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<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument episode_days. This can be used to determine clinical episodes for any epidemiological analysis. The get_episode() function returns the index number of the episode per group, while the is_new_episode() function returns values TRUE/FALSE to indicate whether an item in a vector is the start of a new episode."><title>Determine (New) Episodes for Patients — get_episode • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><link href="../deps/Fira_Code-0.4.5/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Determine (New) Episodes for Patients — get_episode"><meta property="og:description" content="These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument episode_days. This can be used to determine clinical episodes for any epidemiological analysis. The get_episode() function returns the index number of the episode per group, while the is_new_episode() function returns values TRUE/FALSE to indicate whether an item in a vector is the start of a new episode."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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<img src="../logo.svg" class="logo" alt=""><h1>Determine (New) Episodes for Patients</h1>
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<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/episode.R" class="external-link"><code>R/episode.R</code></a></small>
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<div class="d-none name"><code>get_episode.Rd</code></div>
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<div class="ref-description section level2">
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<p>These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument <code>episode_days</code>. This can be used to determine clinical episodes for any epidemiological analysis. The <code>get_episode()</code> function returns the index number of the episode per group, while the <code>is_new_episode()</code> function returns values <code>TRUE</code>/<code>FALSE</code> to indicate whether an item in a vector is the start of a new episode.</p>
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<div class="section level2">
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<h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
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<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">get_episode</span><span class="op">(</span><span class="va">x</span>, <span class="va">episode_days</span>, <span class="va">...</span><span class="op">)</span></span>
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<span></span>
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<span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">x</span>, <span class="va">episode_days</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
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<div class="section level2">
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<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
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<dl><dt>x</dt>
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<dd><p>vector of dates (class <code>Date</code> or <code>POSIXt</code>), will be sorted internally to determine episodes</p></dd>
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<dt>episode_days</dt>
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<dd><p>required episode length in days, can also be less than a day or <code>Inf</code>, see <em>Details</em></p></dd>
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<dt>...</dt>
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<dd><p>ignored, only in place to allow future extensions</p></dd>
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</dl></div>
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<div class="section level2">
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<h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
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<ul><li><p><code>get_episode()</code>: a <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> vector</p></li>
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<li><p><code>is_new_episode()</code>: a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector</p></li>
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</ul></div>
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<div class="section level2">
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<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
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<p>Dates are first sorted from old to new. The oldest date will mark the start of the first episode. After this date, the next date will be marked that is at least <code>episode_days</code> days later than the start of the first episode. From that second marked date on, the next date will be marked that is at least <code>episode_days</code> days later than the start of the second episode which will be the start of the third episode, and so on. Before the vector is being returned, the original order will be restored.</p>
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<p>The <code><a href="first_isolate.html">first_isolate()</a></code> function is a wrapper around the <code>is_new_episode()</code> function, but is more efficient for data sets containing microorganism codes or names and allows for different isolate selection methods.</p>
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<p>The <code>dplyr</code> package is not required for these functions to work, but these functions do support <a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">variable grouping</a> and work conveniently inside <code>dplyr</code> verbs such as <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>.</p>
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</div>
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<div class="section level2">
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<h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
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<div class="dont-index"><p><code><a href="first_isolate.html">first_isolate()</a></code></p></div>
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</div>
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<div class="section level2">
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<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
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<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># `example_isolates` is a data set available in the AMR package.</span></span></span>
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<span class="r-in"><span><span class="co"># See ?example_isolates</span></span></span>
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<span class="r-in"><span><span class="va">df</span> <span class="op"><-</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">200</span><span class="op">)</span>, <span class="op">]</span></span></span>
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<span class="r-in"><span></span></span>
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<span class="r-in"><span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># indices</span></span></span>
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<span class="r-out co"><span class="r-pr">#></span> [1] 15 40 30 35 53 30 34 19 11 63 13 19 55 9 17 46 2 58 62 52 59 9 22 51 37</span>
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<span class="r-out co"><span class="r-pr">#></span> [26] 53 62 5 47 20 48 61 55 24 64 1 29 32 65 6 65 56 65 36 29 28 51 63 39 30</span>
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<span class="r-out co"><span class="r-pr">#></span> [51] 7 3 14 12 37 2 62 25 15 57 54 44 4 13 8 43 12 15 32 43 43 60 62 65 10</span>
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<span class="r-out co"><span class="r-pr">#></span> [76] 23 5 50 36 5 48 48 31 10 13 64 63 26 30 13 33 60 52 10 3 63 7 9 10 12</span>
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<span class="r-out co"><span class="r-pr">#></span> [101] 4 22 31 13 13 40 32 8 59 38 45 36 10 15 62 18 60 57 61 45 66 57 21 60 62</span>
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<span class="r-out co"><span class="r-pr">#></span> [126] 39 2 13 58 19 44 28 43 59 58 15 27 12 11 9 56 59 52 63 9 53 59 58 57 7</span>
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<span class="r-out co"><span class="r-pr">#></span> [151] 31 21 29 2 38 13 57 55 48 53 54 6 49 65 16 12 44 63 13 35 53 21 41 19 59</span>
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<span class="r-out co"><span class="r-pr">#></span> [176] 23 50 8 30 56 4 61 39 9 3 66 40 28 39 42 8 44 11 15 36 12 16 20 10 24</span>
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<span class="r-in"><span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</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>
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<span class="r-out co"><span class="r-pr">#></span> [1] FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE FALSE TRUE FALSE</span>
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<span class="r-out co"><span class="r-pr">#></span> [13] TRUE FALSE TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE TRUE TRUE</span>
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<span class="r-out co"><span class="r-pr">#></span> [25] FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE</span>
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<span class="r-out co"><span class="r-pr">#></span> [37] FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE TRUE</span>
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<span class="r-out co"><span class="r-pr">#></span> [49] FALSE FALSE FALSE TRUE TRUE FALSE TRUE FALSE FALSE TRUE FALSE TRUE</span>
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<span class="r-out co"><span class="r-pr">#></span> [61] TRUE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE TRUE FALSE TRUE</span>
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<span class="r-out co"><span class="r-pr">#></span> [73] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE TRUE TRUE</span>
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<span class="r-out co"><span class="r-pr">#></span> [85] FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE</span>
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<span class="r-out co"><span class="r-pr">#></span> [97] FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE</span>
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<span class="r-out co"><span class="r-pr">#></span> [109] FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE FALSE FALSE TRUE TRUE</span>
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||
<span class="r-out co"><span class="r-pr">#></span> [121] FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE TRUE</span>
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<span class="r-out co"><span class="r-pr">#></span> [133] FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE FALSE</span>
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<span class="r-out co"><span class="r-pr">#></span> [145] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE TRUE FALSE</span>
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<span class="r-out co"><span class="r-pr">#></span> [157] FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE</span>
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<span class="r-out co"><span class="r-pr">#></span> [169] FALSE TRUE FALSE TRUE TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE</span>
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<span class="r-out co"><span class="r-pr">#></span> [181] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE FALSE TRUE</span>
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<span class="r-out co"><span class="r-pr">#></span> [193] FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE</span>
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<span class="r-in"><span></span></span>
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<span class="r-in"><span><span class="co"># filter on results from the third 60-day episode only, using base R</span></span></span>
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<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>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 3 × 46</span></span>
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<span class="r-out co"><span class="r-pr">#></span> date patient age gender ward mo PEN OXA FLC AMX </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><date></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> 2002-07-16 241328 78 M Outpatie… B_STPHY_CONS R NA S R </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> 2002-08-19 A49852 70 M Clinical B_ESCHR_COLI R NA NA NA </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> 2002-07-30 218912 76 F ICU B_ESCHR_COLI R NA NA NA </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># … with 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>,</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># FEP <sir>, CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>,</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># GEN <sir>, TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>,</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># NIT <sir>, FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>,</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># TEC <sir>, TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>,</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># AZM <sir>, IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>,</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># MUP <sir>, RIF <sir></span></span>
|
||
<span class="r-in"><span></span></span>
|
||
<span class="r-in"><span><span class="co"># the functions also work for less than a day, e.g. to include one per hour:</span></span></span>
|
||
<span class="r-in"><span><span class="fu">get_episode</span><span class="op">(</span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/Sys.time.html" class="external-link">Sys.time</a></span><span class="op">(</span><span class="op">)</span>,</span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/Sys.time.html" class="external-link">Sys.time</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> <span class="fl">60</span> <span class="op">*</span> <span class="fl">60</span></span></span>
|
||
<span class="r-in"><span> <span class="op">)</span>,</span></span>
|
||
<span class="r-in"><span> episode_days <span class="op">=</span> <span class="fl">1</span> <span class="op">/</span> <span class="fl">24</span></span></span>
|
||
<span class="r-in"><span><span class="op">)</span></span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> [1] 1 2</span>
|
||
<span class="r-in"><span></span></span>
|
||
<span class="r-in"><span><span class="co"># \donttest{</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"># is_new_episode() can also be used in dplyr verbs to determine patient</span></span></span>
|
||
<span class="r-in"><span> <span class="co"># episodes based on any (combination of) grouping variables:</span></span></span>
|
||
<span class="r-in"><span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>condition <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></span>
|
||
<span class="r-in"><span> x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"A"</span>, <span class="st">"B"</span>, <span class="st">"C"</span><span class="op">)</span>,</span></span>
|
||
<span class="r-in"><span> size <span class="op">=</span> <span class="fl">200</span>,</span></span>
|
||
<span class="r-in"><span> replace <span class="op">=</span> <span class="cn">TRUE</span></span></span>
|
||
<span class="r-in"><span> <span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">condition</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>new_episode <span class="op">=</span> <span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">365</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<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="va">patient</span>, <span class="va">date</span>, <span class="va">condition</span>, <span class="va">new_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">#></span> <span style="color: #949494;"># A tibble: 200 × 4</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: condition [3]</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> patient date condition new_episode</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><date></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><lgl></span> </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 827322 2005-06-06 B FALSE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> BC9909 2011-07-08 A TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> F08866 2009-01-08 A FALSE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 48BB05 2010-03-15 C FALSE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> 419568 2014-10-19 C TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 501361 2008-12-06 C FALSE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 650870 2009-11-12 B TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 3CF3C4 2006-06-26 C TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 189363 2004-06-22 A FALSE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> D39422 2017-05-17 A FALSE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># … with 190 more rows</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="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">ward</span>, <span class="va">patient</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">transmute</a></span><span class="op">(</span><span class="va">date</span>,</span></span>
|
||
<span class="r-in"><span> <span class="va">patient</span>,</span></span>
|
||
<span class="r-in"><span> new_index <span class="op">=</span> <span class="fu">get_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span>,</span></span>
|
||
<span class="r-in"><span> new_logical <span class="op">=</span> <span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span></span></span>
|
||
<span class="r-in"><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">#></span> <span style="color: #949494;"># A tibble: 200 × 5</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: ward, patient [185]</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> ward date patient new_index new_logical</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><date></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><lgl></span> </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> Clinical 2005-06-06 827322 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> Clinical 2011-07-08 BC9909 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> Clinical 2009-01-08 F08866 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> Clinical 2010-03-15 48BB05 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> Clinical 2014-10-19 419568 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> Clinical 2008-12-06 501361 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> Outpatient 2009-11-12 650870 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> Clinical 2006-06-26 3CF3C4 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> Clinical 2004-06-22 189363 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> Clinical 2017-05-17 D39422 1 TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># … with 190 more rows</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="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">ward</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span></span></span>
|
||
<span class="r-in"><span> n_patients <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct</a></span><span class="op">(</span><span class="va">patient</span><span class="op">)</span>,</span></span>
|
||
<span class="r-in"><span> n_episodes_365 <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">365</span><span class="op">)</span><span class="op">)</span>,</span></span>
|
||
<span class="r-in"><span> n_episodes_60 <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">is_new_episode</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="op">)</span>,</span></span>
|
||
<span class="r-in"><span> n_episodes_30 <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">30</span><span class="op">)</span><span class="op">)</span></span></span>
|
||
<span class="r-in"><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">#></span> <span style="color: #949494;"># A tibble: 3 × 5</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> ward n_patients n_episodes_365 n_episodes_60 n_episodes_30</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><int></span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Clinical 116 15 55 74</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> ICU 58 11 34 44</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> Outpatient 11 7 11 11</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"># 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>
|
||
<span class="r-in"><span> <span class="va">x</span> <span class="op"><-</span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="first_isolate.html">filter_first_isolate</a></span><span class="op">(</span></span></span>
|
||
<span class="r-in"><span> include_unknown <span class="op">=</span> <span class="cn">TRUE</span>,</span></span>
|
||
<span class="r-in"><span> method <span class="op">=</span> <span class="st">"episode-based"</span></span></span>
|
||
<span class="r-in"><span> <span class="op">)</span></span></span>
|
||
<span class="r-in"><span></span></span>
|
||
<span class="r-in"><span> <span class="va">y</span> <span class="op"><-</span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">mo</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">365</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">ungroup</a></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"><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-msg co"><span class="r-pr">#></span> Including isolates from ICU.</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> [1] TRUE</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"># 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>
|
||
<span class="r-in"><span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">mo</span>, <span class="va">ward</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>flag_episode <span class="op">=</span> <span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">365</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
|
||
<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">#></span> <span style="color: #949494;"># A tibble: 200 × 4</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: patient, mo, ward [190]</span></span>
|
||
<span class="r-out co"><span class="r-pr">#></span> patient mo ward flag_episode</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><lgl></span> </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 827322 B_KLBSL_OXYT Clinical TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> BC9909 B_ESCHR_COLI Clinical TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> F08866 B_ESCHR_COLI Clinical TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 48BB05 B_STPHY_CONS Clinical TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> 419568 B_STRPT_PNMN Clinical TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 501361 B_STNTR_MLTP Clinical TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 650870 B_ESCHR_COLI Outpatient TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 3CF3C4 B_STPHY_CONS Clinical TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 189363 B_STPHY_AURS Clinical TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> D39422 B_KLBSL_PNMN Clinical TRUE </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># … with 190 more rows</span></span>
|
||
<span class="r-in"><span><span class="co"># }</span></span></span>
|
||
</code></pre></div>
|
||
</div>
|
||
</main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
|
||
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|
||
|
||
|
||
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|
||
<p></p><p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU General Public License version 2.0 (GPL-2)</a>.<br>Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands.</p>
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|
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|
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|
||
<p></p><p><a target="_blank" href="https://www.rug.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/logos/logo_rug.svg" style="max-width: 150px;"></a><a target="_blank" href="https://www.umcg.nl" class="external-link"><img src="https://github.com/msberends/AMR/raw/main/pkgdown/logos/logo_umcg.svg" style="max-width: 150px;"></a></p>
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