the methods on the <code><a href="../reference/first_isolate.html">first_isolate()</a></code> page.</p>
<p>The outcome of the function can easily be added to our data:</p>
<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>first <span class="op">=</span> <span class="fu"><a href="../reference/first_isolate.html">first_isolate</a></span><span class="op">(</span>info <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ Determining first isolates using an episode length of 365 days</span></span>
@@ -530,16 +411,16 @@ the methods on the <code><a href="../reference/first_isolate.html">first_isolate
<p>So only 90% is suitable for resistance analysis! We can now filter on
it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code> function, also from the
<code>dplyr</code> package:</p>
<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">first</span> <span class="op">==</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
<p>For future use, the above two syntaxes can be shortened:</p>
<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op">&lt;-</span> <span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="../reference/first_isolate.html">filter_first_isolate</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
<p>So we end up with 2 712 isolates for analysis. Now our data looks
like:</p>
<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,712 × 9</span></span></span>
<span><span class="co">#&gt; patient_id hospital date bacteria AMX AMC CIP GEN first</span></span>
@@ -564,7 +445,7 @@ like:</p>
<p>The base R <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code> function gives a good first
impression, as it comes with support for the new <code>mo</code> and
<code>sir</code> classes that we now have in our data set:</p>
<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">our_data_1st</span><span class="op">)</span></span>
<span><span class="co">#&gt; patient_id hospital date </span></span>
<span><span class="co">#&gt; Length:2712 Length:2712 Min. :2011-01-01 </span></span>
@@ -586,9 +467,8 @@ impression, as it comes with support for the new <code>mo</code> and
<span><span class="co">#&gt; %SDD : 0.0% (n=0) %SDD : 0.0% (n=0) </span></span>
<span><span class="co">#&gt; %I : 6.6% (n=178) %I : 3.1% (n=85) </span></span>
<span><span class="co">#&gt; %R :42.0% (n=1138) %R :37.3% (n=1011) </span></span>
<span><span class="co">#&gt; %NI : 0.0% (n=0) %NI : 0.0% (n=0)</span></span></code></pre></div>
<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; %NI : 0.0% (n=0) %NI : 0.0% (n=0)</span></span>
<span></span>
<span><span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">our_data_1st</span><span class="op">)</span></span>
<span><span class="co">#&gt; Rows: 2,712</span></span>
<span><span class="co">#&gt; Columns: 9</span></span>
@@ -600,9 +480,8 @@ impression, as it comes with support for the new <code>mo</code> and
<span><span class="co">#&gt; $ AMC <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> I, I, I, S, S, S, S, S, S, S, S, S, I, S, S, S, S, R, S, S,…</span></span>
<span><span class="co">#&gt; $ CIP <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> S, S, S, S, R, S, S, S, S, S, S, S, S, S, S, S, S, S, S, S,…</span></span>
<span><span class="co">#&gt; $ GEN <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> S, S, S, S, S, S, S, S, S, S, R, S, S, S, S, S, S, S, S, S,…</span></span>
<span><span class="co">#&gt; $ first <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,…</span></span></code></pre></div>
<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; $ first <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,…</span></span>
<span></span>
<span><span class="co"># number of unique values per column:</span></span>
<span><span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">our_data_1st</span>, <span class="va">n_distinct</span><span class="op">)</span></span>
<span><span class="co">#&gt; patient_id hospital date bacteria AMX AMC CIP </span></span>
@@ -615,7 +494,7 @@ impression, as it comes with support for the new <code>mo</code> and
<p>To just get an idea how the species are distributed, create a
frequency table with <code><a href="../reference/count.html">count()</a></code> based on the name of the
microorganisms:</p>
<div class="sourceCode" id="cb24"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="../reference/count.html">count</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span>, sort <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 4 × 2</span></span></span>
@@ -624,9 +503,8 @@ microorganisms:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> Escherichia coli <span style="text-decoration: underline;">1</span>518</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> Staphylococcus aureus 730</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> Streptococcus pneumoniae 426</span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae 326</span></span></code></pre></div>
<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae 326</span></span>
<span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="../reference/count.html">count</a></span><span class="op">(</span><span class="fu"><a href="../reference/mo_property.html">mo_name</a></span><span class="op">(</span><span class="va">bacteria</span><span class="op">)</span>, sort <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 4 × 2</span></span></span>
@@ -643,7 +521,7 @@ microorganisms:</p>
<p>Using so-called antibiotic class selectors, you can select or filter
columns based on the antibiotic class that your antibiotic results are
in:</p>
<div class="sourceCode" id="cb26"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">date</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ For aminoglycosides() using column 'GEN' (gentamicin)</span></span>
@@ -660,9 +538,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> 2015-04-27 S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> 2011-06-21 S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> 2014-09-05 S </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span>
<span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC'</span></span>
@@ -680,9 +557,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> B_STPHY_AURS S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> B_ESCHR_COLI S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> B_ESCHR_COLI S S </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span>
<span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">bacteria</span>, <span class="fu"><a href="https://tidyselect.r-lib.org/reference/where.html" class="external-link">where</a></span><span class="op">(</span><span class="va">is.sir</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,712 × 5</span></span></span>
@@ -698,9 +574,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> B_STPHY_AURS S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> B_ESCHR_COLI S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> B_ESCHR_COLI S S S S </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 2,702 more rows</span></span></span>
<span></span>
<span><span class="co"># filtering using AB selectors is also possible:</span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/any.html" class="external-link">any</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span></span>
@@ -718,9 +593,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> P5 A 2019-03-09 B_STPHY_AURS S S S R TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> Q8 A 2019-08-10 B_STPHY_AURS S S S R TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> K5 A 2013-03-15 B_STRPT_PNMN S S S R TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 1,001 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 1,001 more rows</span></span></span>
<span></span>
<span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="co">#&gt; ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC'</span></span>
@@ -738,9 +612,8 @@ in:</p>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 8</span> Q2 A 2019-09-22 B_ESCHR_COLI R R S S TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;"> 9</span> X7 A 2011-03-20 B_ESCHR_COLI R R S R TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #BCBCBC;">10</span> V1 A 2018-08-07 B_STPHY_AURS R R S S TRUE </span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 473 more rows</span></span></span></code></pre></div>
<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 473 more rows</span></span></span>
<span></span>
<span><span class="co"># even works in base R (since R 3.0):</span></span>
<span><span class="va">our_data_1st</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/all.html" class="external-link">all</a></span><span class="op">(</span><span class="fu"><a href="../reference/antibiotic_class_selectors.html">betalactams</a></span><span class="op">(</span><span class="op">)</span> <span class="op">==</span> <span class="st">"R"</span><span class="op">)</span>, <span class="op">]</span></span>
<span><span class="co">#&gt; ℹ For betalactams() using columns 'AMX' (amoxicillin) and 'AMC'</span></span>
@@ -793,7 +666,7 @@ failure</li>
function to create any of the above antibiogram types. For starters,
this is what the included <code>example_isolates</code> data set looks
like:</p>
<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">example_isolates</span></span>
<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 2,000 × 46</span></span></span>
<span><span class="co">#&gt; date patient age gender ward mo PEN OXA FLC AMX </span></span>
@@ -822,7 +695,7 @@ like:</p>
should be used. The <code>antibiotics</code> argument in the
<code><a href="../reference/antibiogram.html">antibiogram()</a></code> function supports any (combination) of the
previously mentioned antibiotic class selectors:</p>
<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
<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> antibiotics <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/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</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>
@@ -949,7 +822,7 @@ Chinese, Czech, Danish, Dutch, Finnish, French, German, Greek, Italian,
Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish,
Swedish, Turkish, or Ukrainian. In this next example, we force the
language to be Spanish using the <code>language</code> argument:</p>
<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r">
<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> antibiotics <span class="op">=</span> <span class="fu"><a href="../reference/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>,</span>
@@ -995,7 +868,7 @@ language to be Spanish using the <code>language</code> argument:</p>
</h4>
<p>To create a combined antibiogram, use antibiotic codes or names with
a plus <code>+</code> character like this:</p>
<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb18"><pre class="downlit sourceCode r">
<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> antibiotics <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">
@@ -1077,7 +950,7 @@ a plus <code>+</code> character like this:</p>
<p>To create a syndromic antibiogram, the <code>syndromic_group</code>
argument must be used. This can be any column in the data, or e.g. an
<code><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse()</a></code> with calculations based on certain columns:</p>
<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r">
<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> antibiotics <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/antibiotic_class_selectors.html">aminoglycosides</a></span><span class="op">(</span><span class="op">)</span>, <span class="fu"><a href="../reference/antibiotic_class_selectors.html">carbapenems</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span>,</span>
<span> syndromic_group <span class="op">=</span> <span class="st">"ward"</span><span class="op">)</span></span>
@@ -1271,7 +1144,7 @@ Antibiogram) in which cases are predefined based on clinical or
demographic characteristics (e.g., endocarditis in 75+ females). This
next example is a simplification without clinical characteristics, but
just gives an idea of how a WISCA can be created:</p>
<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">wisca</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/antibiogram.html">antibiogram</a></span><span class="op">(</span><span class="va">example_isolates</span>,</span>
<span> antibiotics <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="st">"AMC+CIP"</span>, <span class="st">"TZP"</span>, <span class="st">"TZP+TOB"</span><span class="op">)</span>,</span>
<span> mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>,</span>
@@ -1339,7 +1212,7 @@ just gives an idea of how a WISCA can be created:</p>
<p>Antibiograms can be plotted using <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot()</a></code> from the
<code>ggplot2</code> packages, since this <code>AMR</code> package
provides an extension to that function:</p>
<div class="sourceCode" id="cb38"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">autoplot</a></span><span class="op">(</span><span class="va">wisca</span><span class="op">)</span></span></code></pre></div>
<p><img src="AMR_files/figure-html/unnamed-chunk-10-1.png" width="720"></p>
<p>To calculate antimicrobial resistance in a more sensible way, also by
@@ -1368,12 +1241,12 @@ proportion of R (<code><a href="../reference/proportion.html">proportion_R()</a>
I (<code><a href="../reference/proportion.html">proportion_SI()</a></code>, equal to
<code><a href="../reference/proportion.html">susceptibility()</a></code>). These functions can be used on their
own:</p>
<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb22"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] 0.4288348</span></span></code></pre></div>
<p>Or can be used in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> and
<code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb40"><pre class="downlit sourceCode r">
<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">our_data_1st</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">hospital</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></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>amoxicillin <span class="op">=</span> <span class="fu"><a href="../reference/proportion.html">resistance</a></span><span class="op">(</span><span class="va">AMX</span><span class="op">)</span><span class="op">)</span></span>
@@ -1387,7 +1260,7 @@ own:</p>
<p><em>Author: Dr. Matthijs Berends, 26th Feb 2023</em></p>
</div>
</div>
</main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
</nav></aside>
</div>
@@ -1404,9 +1277,9 @@ own:</p>
</footer>
</div>
</body>
</html>