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(v0.8.0.9033) antivirals data set, cleanup

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@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9031</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to conduct AMR analysis</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">15 November 2019</h4>
<h4 class="date">18 November 2019</h4>
<div class="hidden name"><code>AMR.Rmd</code></div>
@ -196,7 +196,7 @@
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 15 November 2019.</p>
<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 18 November 2019.</p>
<div id="introduction" class="section level1">
<h1 class="hasAnchor">
<a href="#introduction" class="anchor"></a>Introduction</h1>
@ -212,21 +212,21 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2019-11-15</td>
<td align="center">2019-11-18</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">2019-11-15</td>
<td align="center">2019-11-18</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">2019-11-15</td>
<td align="center">2019-11-18</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
@ -321,8 +321,8 @@
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2015-09-02</td>
<td align="center">V3</td>
<td align="center">2011-03-27</td>
<td align="center">O9</td>
<td align="center">Hospital B</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
@ -332,41 +332,30 @@
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2017-06-27</td>
<td align="center">H4</td>
<td align="center">2015-09-08</td>
<td align="center">U5</td>
<td align="center">Hospital C</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2012-05-31</td>
<td align="center">X3</td>
<td align="center">Hospital B</td>
<td align="center">Streptococcus pneumoniae</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2013-06-08</td>
<td align="center">K2</td>
<td align="center">Hospital B</td>
<tr class="odd">
<td align="center">2014-09-10</td>
<td align="center">L5</td>
<td align="center">Hospital C</td>
<td align="center">Staphylococcus aureus</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2012-02-10</td>
<td align="center">M5</td>
<tr class="even">
<td align="center">2011-07-28</td>
<td align="center">D7</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
@ -375,16 +364,27 @@
<td align="center">S</td>
<td align="center">M</td>
</tr>
<tr class="odd">
<td align="center">2013-04-12</td>
<td align="center">N6</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
</tr>
<tr class="even">
<td align="center">2010-06-25</td>
<td align="center">N7</td>
<td align="center">Hospital D</td>
<td align="center">2017-03-29</td>
<td align="center">F1</td>
<td align="center">Hospital A</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">M</td>
</tr>
</tbody>
</table>
@ -406,8 +406,8 @@
#
# Item Count Percent Cum. Count Cum. Percent
# --- ----- ------- -------- ----------- -------------
# 1 M 10,309 51.55% 10,309 51.55%
# 2 F 9,691 48.46% 20,000 100.00%</code></pre>
# 1 M 10,413 52.06% 10,413 52.06%
# 2 F 9,587 47.94% 20,000 100.00%</code></pre>
<p>So, we can draw at least two conclusions immediately. From a data scientists perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researchers perspective: there are slightly more men. Nothing we didn’t already know.</p>
<p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@ -422,8 +422,8 @@
<a class="sourceLine" id="cb14-3" data-line-number="3"><span class="co"># Other rules by this AMR package</span></a>
<a class="sourceLine" id="cb14-4" data-line-number="4"><span class="co"># Non-EUCAST: inherit amoxicillin results for unavailable ampicillin (no changes)</span></a>
<a class="sourceLine" id="cb14-5" data-line-number="5"><span class="co"># Non-EUCAST: inherit ampicillin results for unavailable amoxicillin (no changes)</span></a>
<a class="sourceLine" id="cb14-6" data-line-number="6"><span class="co"># Non-EUCAST: set amoxicillin/clav acid = S where ampicillin = S (3,022 values changed)</span></a>
<a class="sourceLine" id="cb14-7" data-line-number="7"><span class="co"># Non-EUCAST: set ampicillin = R where amoxicillin/clav acid = R (151 values changed)</span></a>
<a class="sourceLine" id="cb14-6" data-line-number="6"><span class="co"># Non-EUCAST: set amoxicillin/clav acid = S where ampicillin = S (2,986 values changed)</span></a>
<a class="sourceLine" id="cb14-7" data-line-number="7"><span class="co"># Non-EUCAST: set ampicillin = R where amoxicillin/clav acid = R (176 values changed)</span></a>
<a class="sourceLine" id="cb14-8" data-line-number="8"><span class="co"># Non-EUCAST: set piperacillin = R where piperacillin/tazobactam = R (no changes)</span></a>
<a class="sourceLine" id="cb14-9" data-line-number="9"><span class="co"># Non-EUCAST: set piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
<a class="sourceLine" id="cb14-10" data-line-number="10"><span class="co"># Non-EUCAST: set trimethoprim = R where trimethoprim/sulfa = R (no changes)</span></a>
@ -448,14 +448,14 @@
<a class="sourceLine" id="cb14-29" data-line-number="29"><span class="co"># Pasteurella multocida (no changes)</span></a>
<a class="sourceLine" id="cb14-30" data-line-number="30"><span class="co"># Staphylococcus (no changes)</span></a>
<a class="sourceLine" id="cb14-31" data-line-number="31"><span class="co"># Streptococcus groups A, B, C, G (no changes)</span></a>
<a class="sourceLine" id="cb14-32" data-line-number="32"><span class="co"># Streptococcus pneumoniae (1,071 values changed)</span></a>
<a class="sourceLine" id="cb14-32" data-line-number="32"><span class="co"># Streptococcus pneumoniae (1,015 values changed)</span></a>
<a class="sourceLine" id="cb14-33" data-line-number="33"><span class="co"># Viridans group streptococci (no changes)</span></a>
<a class="sourceLine" id="cb14-34" data-line-number="34"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-35" data-line-number="35"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,282 values changed)</span></a>
<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,284 values changed)</span></a>
<a class="sourceLine" id="cb14-37" data-line-number="37"><span class="co"># Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-38" data-line-number="38"><span class="co"># Table 03: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,783 values changed)</span></a>
<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,796 values changed)</span></a>
<a class="sourceLine" id="cb14-40" data-line-number="40"><span class="co"># Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
<a class="sourceLine" id="cb14-41" data-line-number="41"><span class="co"># Table 09: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
<a class="sourceLine" id="cb14-42" data-line-number="42"><span class="co"># Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins (no changes)</span></a>
@ -463,15 +463,15 @@
<a class="sourceLine" id="cb14-44" data-line-number="44"><span class="co"># Table 13: Interpretive rules for quinolones (no changes)</span></a>
<a class="sourceLine" id="cb14-45" data-line-number="45"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-46" data-line-number="46"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># EUCAST rules affected 6,586 out of 20,000 rows, making a total of 8,309 edits</span></a>
<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># EUCAST rules affected 6,569 out of 20,000 rows, making a total of 8,257 edits</span></a>
<a class="sourceLine" id="cb14-48" data-line-number="48"><span class="co"># =&gt; added 0 test results</span></a>
<a class="sourceLine" id="cb14-49" data-line-number="49"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># =&gt; changed 8,309 test results</span></a>
<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co"># - 129 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co"># - 4,834 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-53" data-line-number="53"><span class="co"># - 1,222 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-54" data-line-number="54"><span class="co"># - 324 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-55" data-line-number="55"><span class="co"># - 1,800 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># =&gt; changed 8,257 test results</span></a>
<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co"># - 123 test results changed from S to I</span></a>
<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co"># - 4,779 test results changed from S to R</span></a>
<a class="sourceLine" id="cb14-53" data-line-number="53"><span class="co"># - 1,134 test results changed from I to S</span></a>
<a class="sourceLine" id="cb14-54" data-line-number="54"><span class="co"># - 369 test results changed from I to R</span></a>
<a class="sourceLine" id="cb14-55" data-line-number="55"><span class="co"># - 1,852 test results changed from R to S</span></a>
<a class="sourceLine" id="cb14-56" data-line-number="56"><span class="co"># --------------------------------------------------------------------------</span></a>
<a class="sourceLine" id="cb14-57" data-line-number="57"><span class="co"># </span></a>
<a class="sourceLine" id="cb14-58" data-line-number="58"><span class="co"># Use eucast_rules(..., verbose = TRUE) (on your original data) to get a data.frame with all specified edits instead.</span></a></code></pre></div>
@ -499,8 +499,8 @@
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
<a class="sourceLine" id="cb16-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,688 first isolates (28.4% of total)</span></a></code></pre></div>
<p>So only 28.4% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,699 first isolates (28.5% of total)</span></a></code></pre></div>
<p>So only 28.5% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
<p>For future use, the above two syntaxes can be shortened with the <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> function:</p>
@ -510,7 +510,7 @@
<div id="first-weighted-isolates" class="section level2">
<h2 class="hasAnchor">
<a href="#first-weighted-isolates" class="anchor"></a>First <em>weighted</em> isolates</h2>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient I9, sorted on date:</p>
<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient X7, sorted on date:</p>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -526,19 +526,19 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-02-08</td>
<td align="center">I9</td>
<td align="center">2010-03-18</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-03-05</td>
<td align="center">I9</td>
<td align="center">2010-04-28</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -548,30 +548,30 @@
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-05-14</td>
<td align="center">I9</td>
<td align="center">2010-06-26</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-12-10</td>
<td align="center">I9</td>
<td align="center">2010-08-06</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-12-17</td>
<td align="center">I9</td>
<td align="center">2010-08-31</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -581,19 +581,19 @@
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2011-04-18</td>
<td align="center">I9</td>
<td align="center">2010-10-15</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-04-25</td>
<td align="center">I9</td>
<td align="center">2010-11-19</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -603,8 +603,8 @@
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-06-06</td>
<td align="center">I9</td>
<td align="center">2011-01-20</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -614,23 +614,23 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-07-14</td>
<td align="center">I9</td>
<td align="center">2011-04-10</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-07-31</td>
<td align="center">I9</td>
<td align="center">2011-04-12</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
</tr>
@ -647,7 +647,7 @@
<a class="sourceLine" id="cb19-7" data-line-number="7"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
<a class="sourceLine" id="cb19-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
<a class="sourceLine" id="cb19-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I</span></a>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,051 first weighted isolates (75.3% of total)</span></a></code></pre></div>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,085 first weighted isolates (75.4% of total)</span></a></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="center">isolate</th>
@ -664,80 +664,68 @@
<tbody>
<tr class="odd">
<td align="center">1</td>
<td align="center">2010-02-08</td>
<td align="center">I9</td>
<td align="center">2010-03-18</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">2</td>
<td align="center">2010-03-05</td>
<td align="center">I9</td>
<td align="center">2010-04-28</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="odd">
<td align="center">3</td>
<td align="center">2010-05-14</td>
<td align="center">I9</td>
<td align="center">2010-06-26</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">4</td>
<td align="center">2010-12-10</td>
<td align="center">I9</td>
<td align="center">2010-08-06</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">5</td>
<td align="center">2010-12-17</td>
<td align="center">I9</td>
<td align="center">2010-08-31</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">6</td>
<td align="center">2011-04-18</td>
<td align="center">I9</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2011-04-25</td>
<td align="center">I9</td>
<td align="center">2010-10-15</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
@ -746,10 +734,22 @@
<td align="center">FALSE</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td align="center">7</td>
<td align="center">2010-11-19</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
</tr>
<tr class="even">
<td align="center">8</td>
<td align="center">2011-06-06</td>
<td align="center">I9</td>
<td align="center">2011-01-20</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
@ -760,35 +760,35 @@
</tr>
<tr class="odd">
<td align="center">9</td>
<td align="center">2011-07-14</td>
<td align="center">I9</td>
<td align="center">2011-04-10</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td align="center">10</td>
<td align="center">2011-07-31</td>
<td align="center">I9</td>
<td align="center">2011-04-12</td>
<td align="center">X7</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">FALSE</td>
<td align="center">TRUE</td>
<td align="center">FALSE</td>
</tr>
</tbody>
</table>
<p>Instead of 2, now 9 isolates are flagged. In total, 75.3% of all isolates are marked ‘first weighted’ - 46.8% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>Instead of 2, now 6 isolates are flagged. In total, 75.4% of all isolates are marked ‘first weighted’ - 46.9% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
<p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
<p>So we end up with 15,051 isolates for analysis.</p>
<p>So we end up with 15,085 isolates for analysis.</p>
<p>We can remove unneeded columns:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(first, keyab))</a></code></pre></div>
@ -813,13 +813,29 @@
</tr></thead>
<tbody>
<tr class="odd">
<td>2</td>
<td align="center">2017-06-27</td>
<td align="center">H4</td>
<td align="center">Hospital C</td>
<td>1</td>
<td align="center">2011-03-27</td>
<td align="center">O9</td>
<td align="center">Hospital B</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>4</td>
<td align="center">2011-07-28</td>
<td align="center">D7</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
@ -828,59 +844,27 @@
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>3</td>
<td align="center">2012-05-31</td>
<td align="center">X3</td>
<td align="center">Hospital B</td>
<tr class="odd">
<td>8</td>
<td align="center">2015-08-23</td>
<td align="center">M1</td>
<td align="center">Hospital D</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">I</td>
<td align="center">I</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">F</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>4</td>
<td align="center">2013-06-08</td>
<td align="center">K2</td>
<td align="center">Hospital B</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">I</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-positive</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>5</td>
<td align="center">2012-02-10</td>
<td align="center">M5</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">M</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
<tr class="odd">
<td>7</td>
<td align="center">2015-10-03</td>
<td align="center">B7</td>
<td align="center">Hospital A</td>
<td>9</td>
<td align="center">2017-03-08</td>
<td align="center">G2</td>
<td align="center">Hospital B</td>
<td align="center">B_KLBSL_PNMN</td>
<td align="center">R</td>
<td align="center">S</td>
@ -892,20 +876,36 @@
<td align="center">pneumoniae</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>9</td>
<td align="center">2016-04-27</td>
<td align="center">O7</td>
<td align="center">Hospital B</td>
<td align="center">B_STRPT_PNMN</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<tr class="odd">
<td>10</td>
<td align="center">2013-11-09</td>
<td align="center">Q8</td>
<td align="center">Hospital A</td>
<td align="center">B_STPHY_AURS</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-positive</td>
<td align="center">Streptococcus</td>
<td align="center">pneumoniae</td>
<td align="center">Staphylococcus</td>
<td align="center">aureus</td>
<td align="center">TRUE</td>
</tr>
<tr class="even">
<td>16</td>
<td align="center">2010-06-08</td>
<td align="center">O4</td>
<td align="center">Hospital A</td>
<td align="center">B_ESCHR_COLI</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">F</td>
<td align="center">Gram-negative</td>
<td align="center">Escherichia</td>
<td align="center">coli</td>
<td align="center">TRUE</td>
</tr>
</tbody>
@ -927,7 +927,7 @@
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(genus, species)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
<p>Class: character<br>
Length: 15,051 (of which NA: 0 = 0%)<br>
Length: 15,085 (of which NA: 0 = 0%)<br>
Unique: 4</p>
<p>Shortest: 16<br>
Longest: 24</p>
@ -944,33 +944,33 @@ Longest: 24</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Escherichia coli</td>
<td align="right">7,443</td>
<td align="right">49.45%</td>
<td align="right">7,443</td>
<td align="right">49.45%</td>
<td align="right">7,426</td>
<td align="right">49.23%</td>
<td align="right">7,426</td>
<td align="right">49.23%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Staphylococcus aureus</td>
<td align="right">3,689</td>
<td align="right">24.51%</td>
<td align="right">11,132</td>
<td align="right">73.96%</td>
<td align="right">3,769</td>
<td align="right">24.99%</td>
<td align="right">11,195</td>
<td align="right">74.21%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Streptococcus pneumoniae</td>
<td align="right">2,398</td>
<td align="right">15.93%</td>
<td align="right">13,530</td>
<td align="right">89.89%</td>
<td align="right">2,340</td>
<td align="right">15.51%</td>
<td align="right">13,535</td>
<td align="right">89.72%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Klebsiella pneumoniae</td>
<td align="right">1,521</td>
<td align="right">10.11%</td>
<td align="right">15,051</td>
<td align="right">1,550</td>
<td align="right">10.28%</td>
<td align="right">15,085</td>
<td align="right">100.00%</td>
</tr>
</tbody>
@ -982,7 +982,7 @@ Longest: 24</p>
<p>The functions <code><a href="../reference/proportion.html">resistance()</a></code> and <code><a href="../reference/proportion.html">susceptibility()</a></code> can be used to calculate antimicrobial resistance or susceptibility. For more specific analyses, the functions <code><a href="../reference/proportion.html">proportion_S()</a></code>, <code><a href="../reference/proportion.html">proportion_SI()</a></code>, <code><a href="../reference/proportion.html">proportion_I()</a></code>, <code><a href="../reference/proportion.html">proportion_IR()</a></code> and <code><a href="../reference/proportion.html">proportion_R()</a></code> can be used to determine the proportion of a specific antimicrobial outcome.</p>
<p>As per the EUCAST guideline of 2019, we calculate resistance as the proportion of R (<code><a href="../reference/proportion.html">proportion_R()</a></code>, equal to <code><a href="../reference/proportion.html">resistance()</a></code>) and susceptibility as the proportion of S and 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="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/proportion.html">resistance</a></span>(AMX)</a>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4655505</span></a></code></pre></div>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] 0.4684123</span></a></code></pre></div>
<p>Or can be used in conjuction with <code><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">summarise()</a></code>, both from the <code>dplyr</code> package:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb26-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital) <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -995,19 +995,19 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4651671</td>
<td align="center">0.4666964</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4687618</td>
<td align="center">0.4711845</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4569626</td>
<td align="center">0.4627451</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4668462</td>
<td align="center">0.4704102</td>
</tr>
</tbody>
</table>
@ -1025,23 +1025,23 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Hospital A</td>
<td align="center">0.4651671</td>
<td align="center">4579</td>
<td align="center">0.4666964</td>
<td align="center">4489</td>
</tr>
<tr class="even">
<td align="center">Hospital B</td>
<td align="center">0.4687618</td>
<td align="center">5282</td>
<td align="center">0.4711845</td>
<td align="center">5327</td>
</tr>
<tr class="odd">
<td align="center">Hospital C</td>
<td align="center">0.4569626</td>
<td align="center">2219</td>
<td align="center">0.4627451</td>
<td align="center">2295</td>
</tr>
<tr class="even">
<td align="center">Hospital D</td>
<td align="center">0.4668462</td>
<td align="center">2971</td>
<td align="center">0.4704102</td>
<td align="center">2974</td>
</tr>
</tbody>
</table>
@ -1061,27 +1061,27 @@ Longest: 24</p>
<tbody>
<tr class="odd">
<td align="center">Escherichia</td>
<td align="center">0.9183125</td>
<td align="center">0.9039366</td>
<td align="center">0.9934166</td>
<td align="center">0.9243200</td>
<td align="center">0.8955023</td>
<td align="center">0.9934016</td>
</tr>
<tr class="even">
<td align="center">Klebsiella</td>
<td align="center">0.9119001</td>
<td align="center">0.8954635</td>
<td align="center">0.9960552</td>
<td align="center">0.9174194</td>
<td align="center">0.9019355</td>
<td align="center">0.9967742</td>
</tr>
<tr class="odd">
<td align="center">Staphylococcus</td>
<td align="center">0.9262673</td>
<td align="center">0.9227433</td>
<td align="center">0.9951206</td>
<td align="center">0.9193420</td>
<td align="center">0.9211993</td>
<td align="center">0.9936323</td>
</tr>
<tr class="even">
<td align="center">Streptococcus</td>
<td align="center">0.6092577</td>
<td align="center">0.6128205</td>
<td align="center">0.0000000</td>
<td align="center">0.6092577</td>
<td align="center">0.6128205</td>
</tr>
</tbody>
</table>
@ -1155,7 +1155,7 @@ Longest: 24</p>
<div id="independence-test" class="section level2">
<h2 class="hasAnchor">
<a href="#independence-test" class="anchor"></a>Independence test</h2>
<p>The next example uses the included <code>example_isolates</code>, which is an anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found in septic patients in 4 different hospitals in the Netherlands, between 2001 and 2017. This <code>data.frame</code> can be used to practice AMR analysis.</p>
<p>The next example uses the <code>example_isolates</code> data set. This is a data set included with this package and contains 2,000 microbial isolates with their full antibiograms. It reflects reality and can be used to practice AMR analysis.</p>
<p>We will compare the resistance to fosfomycin (column <code>FOS</code>) in hospital A and D. The input for the <code><a href="https://rdrr.io/r/stats/fisher.test.html">fisher.test()</a></code> can be retrieved with a transformation like this:</p>
<div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb34-1" data-line-number="1"><span class="co"># use package 'tidyr' to pivot data; </span></a>
<a class="sourceLine" id="cb34-2" data-line-number="2"><span class="co"># it gets installed with this 'AMR' package</span></a>

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@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">10 November 2019</h4>
<h4 class="date">18 November 2019</h4>
<div class="hidden name"><code>EUCAST.Rmd</code></div>

63
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@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to determine multi-drug resistance (MDR)</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">10 November 2019</h4>
<h4 class="date">18 November 2019</h4>
<div class="hidden name"><code>MDR.Rmd</code></div>
@ -196,11 +196,11 @@
<p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine multi-drug resistant organisms (MDRO).</p>
<p>With the function <code><a href="../reference/mdro.html">mdro()</a></code>, you can determine which micro-organisms are multi-drug resistant organisms (MDRO).</p>
<div id="type-of-input" class="section level4">
<h4 class="hasAnchor">
<a href="#type-of-input" class="anchor"></a>Type of input</h4>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> takes a data set as input, such as a regular <code>data.frame</code>. It automatically determines the right columns for info about your isolates, like the name of the species and all columns with results of antimicrobial agents. See the help page for more info about how to set the right settings for your data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function takes a data set as input, such as a regular <code>data.frame</code>. It tries to automatically determine the right columns for info about your isolates, like the name of the species and all columns with results of antimicrobial agents. See the help page for more info about how to set the right settings for your data with the command <code><a href="../reference/mdro.html">?mdro</a></code>.</p>
<p>For WHONET data (and most other data), all settings are automatically set correctly.</p>
</div>
<div id="guidelines" class="section level4">
@ -229,7 +229,8 @@ The German national guideline - Mueller et al. (2015) Antimicrobial Resistance a
<div id="examples" class="section level4">
<h4 class="hasAnchor">
<a href="#examples" class="anchor"></a>Examples</h4>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered <code>factor</code>. For example, the output of the default guideline by Magiorakos <em>et al.</em> returns a <code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in that order. If we test that guideline on the included <code>example_isolates</code> data set, we get:</p>
<p>The <code><a href="../reference/mdro.html">mdro()</a></code> function always returns an ordered <code>factor</code>. For example, the output of the default guideline by Magiorakos <em>et al.</em> returns a <code>factor</code> with levels ‘Negative’, ‘MDR’, ‘XDR’ or ‘PDR’ in that order.</p>
<p>The next example uses the <code>example_isolates</code> data set. This is a data set included with this package and contains 2,000 microbial isolates with their full antibiograms. It reflects reality and can be used to practice AMR analysis. If we test the MDR/XDR/PDR guideline on this data set, we get:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span>(dplyr) <span class="co"># to support pipes: %&gt;%</span></a></code></pre></div>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1">example_isolates <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb2-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="../reference/mdro.html">mdro</a></span>() <span class="op">%&gt;%</span><span class="st"> </span></a>
@ -306,14 +307,14 @@ Unique: 2</p>
<p>The data set now looks like this:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(my_TB_data)</a>
<a class="sourceLine" id="cb5-2" data-line-number="2"><span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span></a>
<a class="sourceLine" id="cb5-3" data-line-number="3"><span class="co"># 1 S R S R I R</span></a>
<a class="sourceLine" id="cb5-4" data-line-number="4"><span class="co"># 2 I S R I R R</span></a>
<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="co"># 3 S R S S S R</span></a>
<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># 4 R S S S R S</span></a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># 5 S S S S I R</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># 6 I S R I S S</span></a>
<a class="sourceLine" id="cb5-3" data-line-number="3"><span class="co"># 1 S R S S S S</span></a>
<a class="sourceLine" id="cb5-4" data-line-number="4"><span class="co"># 2 S S S S R S</span></a>
<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="co"># 3 S R R S S R</span></a>
<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># 4 S R S S I S</span></a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># 5 R S S I R S</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># 6 R R S S R R</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># kanamycin</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># 1 S</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># 1 R</span></a>
<a class="sourceLine" id="cb5-11" data-line-number="11"><span class="co"># 2 R</span></a>
<a class="sourceLine" id="cb5-12" data-line-number="12"><span class="co"># 3 R</span></a>
<a class="sourceLine" id="cb5-13" data-line-number="13"><span class="co"># 4 S</span></a>
@ -335,7 +336,7 @@ Unique: 2</p>
<a class="sourceLine" id="cb7-11" data-line-number="11"><span class="co"># Author: WHO (World Health Organization)</span></a>
<a class="sourceLine" id="cb7-12" data-line-number="12"><span class="co"># Source: https://www.who.int/tb/publications/pmdt_companionhandbook/en/</span></a>
<a class="sourceLine" id="cb7-13" data-line-number="13"><span class="co"># </span></a>
<a class="sourceLine" id="cb7-14" data-line-number="14"><span class="co"># =&gt; Found 4320 MDROs out of 5000 tested isolates (86.4%)</span></a></code></pre></div>
<a class="sourceLine" id="cb7-14" data-line-number="14"><span class="co"># =&gt; Found 4341 MDROs out of 5000 tested isolates (86.8%)</span></a></code></pre></div>
<p>Create a frequency table of the results:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1"><span class="kw"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(my_TB_data<span class="op">$</span>mdr)</a></code></pre></div>
<p><strong>Frequency table</strong></p>
@ -356,40 +357,40 @@ Unique: 5</p>
<tr class="odd">
<td align="left">1</td>
<td align="left">Mono-resistant</td>
<td align="right">3243</td>
<td align="right">64.86%</td>
<td align="right">3243</td>
<td align="right">64.86%</td>
<td align="right">3281</td>
<td align="right">65.62%</td>
<td align="right">3281</td>
<td align="right">65.62%</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">Negative</td>
<td align="right">680</td>
<td align="right">13.60%</td>
<td align="right">3923</td>
<td align="right">78.46%</td>
<td align="right">659</td>
<td align="right">13.18%</td>
<td align="right">3940</td>
<td align="right">78.80%</td>
</tr>
<tr class="odd">
<td align="left">3</td>
<td align="left">Multi-drug-resistant</td>
<td align="right">587</td>
<td align="right">11.74%</td>
<td align="right">4510</td>
<td align="right">90.20%</td>
<td align="right">571</td>
<td align="right">11.42%</td>
<td align="right">4511</td>
<td align="right">90.22%</td>
</tr>
<tr class="even">
<td align="left">4</td>
<td align="left">Poly-resistant</td>
<td align="right">302</td>
<td align="right">6.04%</td>
<td align="right">4812</td>
<td align="right">96.24%</td>
<td align="right">278</td>
<td align="right">5.56%</td>
<td align="right">4789</td>
<td align="right">95.78%</td>
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Extensively drug-resistant</td>
<td align="right">188</td>
<td align="right">3.76%</td>
<td align="right">211</td>
<td align="right">4.22%</td>
<td align="right">5000</td>
<td align="right">100.00%</td>
</tr>

4
docs/articles/SPSS.html
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@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9031</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to import data from SPSS / SAS / Stata</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">15 November 2019</h4>
<h4 class="date">18 November 2019</h4>
<div class="hidden name"><code>SPSS.Rmd</code></div>

4
docs/articles/WHONET.html
View File

@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9029</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>How to work with WHONET data</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">10 November 2019</h4>
<h4 class="date">18 November 2019</h4>
<div class="hidden name"><code>WHONET.Rmd</code></div>

102
docs/articles/benchmarks.html
View File

@ -41,7 +41,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
</span>
</div>
@ -187,7 +187,7 @@
<h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">16 October 2019</h4>
<h4 class="date">18 November 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -221,21 +221,21 @@
<a class="sourceLine" id="cb2-16" data-line-number="16"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(S.aureus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 9.9 10 14 11 12 35 10</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 33.0 33 39 38 39 52 10</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 32.0 36 44 38 56 68 10</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 10.0 10 13 11 11 34 10</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 10.0 11 19 12 33 42 10</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 25.0 26 32 28 32 53 10</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 24.0 25 31 27 30 52 10</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 31.0 32 39 34 38 84 10</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 610.0 640 680 680 710 770 10</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 330.0 340 350 350 360 370 10</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 9.8 10 13 11 12 34 10</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 20.0 22 29 24 31 57 10</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 20.0 20 29 23 42 47 10</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 21.0 23 30 25 43 47 10</span></a></code></pre></div>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 10 10 16 11 13 58 10</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 33 34 50 45 67 80 10</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 34 38 44 39 43 72 10</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 10 11 16 12 15 44 10</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 11 11 17 12 14 59 10</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 26 30 37 33 48 54 10</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 26 27 31 28 32 48 10</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 31 35 37 37 40 44 10</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 650 690 750 710 840 900 10</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 380 410 430 430 440 500 10</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 10 11 20 11 37 44 10</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 20 22 51 29 47 220 10</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 21 23 32 25 41 57 10</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 20 21 23 22 23 27 10</span></a></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-5-1.png" width="562.5"></p>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first one is a WHONET code) or common laboratory codes, or common full organism names like the last one. Full organism names are always preferred.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Methanosarcina semesiae</em> (<code>B_MTHNSR_SEMS</code>), a bug probably never found before in humans:</p>
@ -247,19 +247,19 @@
<a class="sourceLine" id="cb3-6" data-line-number="6"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(M.semesiae, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("metsem") 1343.00 1385.00 1398.00 1403.00 1418.0</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("METSEM") 1299.00 1356.00 1397.00 1396.00 1442.0</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("M. semesiae") 1892.00 2028.00 2052.00 2041.00 2084.0</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("M. semesiae") 1990.00 2017.00 2062.00 2032.00 2094.0</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Methanosarcina semesiae") 32.63 33.24 38.58 35.82 40.2</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("metsem") 1415.00 1467.00 1505.00 1493.00 1537.00</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("METSEM") 1447.00 1488.00 1530.00 1521.00 1555.00</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("M. semesiae") 2216.00 2239.00 2293.00 2284.00 2351.00</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("M. semesiae") 2143.00 2212.00 2304.00 2307.00 2332.00</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Methanosarcina semesiae") 32.44 35.59 43.59 38.19 45.88</span></a>
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co"># max neval</span></a>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1437.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 1488.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2169.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2245.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 57.04 10</span></a></code></pre></div>
<p>That takes 14.3 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Methanosarcina semesiae</em>) are almost fast - these are the most probable input from most data sets.</p>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1627.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 1628.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2395.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2535.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 69.48 10</span></a></code></pre></div>
<p>That takes 13.8 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Methanosarcina semesiae</em>) are almost fast - these are the most probable input from most data sets.</p>
<p>In the figure below, we compare <em>Escherichia coli</em> (which is very common) with <em>Prevotella brevis</em> (which is moderately common) and with <em>Methanosarcina semesiae</em> (which is uncommon):</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-9-1.png" width="562.5"></p>
<p>In reality, the <code><a href="../reference/as.mo.html">as.mo()</a></code> functions <strong>learns from its own output to speed up determinations for next times</strong>. In above figure, this effect was disabled to show the difference with the boxplot below - when you would use <code><a href="../reference/as.mo.html">as.mo()</a></code> yourself:</p>
@ -296,8 +296,8 @@
<a class="sourceLine" id="cb4-24" data-line-number="24"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb4-25" data-line-number="25"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb4-26" data-line-number="26"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 645 661 683 672 686 771 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.67 seconds (671 ms). You only lose time on your unique input values.</p>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 642 674 702 687 713 843 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.69 seconds (686 ms). You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
@ -309,10 +309,10 @@
<a class="sourceLine" id="cb5-4" data-line-number="4"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.380 6.530 7.750 7.180 8.21 11.30 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 24.300 25.500 30.400 26.900 31.60 54.80 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.803 0.827 0.926 0.869 0.95 1.22 10</span></a></code></pre></div>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.350 6.420 6.880 6.530 7.180 8.56 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 24.600 25.100 31.300 25.700 27.900 62.80 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.798 0.867 0.914 0.892 0.931 1.14 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0009 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),</a>
<a class="sourceLine" id="cb6-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),</a>
@ -326,14 +326,14 @@
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb6-11" data-line-number="11"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-12" data-line-number="12"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.509 0.530 0.681 0.565 0.661 1.630 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.518 0.526 0.598 0.553 0.564 0.875 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.848 0.882 1.100 0.990 1.180 1.920 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.566 0.592 0.734 0.714 0.765 1.120 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.486 0.522 0.555 0.542 0.551 0.681 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.466 0.493 0.598 0.553 0.586 1.110 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.462 0.498 0.598 0.525 0.671 0.921 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.480 0.489 0.566 0.508 0.628 0.756 10</span></a></code></pre></div>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.446 0.459 0.471 0.475 0.481 0.485 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.502 0.506 0.518 0.513 0.521 0.568 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.774 0.802 0.811 0.815 0.823 0.838 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.505 0.511 0.532 0.515 0.534 0.627 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.467 0.469 0.495 0.478 0.481 0.676 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.457 0.467 0.478 0.479 0.484 0.509 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.452 0.460 0.467 0.471 0.472 0.478 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.460 0.469 0.473 0.473 0.480 0.486 10</span></a></code></pre></div>
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
</div>
<div id="results-in-other-languages" class="section level3">
@ -359,14 +359,14 @@
<a class="sourceLine" id="cb7-17" data-line-number="17"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="kw"><a href="https://rdrr.io/r/base/print.html">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb7-19" data-line-number="19"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 20.01 20.76 28.07 22.47 29.04 54.04 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 21.95 22.28 26.91 22.72 24.24 58.36 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 27.57 27.96 47.86 31.50 54.01 149.80 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 22.08 22.13 28.59 24.11 26.45 58.61 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 21.73 22.33 25.39 25.30 26.90 29.57 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 22.23 22.98 24.95 23.45 23.70 34.08 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 22.02 23.03 24.80 24.37 27.14 28.33 10</span></a></code></pre></div>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 20.49 21.64 27.36 23.44 27.96 53.91 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 23.26 23.37 28.22 24.42 26.13 60.60 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 28.62 29.74 36.90 30.18 33.12 72.41 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 21.77 23.08 27.71 24.75 26.98 55.14 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 22.54 23.37 25.19 25.25 26.41 29.08 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 23.04 23.99 30.97 26.14 30.78 52.61 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 22.40 23.07 24.26 23.14 24.44 31.60 10</span></a></code></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9033</span>
</span>
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
</span>
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@ -187,7 +187,7 @@
<h1>How to predict antimicrobial resistance</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">16 October 2019</h4>
<h4 class="date">18 November 2019</h4>
<div class="hidden name"><code>resistance_predict.Rmd</code></div>

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