Built site for AMR: 2.0.0.9035@7cd9ca2

articles/AMR.html

@@ -204,7 +204,7 @@
 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 11 July 2023.</p>
+generated on 12 July 2023.</p>
 <div class="section level2">
 <h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
 </h2>
@@ -260,21 +260,21 @@ make the structure of your data generally look like this:</p>
 </tr></thead>
 <tbody>
 <tr class="odd">
-<td align="center">2023-07-11</td>
+<td align="center">2023-07-12</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">2023-07-11</td>
+<td align="center">2023-07-12</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">2023-07-11</td>
+<td align="center">2023-07-12</td>
 <td align="center">efgh</td>
 <td align="center">Escherichia coli</td>
 <td align="center">R</td>

articles/MDR.html

@@ -402,19 +402,19 @@ names or codes, this would have worked exactly the same way:</p>
 <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">my_TB_data</span><span class="op">)</span></span>
 <span><span class="co">#&gt;   rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span></span>
-<span><span class="co">#&gt; 1          S         S            I          S            I            I</span></span>
+<span><span class="co">#&gt; 1          S         R            R          I            I            R</span></span>
-<span><span class="co">#&gt; 2          S         I            R          R            S            S</span></span>
+<span><span class="co">#&gt; 2          I         R            R          I            S            I</span></span>
-<span><span class="co">#&gt; 3          R         S            I          R            I            I</span></span>
+<span><span class="co">#&gt; 3          I         S            I          R            R            I</span></span>
-<span><span class="co">#&gt; 4          S         I            I          R            R            R</span></span>
+<span><span class="co">#&gt; 4          R         R            I          R            I            S</span></span>
-<span><span class="co">#&gt; 5          S         R            I          S            R            R</span></span>
+<span><span class="co">#&gt; 5          R         S            I          I            I            S</span></span>
-<span><span class="co">#&gt; 6          S         S            I          S            S            I</span></span>
+<span><span class="co">#&gt; 6          I         S            I          S            I            R</span></span>
 <span><span class="co">#&gt;   kanamycin</span></span>
-<span><span class="co">#&gt; 1         I</span></span>
+<span><span class="co">#&gt; 1         S</span></span>
-<span><span class="co">#&gt; 2         S</span></span>
+<span><span class="co">#&gt; 2         I</span></span>
-<span><span class="co">#&gt; 3         S</span></span>
+<span><span class="co">#&gt; 3         R</span></span>
-<span><span class="co">#&gt; 4         I</span></span>
+<span><span class="co">#&gt; 4         R</span></span>
-<span><span class="co">#&gt; 5         S</span></span>
+<span><span class="co">#&gt; 5         I</span></span>
-<span><span class="co">#&gt; 6         S</span></span></code></pre></div>
+<span><span class="co">#&gt; 6         I</span></span></code></pre></div>
 <p>We can now add the interpretation of MDR-TB to our data set. You can
 use:</p>
 <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
@@ -455,40 +455,40 @@ Unique: 5</p>
 <tr class="odd">
 <td align="left">1</td>
 <td align="left">Mono-resistant</td>
-<td align="right">3201</td>
+<td align="right">3187</td>
-<td align="right">64.02%</td>
+<td align="right">63.74%</td>
-<td align="right">3201</td>
+<td align="right">3187</td>
-<td align="right">64.02%</td>
+<td align="right">63.74%</td>
 </tr>
 <tr class="even">
 <td align="left">2</td>
 <td align="left">Negative</td>
-<td align="right">976</td>
+<td align="right">1017</td>
-<td align="right">19.52%</td>
+<td align="right">20.34%</td>
-<td align="right">4177</td>
+<td align="right">4204</td>
-<td align="right">83.54%</td>
+<td align="right">84.08%</td>
 </tr>
 <tr class="odd">
 <td align="left">3</td>
 <td align="left">Multi-drug-resistant</td>
-<td align="right">477</td>
+<td align="right">456</td>
-<td align="right">9.54%</td>
+<td align="right">9.12%</td>
-<td align="right">4654</td>
+<td align="right">4660</td>
-<td align="right">93.08%</td>
+<td align="right">93.20%</td>
 </tr>
 <tr class="even">
 <td align="left">4</td>
 <td align="left">Poly-resistant</td>
-<td align="right">241</td>
+<td align="right">230</td>
-<td align="right">4.82%</td>
+<td align="right">4.60%</td>
-<td align="right">4895</td>
+<td align="right">4890</td>
-<td align="right">97.90%</td>
+<td align="right">97.80%</td>
 </tr>
 <tr class="odd">
 <td align="left">5</td>
 <td align="left">Extensively drug-resistant</td>
-<td align="right">105</td>
+<td align="right">110</td>
-<td align="right">2.10%</td>
+<td align="right">2.20%</td>
 <td align="right">5000</td>
 <td align="right">100.00%</td>
 </tr>

articles/PCA.html

@@ -307,7 +307,7 @@ function:</p>
 <span><span class="co">#&gt; [1] "Caryophanales"    "Enterobacterales" "Lactobacillales"  "Pseudomonadales"</span></span>
 <span><span class="co">#&gt; Importance of components:</span></span>
 <span><span class="co">#&gt;                           PC1    PC2    PC3     PC4     PC5     PC6       PC7</span></span>
-<span><span class="co">#&gt; Standard deviation     2.1539 1.6807 0.6138 0.33879 0.20808 0.03140 9.577e-17</span></span>
+<span><span class="co">#&gt; Standard deviation     2.1539 1.6807 0.6138 0.33879 0.20808 0.03140 1.232e-16</span></span>
 <span><span class="co">#&gt; Proportion of Variance 0.5799 0.3531 0.0471 0.01435 0.00541 0.00012 0.000e+00</span></span>
 <span><span class="co">#&gt; Cumulative Proportion  0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00</span></span></code></pre></div>
 <pre><code><span><span class="co">#&gt; Groups (n=4, named as 'order'):</span></span>

articles/datasets.html

@@ -193,7 +193,7 @@
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.svg" class="logo" alt=""><h1>Data sets for download / own use</h1>
             
-            <h4 data-toc-skip class="date">11 July 2023</h4>
+            <h4 data-toc-skip class="date">12 July 2023</h4>
       
       <small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
       <div class="d-none name"><code>datasets.Rmd</code></div>
@@ -243,7 +243,6 @@ Feather file</a> (5.5 MB)<br>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.parquet" class="external-link">Apache
 Parquet file</a> (2.6 MB)<br>
 </li>
-<li><em>(unavailable as SAS data (SAS) file)</em></li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.xpt" class="external-link">SAS
 transport (XPT) file</a> (48.6 MB)<br>
 </li>
@@ -552,7 +551,6 @@ Feather file</a> (0.1 MB)<br>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antibiotics.parquet" class="external-link">Apache
 Parquet file</a> (97 kB)<br>
 </li>
-<li><em>(unavailable as SAS data (SAS) file)</em></li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antibiotics.xpt" class="external-link">SAS
 transport (XPT) file</a> (1.4 MB)<br>
 </li>
@@ -753,7 +751,6 @@ Feather file</a> (15 kB)<br>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antivirals.parquet" class="external-link">Apache
 Parquet file</a> (13 kB)<br>
 </li>
-<li><em>(unavailable as SAS data (SAS) file)</em></li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/antivirals.xpt" class="external-link">SAS
 transport (XPT) file</a> (68 kB)<br>
 </li>
@@ -914,7 +911,7 @@ column names:<br><em>guideline</em>, <em>type</em>, <em>method</em>, <em>site</e
 <em>uti</em>.</p>
 <p>This data set is in R available as <code>clinical_breakpoints</code>,
 after you load the <code>AMR</code> package.</p>
-<p>It was last updated on 10 July 2023 17:04:12 UTC. Find more info
+<p>It was last updated on 12 July 2023 10:41:25 UTC. Find more info
 about the structure of this data set <a href="https://msberends.github.io/AMR/reference/clinical_breakpoints.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
@@ -933,7 +930,6 @@ Feather file</a> (1.2 MB)<br>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/clinical_breakpoints.parquet" class="external-link">Apache
 Parquet file</a> (87 kB)<br>
 </li>
-<li><em>(unavailable as SAS data (SAS) file)</em></li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/clinical_breakpoints.xpt" class="external-link">SAS
 transport (XPT) file</a> (7.7 MB)<br>
 </li>
@@ -1115,7 +1111,6 @@ Feather file</a> (1.2 MB)<br>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.parquet" class="external-link">Apache
 Parquet file</a> (0.2 MB)<br>
 </li>
-<li><em>(unavailable as SAS data (SAS) file)</em></li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/intrinsic_resistant.xpt" class="external-link">SAS
 transport (XPT) file</a> (9.5 MB)<br>
 </li>
@@ -1404,7 +1399,6 @@ Feather file</a> (21 kB)<br>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/dosage.parquet" class="external-link">Apache
 Parquet file</a> (9 kB)<br>
 </li>
-<li><em>(unavailable as SAS data (SAS) file)</em></li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/dosage.xpt" class="external-link">SAS
 transport (XPT) file</a> (0.1 MB)<br>
 </li>
@@ -2052,14 +2046,14 @@ reality and can be used to practise AMR data analysis.</p>
 <code>microorganisms.groups</code>: Species Groups and
 Microbiological Complexes<a class="anchor" aria-label="anchor" href="#microorganisms-groups-species-groups-and-microbiological-complexes"></a>
 </h2>
-<p>A data set with 444 rows and 4 columns, containing the following
+<p>A data set with 448 rows and 4 columns, containing the following
 column names:<br><em>mo_group</em>, <em>mo</em>, <em>mo_group_name</em>, and
 <em>mo_name</em>.</p>
 <p>This data set is in R available as
 <code>microorganisms.groups</code>, after you load the <code>AMR</code>
 package.</p>
-<p>It was last updated on 8 July 2023 15:30:05 UTC. Find more info about
+<p>It was last updated on 12 July 2023 10:41:25 UTC. Find more info
-the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.groups.html">here</a>.</p>
+about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.groups.html">here</a>.</p>
 <p><strong>Direct download links:</strong></p>
 <ul>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.groups.rds" class="external-link">original
@@ -2077,7 +2071,6 @@ Feather file</a> (17 kB)<br>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.groups.parquet" class="external-link">Apache
 Parquet file</a> (12 kB)<br>
 </li>
-<li><em>(unavailable as SAS data (SAS) file)</em></li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.groups.xpt" class="external-link">SAS
 transport (XPT) file</a> (0 kB)<br>
 </li>
@@ -2177,7 +2170,6 @@ Feather file</a> (85 kB)<br>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.parquet" class="external-link">Apache
 Parquet file</a> (57 kB)<br>
 </li>
-<li><em>(unavailable as SAS data (SAS) file)</em></li>
 <li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.xpt" class="external-link">SAS
 transport (XPT) file</a> (0 kB)<br>
 </li>

pkgdown.yml

@@ -11,7 +11,7 @@ articles:
   other_pkg: other_pkg.html
   resistance_predict: resistance_predict.html
   welcome_to_AMR: welcome_to_AMR.html
-last_built: 2023-07-11T12:34Z
+last_built: 2023-07-12T10:46Z
 urls:
   reference: https://msberends.github.io/AMR/reference
   article: https://msberends.github.io/AMR/articles

reference/age.html

@@ -222,16 +222,16 @@
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="va">df</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    birth_date age age_exact age_at_y2k</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1  1950-05-27  73  73.12329         49</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 1  1966-03-31  57  57.28219         33</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2  1951-02-26  72  72.36986         48</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 2  1978-05-07  45  45.18082         21</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3  1944-02-02  79  79.43562         55</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 3  1938-05-09  85  85.17534         61</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4  1948-07-31  74  74.94521         51</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 4  1944-10-01  78  78.77808         55</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5  1973-07-03  50  50.02192         26</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 5  1933-10-17  89  89.73425         66</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6  1966-03-18  57  57.31507         33</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 6  1994-05-11  29  29.16986          5</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 7  1940-03-31  83  83.27945         59</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 7  1950-03-26  73  73.29589         49</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 8  1954-05-16  69  69.15342         45</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 8  1999-12-14  23  23.57534          0</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 9  1943-12-26  79  79.53973         56</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 9  1952-02-05  71  71.43014         47</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1997-02-17  26  26.39452          2</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1991-03-26  32  32.29589          8</span>
 </code></pre></div>
     </div>
   </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>

reference/antibiotic_class_selectors.html

@@ -626,11 +626,11 @@ In short, if you have a column name that resembles an antimicrobial drug, it wil
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 1</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   kefzol</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> R     </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> I     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> S     </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> I     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> I     </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> R     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> S     </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> I     </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> R     </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> I     </span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
 <span class="r-in"><span>  <span class="co"># get AMR for all aminoglycosides e.g., per ward:</span></span></span>

reference/as.sir.html

@@ -567,19 +567,19 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 13 × 13</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    datetime            index ab_user    mo_user    ab   mo                input</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span>              <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;ab&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>              <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2023-07-11 <span style="color: #949494;">12:34:59</span>     1 TOB        Escherich… TOB  B_[ORD]_ENTRBCTR 16    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2023-07-12 <span style="color: #949494;">10:47:46</span>     1 TOB        Escherich… TOB  B_[ORD]_ENTRBCTR 16    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2023-07-11 <span style="color: #949494;">12:34:59</span>     1 GEN        Escherich… GEN  B_[ORD]_ENTRBCTR 18    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2023-07-12 <span style="color: #949494;">10:47:46</span>     1 GEN        Escherich… GEN  B_[ORD]_ENTRBCTR 18    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2023-07-11 <span style="color: #949494;">12:34:59</span>     1 CIP        Escherich… CIP  B_[ORD]_ENTRBCTR  0.256</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2023-07-12 <span style="color: #949494;">10:47:45</span>     1 CIP        Escherich… CIP  B_[ORD]_ENTRBCTR  0.256</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2023-07-11 <span style="color: #949494;">12:34:59</span>     1 AMP        Escherich… AMP  B_[ORD]_ENTRBCTR  8    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2023-07-12 <span style="color: #949494;">10:47:45</span>     1 AMP        Escherich… AMP  B_[ORD]_ENTRBCTR  8    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2023-07-11 <span style="color: #949494;">12:34:52</span>     1 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      0.01 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2023-07-12 <span style="color: #949494;">10:47:35</span>     1 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      0.01 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2023-07-11 <span style="color: #949494;">12:34:52</span>     2 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      2    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2023-07-12 <span style="color: #949494;">10:47:35</span>     2 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      2    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2023-07-11 <span style="color: #949494;">12:34:52</span>     3 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      4    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2023-07-12 <span style="color: #949494;">10:47:35</span>     3 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      4    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2023-07-11 <span style="color: #949494;">12:34:52</span>     4 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      8    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2023-07-12 <span style="color: #949494;">10:47:35</span>     4 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      8    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2023-07-11 <span style="color: #949494;">12:34:52</span>     1 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      2    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2023-07-12 <span style="color: #949494;">10:47:35</span>     1 AMX        B_STRPT_P… AMX  B_STRPT_PNMN      2    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2023-07-11 <span style="color: #949494;">12:34:51</span>     1 TOB        Escherich… TOB  B_[ORD]_ENTRBCTR 16    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2023-07-12 <span style="color: #949494;">10:47:35</span>     1 TOB        Escherich… TOB  B_[ORD]_ENTRBCTR 16    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">11</span> 2023-07-11 <span style="color: #949494;">12:34:51</span>     1 GEN        Escherich… GEN  B_[ORD]_ENTRBCTR 18    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">11</span> 2023-07-12 <span style="color: #949494;">10:47:34</span>     1 GEN        Escherich… GEN  B_[ORD]_ENTRBCTR 18    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">12</span> 2023-07-11 <span style="color: #949494;">12:34:51</span>     1 AMP        Escherich… AMP  B_[ORD]_ENTRBCTR 20    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">12</span> 2023-07-12 <span style="color: #949494;">10:47:34</span>     1 AMP        Escherich… AMP  B_[ORD]_ENTRBCTR 20    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">13</span> 2023-07-11 <span style="color: #949494;">12:34:51</span>     1 ampicillin Strep pneu AMP  B_STRPT_PNMN     18    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">13</span> 2023-07-12 <span style="color: #949494;">10:47:34</span>     1 ampicillin Strep pneu AMP  B_STRPT_PNMN     18    </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 6 more variables: outcome &lt;sir&gt;, method &lt;chr&gt;, breakpoint_S_R &lt;chr&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;</span></span>
 <span class="r-in"><span></span></span>

reference/get_episode.html

@@ -263,29 +263,27 @@
 <span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq_len</a></span><span class="op">(</span><span class="fl">2000</span><span class="op">)</span>, size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, <span class="op">]</span></span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># indices</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1] 45 35 41 11 45 48  8 20 33 25 40 28 46  4 21 29 19 11 30  3  3 15 28 18 45</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>   [1] 42 21 48 39  7 47 25 24 36  9  4 28 35 10 14  1 35 38 46 26 30  1  5 40 48</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [26] 39 17 25 14 38 49 32 39 36 34 26  8 20 44 13 21 47 27  6 47 30  9 26 42 31</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [26] 43 49 16  5 15 30 10 26  8  7 12 50 12  2 20 45 30 14 11 30 42 25 41 23 27</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [51]  7 18 23 43 30 28 22 19 42 10 13  7 13 15 39 23 36 11 32 46 35 49 38  6 12</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [51]  2 27 39 18 44 15 50 32 37 31 12 25 40 34 50 44 37 22 32 44 14 43 50 12 44</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [76]  5 27 27 37 16 17  1 37 43 24 47  2  5 28 12 14  3  4 46  1 36  5 50 40  5</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [76]  8 29  6 19 33 50 42  8 13 42 44 17  4 42 11 48  3  7  8 28 39 49 38 49 21</span>
 <span class="r-in"><span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># TRUE/FALSE</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   [1]  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>   [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [13]  TRUE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE FALSE  TRUE FALSE  TRUE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [13]  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [25] FALSE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [25] FALSE  TRUE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE  TRUE FALSE  TRUE</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [37] FALSE FALSE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE FALSE FALSE  TRUE FALSE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [37]  TRUE FALSE  TRUE  TRUE  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE  TRUE</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [49]  TRUE  TRUE  TRUE FALSE  TRUE  TRUE FALSE FALSE  TRUE FALSE FALSE  TRUE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [49]  TRUE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [61] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [73] FALSE FALSE  TRUE  TRUE FALSE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [73] FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE  TRUE</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [85]  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [85] FALSE FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>  [97] FALSE  TRUE FALSE FALSE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>  [97] FALSE FALSE FALSE FALSE</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># filter on results from the third 60-day episode only, using base R</span></span></span>
 <span class="r-in"><span><span class="va">df</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span> <span class="op">==</span> <span class="fl">3</span><span class="op">)</span>, <span class="op">]</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 46</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 1 × 46</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   date       patient   age gender ward  mo           PEN   OXA   FLC   AMX  </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;date&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2003-04-07 F35553     51 M      ICU   B_STPHY_AURS R     NA    S     R    </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> 2002-09-23 F35553     51 M      ICU   B_STPHY_AURS S     NA    S     NA   </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> 2003-04-02 6BC362     62 M      ICU   B_STRPT_PNMN S     NA    NA    S    </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> 2003-04-21 6BC362     62 M      ICU   B_STPHY_CONS R     NA    R     R    </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 36 more variables: AMC &lt;sir&gt;, AMP &lt;sir&gt;, TZP &lt;sir&gt;, CZO &lt;sir&gt;, FEP &lt;sir&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   CXM &lt;sir&gt;, FOX &lt;sir&gt;, CTX &lt;sir&gt;, CAZ &lt;sir&gt;, CRO &lt;sir&gt;, GEN &lt;sir&gt;,</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;">#   TOB &lt;sir&gt;, AMK &lt;sir&gt;, KAN &lt;sir&gt;, TMP &lt;sir&gt;, SXT &lt;sir&gt;, NIT &lt;sir&gt;,</span></span>
@@ -319,19 +317,19 @@
 <span class="r-in"><span>    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">condition</span>, <span class="va">date</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 4</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups:   patient, condition [97]</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups:   patient, condition [96]</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    patient date       condition new_episode</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;date&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span>      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 023456  2012-11-24 A         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 032343  2003-06-09 B         TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 036063  2010-01-28 B         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 05C73F  2006-01-12 C         TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 047634  2004-06-28 C         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 066895  2002-02-27 C         TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 059414  2006-07-21 C         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 067927  2002-02-14 C         TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 05C73F  2006-01-12 C         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 080086  2010-08-08 A         TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 067927  2002-01-29 B         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 101305  2006-12-13 C         TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 078381  2014-07-17 C         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 105248  2005-06-16 B         TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 0C0688  2014-09-05 C         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 116866  2011-11-07 B         TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 0DBF93  2015-12-03 A         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 122506  2007-08-10 C         TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 0E2483  2007-08-10 B         TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 141061  2014-10-22 A         TRUE       </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
@@ -348,16 +346,16 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups:   ward, patient [92]</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    ward     date       patient new_index new_logical</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;date&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span>      </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> Clinical 2012-11-24 023456          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> Clinical 2003-06-09 032343          1 TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> Clinical 2010-01-28 036063          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> Clinical 2006-01-12 05C73F          1 TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> Clinical 2004-06-28 047634          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> Clinical 2002-02-27 066895          1 TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> Clinical 2006-07-21 059414          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> ICU      2002-02-14 067927          1 TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> Clinical 2006-01-12 05C73F          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> Clinical 2010-08-08 080086          1 TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> ICU      2002-01-29 067927          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> Clinical 2006-12-13 101305          1 TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> ICU      2014-07-17 078381          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> Clinical 2005-06-16 105248          1 TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> Clinical 2014-09-05 0C0688          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> Clinical 2011-11-07 116866          1 TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> ICU      2015-12-03 0DBF93          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> Clinical 2007-08-10 122506          1 TRUE       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> ICU      2007-08-10 0E2483          1 TRUE       </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> Clinical 2014-10-22 141061          1 TRUE       </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
@@ -373,9 +371,9 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 3 × 5</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   ward       n_patients n_episodes_365 n_episodes_60 n_episodes_30</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;int&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;int&gt;</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical           56             13            39            47</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> Clinical           60             14            38            47</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU                28             11            25            28</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> ICU                28              9            22            25</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient          8              6             7             8</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> Outpatient          4              4             4             4</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># grouping on patients and microorganisms leads to the same</span></span></span>
 <span class="r-in"><span><span class="co"># results as first_isolate() when using 'episode-based':</span></span></span>
@@ -393,7 +391,7 @@
 <span class="r-in"><span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="https://rdrr.io/r/base/identical.html" class="external-link">identical</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] FALSE</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] TRUE</span>
 <span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># but is_new_episode() has a lot more flexibility than first_isolate(),</span></span></span>
 <span class="r-in"><span><span class="co"># since you can now group on anything that seems relevant:</span></span></span>
@@ -404,19 +402,19 @@
 <span class="r-in"><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="fu"><a href="https://dplyr.tidyverse.org/reference/group_data.html" class="external-link">group_vars</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span>, <span class="va">flag_episode</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 100 × 4</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups:   patient, mo, ward [96]</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># Groups:   patient, mo, ward [97]</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    patient mo           ward     flag_episode</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;lgl&gt;</span>       </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> E06844  B_STPHY_AURS ICU      TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 438196  B_STPHY_COHN Clinical TRUE        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 545388  B_KLBSL_PNMN Clinical TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> F37316  B_STRPT_PNMN ICU      TRUE        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 208305  B_PROTS_MRBL Clinical TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> D08278  B_ESCHR_COLI ICU      TRUE        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 990867  B_STPHY_AURS Clinical TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 992282  B_STRPT_GRPA Clinical TRUE        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> F74F4C  B_STRPT_PYGN Clinical TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> D63414  B_PROTS_MRBL Clinical TRUE        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 340066  B_ESCHR_COLI Clinical TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 450946  B_STPHY_EPDR ICU      TRUE        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> BB8157  B_STPHY_CONS Clinical TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> E95747  B_KLBSL_PNMN Clinical TRUE        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 533225  B_ESCHR_COLI Clinical TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 451990  B_ESCHR_COLI Clinical TRUE        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 023456  B_PROTS_MRBL Clinical TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 175532  B_ESCHR_COLI Clinical TRUE        </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> B73393  B_STPHY_CONS ICU      TRUE        </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 161373  B_ESCHR_COLI Clinical TRUE        </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 90 more rows</span></span>
 <span class="r-in"><span><span class="co"># }</span></span></span>
 </code></pre></div>

reference/kurtosis.html

@@ -199,9 +199,9 @@
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 3.014051</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 2.959141</span>
 <span class="r-in"><span><span class="fu">kurtosis</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">10000</span><span class="op">)</span>, excess <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.004766215</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] -0.04474896</span>
 </code></pre></div>
     </div>
   </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>

reference/skewness.html

@@ -198,7 +198,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">skewness</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Uniform.html" class="external-link">runif</a></span><span class="op">(</span><span class="fl">1000</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.02416193</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.07297999</span>
 </code></pre></div>
     </div>
   </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>

search.json

@@ -1 +1 @@
-[{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"How to conduct AMR data analysis","text":"Conducting AMR data analysis unfortunately requires -depth knowledge different scientific fields, makes hard right. least, requires: Good questions (always start !) reliable data thorough understanding (clinical) epidemiology, understand clinical epidemiological relevance possible bias results thorough understanding (clinical) microbiology/infectious diseases, understand microorganisms causal infections implications pharmaceutical treatment, well understanding intrinsic acquired microbial resistance Experience data analysis microbiological tests results, understand determination limitations MIC values interpretations SIR values Availability biological taxonomy microorganisms probably normalisation factors pharmaceuticals, defined daily doses (DDD) Available (inter-)national guidelines, profound methods apply course, instantly provide knowledge experience. AMR package, aimed providing (1) tools simplify antimicrobial resistance data cleaning, transformation analysis, (2) methods easily incorporate international guidelines (3) scientifically reliable reference data, including requirements mentioned . AMR package enables standardised reproducible AMR data analysis, application evidence-based rules, determination first isolates, translation various codes microorganisms antimicrobial agents, determination (multi-drug) resistant microorganisms, calculation antimicrobial resistance, prevalence future trends.","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"How to conduct AMR data analysis","text":"tutorial, create fake demonstration data work . can skip Cleaning data already data ready. start analysis, try make structure data generally look like :","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"How to conduct AMR data analysis","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2 RStudio. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. also use cleaner package, can used cleaning data creating frequency tables. AMR package contains data set example_isolates_unclean, might look data users extracted laboratory systems: AMR data analysis, like microorganism column contain valid, --date taxonomy, antibiotic columns cleaned SIR values well.","code":"library(dplyr) library(ggplot2) library(AMR)  # (if not yet installed, install with:) # install.packages(c(\"dplyr\", \"ggplot2\", \"AMR\")) example_isolates_unclean #> # A tibble: 3,000 × 8 #>    patient_id hospital date       bacteria      AMX   AMC   CIP   GEN   #>    <chr>      <chr>    <date>     <chr>         <chr> <chr> <chr> <chr> #>  1 J3         A        2012-11-21 E. coli       R     I     S     S     #>  2 R7         A        2018-04-03 K. pneumoniae R     I     S     S     #>  3 P3         A        2014-09-19 E. coli       R     S     S     S     #>  4 P10        A        2015-12-10 E. coli       S     I     S     S     #>  5 B7         A        2015-03-02 E. coli       S     S     S     S     #>  6 W3         A        2018-03-31 S. aureus     R     S     R     S     #>  7 J8         A        2016-06-14 E. coli       R     S     S     S     #>  8 M3         A        2015-10-25 E. coli       R     S     S     S     #>  9 J3         A        2019-06-19 E. coli       S     S     S     S     #> 10 G6         A        2015-04-27 S. aureus     S     S     S     S     #> # ℹ 2,990 more rows  # we will use 'our_data' as the data set name for this tutorial our_data <- example_isolates_unclean"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"How to conduct AMR data analysis","text":".mo(), users can transform arbitrary microorganism names codes current taxonomy. AMR package contains --date taxonomic data. specific, currently included data retrieved 11 Dec 2022. codes AMR packages come .mo() short, still human readable. importantly, .mo() supports kinds input: first character codes denote taxonomic kingdom, Bacteria (B), Fungi (F), Protozoa (P). AMR package also contain functions directly retrieve taxonomic properties, name, genus, species, family, order, even Gram-stain. start mo_ use .mo() internally, still arbitrary user input can used: Now can thus clean data: Apparently, uncertainty translation taxonomic codes. Let’s check : ’s good.","code":"as.mo(\"Klebsiella pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"K. pneumoniae\") #> ClLine truncated
+[{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"How to conduct AMR data analysis","text":"Conducting AMR data analysis unfortunately requires -depth knowledge different scientific fields, makes hard right. least, requires: Good questions (always start !) reliable data thorough understanding (clinical) epidemiology, understand clinical epidemiological relevance possible bias results thorough understanding (clinical) microbiology/infectious diseases, understand microorganisms causal infections implications pharmaceutical treatment, well understanding intrinsic acquired microbial resistance Experience data analysis microbiological tests results, understand determination limitations MIC values interpretations SIR values Availability biological taxonomy microorganisms probably normalisation factors pharmaceuticals, defined daily doses (DDD) Available (inter-)national guidelines, profound methods apply course, instantly provide knowledge experience. AMR package, aimed providing (1) tools simplify antimicrobial resistance data cleaning, transformation analysis, (2) methods easily incorporate international guidelines (3) scientifically reliable reference data, including requirements mentioned . AMR package enables standardised reproducible AMR data analysis, application evidence-based rules, determination first isolates, translation various codes microorganisms antimicrobial agents, determination (multi-drug) resistant microorganisms, calculation antimicrobial resistance, prevalence future trends.","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"How to conduct AMR data analysis","text":"tutorial, create fake demonstration data work . can skip Cleaning data already data ready. start analysis, try make structure data generally look like :","code":""},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"How to conduct AMR data analysis","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2 RStudio. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. also use cleaner package, can used cleaning data creating frequency tables. AMR package contains data set example_isolates_unclean, might look data users extracted laboratory systems: AMR data analysis, like microorganism column contain valid, --date taxonomy, antibiotic columns cleaned SIR values well.","code":"library(dplyr) library(ggplot2) library(AMR)  # (if not yet installed, install with:) # install.packages(c(\"dplyr\", \"ggplot2\", \"AMR\")) example_isolates_unclean #> # A tibble: 3,000 × 8 #>    patient_id hospital date       bacteria      AMX   AMC   CIP   GEN   #>    <chr>      <chr>    <date>     <chr>         <chr> <chr> <chr> <chr> #>  1 J3         A        2012-11-21 E. coli       R     I     S     S     #>  2 R7         A        2018-04-03 K. pneumoniae R     I     S     S     #>  3 P3         A        2014-09-19 E. coli       R     S     S     S     #>  4 P10        A        2015-12-10 E. coli       S     I     S     S     #>  5 B7         A        2015-03-02 E. coli       S     S     S     S     #>  6 W3         A        2018-03-31 S. aureus     R     S     R     S     #>  7 J8         A        2016-06-14 E. coli       R     S     S     S     #>  8 M3         A        2015-10-25 E. coli       R     S     S     S     #>  9 J3         A        2019-06-19 E. coli       S     S     S     S     #> 10 G6         A        2015-04-27 S. aureus     S     S     S     S     #> # ℹ 2,990 more rows  # we will use 'our_data' as the data set name for this tutorial our_data <- example_isolates_unclean"},{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"How to conduct AMR data analysis","text":".mo(), users can transform arbitrary microorganism names codes current taxonomy. AMR package contains --date taxonomic data. specific, currently included data retrieved 11 Dec 2022. codes AMR packages come .mo() short, still human readable. importantly, .mo() supports kinds input: first character codes denote taxonomic kingdom, Bacteria (B), Fungi (F), Protozoa (P). AMR package also contain functions directly retrieve taxonomic properties, name, genus, species, family, order, even Gram-stain. start mo_ use .mo() internally, still arbitrary user input can used: Now can thus clean data: Apparently, uncertainty translation taxonomic codes. Let’s check : ’s good.","code":"as.mo(\"Klebsiella pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"K. pneumoniae\") #> ClLine truncated