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<meta property="og:title" content="Count isolates — count" />
<meta property="og:title" content="Count isolates — count" />
<meta property="og:description" content="These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in dplyrs summarise and support grouped variables, see Examples.
count_R and count_IR can be used to count resistant isolates, count_S and count_SI can be used to count susceptible isolates." />
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9067</span>
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<div class="ref-description">
<p>These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in <code>dplyr</code>s <code><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></code> and support grouped variables, see <em>Examples</em>.</p>
<p><code>count_R</code> and <code>count_IR</code> can be used to count resistant isolates, <code>count_S</code> and <code>count_SI</code> can be used to count susceptible isolates.<br /></p>
</div>
<pre class="usage"><span class='fu'>count_R</span>(<span class='no'>...</span>, <span class='kw'>only_all_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
@ -252,7 +255,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<span class='fu'>count_df</span>(<span class='no'>data</span>, <span class='kw'>translate_ab</span> <span class='kw'>=</span> <span class='st'>"name"</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='translate.html'>get_locale</a></span>(),
<span class='kw'>combine_SI</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>combine_IR</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@ -274,7 +277,7 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
</tr>
<tr>
<th>language</th>
<td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale</a></code>) and can also be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
<td><p>language of the returned text, defaults to system language (see <code><a href='translate.html'>get_locale</a></code>) and can also be set with <code><a href='https://rdrr.io/r/base/options.html'>getOption</a>("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
</tr>
<tr>
<th>combine_SI</th>
@ -285,38 +288,37 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<td><p>a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see parameter <code>combine_SI</code>.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>Wickham H. <strong>Tidy Data.</strong> The Journal of Statistical Software, vol. 59, 2014. <a href='http://vita.had.co.nz/papers/tidy-data.html'>http://vita.had.co.nz/papers/tidy-data.html</a></p>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Integer</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>These functions are meant to count isolates. Use the <code><a href='portion.html'>portion</a>_*</code> functions to calculate microbial resistance.</p>
<p>The function <code>n_rsi</code> is an alias of <code>count_all</code>. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to <code><a href='https://dplyr.tidyverse.org/reference/n_distinct.html'>n_distinct</a></code>. Their function is equal to <code>count_S(...) + count_IR(...)</code>.</p>
<p>The function <code>count_df</code> takes any variable from <code>data</code> that has an <code>"rsi"</code> class (created with <code><a href='as.rsi.html'>as.rsi</a></code>) and counts the amounts of S, I and R. The resulting <em>tidy data</em> (see Source) <code>data.frame</code> will have three rows (S/I/R) and a column for each variable with class <code>"rsi"</code>.</p>
<p>The function <code>rsi_df</code> works exactly like <code>count_df</code>, but adds the percentage of S, I and R.</p>
<h2 class="hasAnchor" id="interpretation-of-s-i-and-r"><a class="anchor" href="#interpretation-of-s-i-and-r"></a>Interpretation of S, I and R</h2>
<p>In 2019, EUCAST has decided to change the definitions of susceptibility testing categories S, I and R as shown below (<a href='http://www.eucast.org/newsiandr/'>http://www.eucast.org/newsiandr/</a>). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".</p>
<p>In 2019, EUCAST has decided to change the definitions of susceptibility testing categories S, I and R as shown below (<a href='http://www.eucast.org/newsiandr/'>http://www.eucast.org/newsiandr/</a>). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".</p>
<ul>
<li><p><strong>S</strong> - Susceptible, standard dosing regimen: A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.</p></li>
<li><p><strong>I</strong> - Susceptible, increased exposure: A microorganism is categorised as "Susceptible, Increased exposure" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.</p></li>
<li><p><strong>R</strong> - Resistant: A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.</p></li>
</ul>
<p>Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p>
<p>Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.</p>
<p>This AMR package honours this new insight. Use <code><a href='portion.html'>portion_SI</a></code> to determine antimicrobial susceptibility and <code>count_SI</code> to count susceptible isolates.</p>
<h2 class="hasAnchor" id="combination-therapy"><a class="anchor" href="#combination-therapy"></a>Combination therapy</h2>
<p>When using more than one variable for <code>...</code> (= combination therapy)), use <code>only_all_tested</code> to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Antibiotic A and Antibiotic B, about how <code>portion_SI</code> works to calculate the %SI:</p>
<p>When using more than one variable for <code>...</code> (= combination therapy)), use <code>only_all_tested</code> to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Antibiotic A and Antibiotic B, about how <code>portion_SI</code> works to calculate the %SI:</p>
<pre>
--------------------------------------------------------------------
only_all_tested = FALSE only_all_tested = TRUE
@ -335,28 +337,27 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
&lt;NA&gt; &lt;NA&gt; - - - -
--------------------------------------------------------------------
</pre>
<p>Please note that, in combination therapies, for <code>only_all_tested = TRUE</code> applies that:</p><pre>
<p>Please note that, in combination therapies, for <code>only_all_tested = TRUE</code> applies that:</p><pre>
count_S() + count_I() + count_R() == count_all()
portion_S() + portion_I() + portion_R() == 1
</pre><p>and that, in combination therapies, for <code>only_all_tested = FALSE</code> applies that:</p><pre>
count_S() + count_I() + count_R() &gt;= count_all()
portion_S() + portion_I() + portion_R() &gt;= 1
</pre>
<p>Using <code>only_all_tested</code> has no impact when only using one antibiotic as input.</p>
<p>Using <code>only_all_tested</code> has no impact when only using one antibiotic as input.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='portion.html'>portion</a>_*</code> to calculate microbial resistance and susceptibility.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># example_isolates is a data set available in the AMR package.</span>
<pre class="examples"><span class='co'># example_isolates is a data set available in the AMR package.</span>
?<span class='no'>example_isolates</span>
<span class='co'># Count resistant isolates</span>
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<span class='fu'>count_SI</span>(<span class='no'>example_isolates</span>$<span class='no'>AMX</span>)
<span class='fu'><a href='portion.html'>portion_SI</a></span>(<span class='no'>example_isolates</span>$<span class='no'>AMX</span>) * <span class='fu'>n_rsi</span>(<span class='no'>example_isolates</span>$<span class='no'>AMX</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>R</span> <span class='kw'>=</span> <span class='fu'>count_R</span>(<span class='no'>CIP</span>),
@ -396,9 +397,9 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<span class='fu'>count_SI</span>(<span class='no'>example_isolates</span>$<span class='no'>GEN</span>) <span class='co'># 1399</span>
<span class='fu'>count_all</span>(<span class='no'>example_isolates</span>$<span class='no'>GEN</span>) <span class='co'># 1855</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/with'>with</a></span>(<span class='no'>example_isolates</span>,
<span class='fu'><a href='https://rdrr.io/r/base/with.html'>with</a></span>(<span class='no'>example_isolates</span>,
<span class='fu'>count_SI</span>(<span class='no'>AMC</span>, <span class='no'>GEN</span>)) <span class='co'># 1764</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/with'>with</a></span>(<span class='no'>example_isolates</span>,
<span class='fu'><a href='https://rdrr.io/r/base/with.html'>with</a></span>(<span class='no'>example_isolates</span>,
<span class='fu'>n_rsi</span>(<span class='no'>AMC</span>, <span class='no'>GEN</span>)) <span class='co'># 1936</span>
<span class='co'># Get portions S/I/R immediately of all rsi columns</span>
@ -410,43 +411,35 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>hospital_id</span>, <span class='no'>AMX</span>, <span class='no'>CIP</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>count_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># }</span></pre>
<span class='fu'>count_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
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<li><a href="#arguments">Arguments</a></li>
<li><a href="#source">Source</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#interpretation-of-s-i-and-r">Interpretation of S, I and R</a></li>
<li><a href="#combination-therapy">Combination therapy</a></li>
<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
<li><a href="#see-also">See also</a></li>
<li><a href="#examples">Examples</a></li>
</ul>
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@ -469,6 +462,8 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_
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