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@@ -37,7 +37,7 @@
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<a class="navbar-brand me-2" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
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<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
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website update since they are based on randomly created values and the
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page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
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Markdown</a>. However, the methodology remains unchanged. This page was
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generated on 10 June 2024.</p>
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generated on 12 June 2024.</p>
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<div class="section level2">
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<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
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</h2>
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@@ -261,21 +261,21 @@ make the structure of your data generally look like this:</p>
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</tr></thead>
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<tbody>
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<tr class="odd">
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<td align="center">2024-06-10</td>
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<td align="center">2024-06-12</td>
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<td align="center">abcd</td>
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<td align="center">Escherichia coli</td>
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<td align="center">S</td>
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<td align="center">S</td>
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</tr>
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<tr class="even">
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<td align="center">2024-06-10</td>
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<td align="center">2024-06-12</td>
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<td align="center">abcd</td>
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<td align="center">Escherichia coli</td>
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<td align="center">S</td>
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<td align="center">R</td>
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</tr>
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<tr class="odd">
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<td align="center">2024-06-10</td>
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<td align="center">2024-06-12</td>
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<td align="center">efgh</td>
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<td align="center">Escherichia coli</td>
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<td align="center">R</td>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9045</small>
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<main id="main" class="col-md-9"><div class="page-header">
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<img src="../logo.svg" class="logo" alt=""><h1>Data sets for download / own use</h1>
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<h4 data-toc-skip class="date">10 June 2024</h4>
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<h4 data-toc-skip class="date">12 June 2024</h4>
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<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>
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<div class="d-none name"><code>datasets.Rmd</code></div>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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box-shadow: none !important;
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}
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.endorse_img {
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width: 0% !important;
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}
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
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<a class="anchor" aria-label="anchor" href="#the-amr-package-for-r-"></a>
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</h1>
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</div>
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<p><img src="./endorsement_clsi_eucast.jpg" class="endorse_img" align="right" height="120"></p>
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<ul>
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<li>Provides an <strong>all-in-one solution</strong> for AMR data analysis in a One Health approach</li>
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<li>Generates <strong>antibiograms</strong> - traditional, combined, syndromic, and even WISCA</li>
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<small><a href="https://doi.org/10.18637/jss.v104.i03" target="_blank" class="external-link">https://doi.org/10.18637/jss.v104.i03</a></small>
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</p>
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</div>
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<p><a href="./reference/clinical_breakpoints.html#response-from-clsi-and-eucast"><img src="./endorsement_clsi_eucast.jpg" class="endorse_img" align="right" height="120"></a></p>
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<hr>
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<div class="section level3">
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<h3 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9045</small>
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</div>
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<div class="section level2">
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<h2 class="pkg-version" data-toc-text="2.1.1.9044" id="amr-2119044">AMR 2.1.1.9044<a class="anchor" aria-label="anchor" href="#amr-2119044"></a></h2>
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<h2 class="pkg-version" data-toc-text="2.1.1.9045" id="amr-2119045">AMR 2.1.1.9045<a class="anchor" aria-label="anchor" href="#amr-2119045"></a></h2>
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<p><em>(this beta version will eventually become v3.0. We’re happy to reach a new major milestone soon, which will be all about the new One Health support!)</em></p>
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<div class="section level5">
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<h5 id="a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9044">A New Milestone: One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9044"></a></h5>
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<h5 id="a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9045">A New Milestone: One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9045"></a></h5>
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<p>This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the <a href="https://www.upei.ca/avc" class="external-link">University of Prince Edward Island</a>, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.</p>
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</div>
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<div class="section level3">
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<h3 id="breaking-2-1-1-9044">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9044"></a></h3>
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<h3 id="breaking-2-1-1-9045">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9045"></a></h3>
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<ul><li>Removed all functions and references that used the deprecated <code>rsi</code> class, which were all replaced with their <code>sir</code> equivalents over a year ago</li>
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</ul></div>
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<div class="section level3">
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<h3 id="new-2-1-1-9044">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9044"></a></h3>
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<h3 id="new-2-1-1-9045">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9045"></a></h3>
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<ul><li>One Health implementation
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<ul><li>Function <code><a href="../reference/as.sir.html">as.sir()</a></code> now has extensive support for animal breakpoints from CLSI. Use <code>breakpoint_type = "animal"</code> and set the <code>host</code> argument to a variable that contains animal species names.</li>
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<li>The <code>clinical_breakpoints</code> data set contains all these breakpoints, and can be downloaded on our <a href="https://msberends.github.io/AMR/articles/datasets.html">download page</a>.</li>
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<li>Function <code><a href="../reference/mo_property.html">mo_group_members()</a></code> to retrieve the member microorganisms of a microorganism group. For example, <code>mo_group_members("Strep group C")</code> returns a vector of all microorganisms that are in that group.</li>
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</ul></div>
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<div class="section level3">
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<h3 id="changed-2-1-1-9044">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9044"></a></h3>
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<h3 id="changed-2-1-1-9045">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9045"></a></h3>
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<ul><li>For SIR interpretation, it is now possible to use column names for argument <code>ab</code>, <code>mo</code>, and <code>uti</code>: <code>as.sir(..., ab = "column1", mo = "column2", uti = "column3")</code>. This greatly improves the flexibility for users.</li>
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<li>Extended the antibiotic selectors with <code><a href="../reference/antibiotic_class_selectors.html">nitrofurans()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">rifamycins()</a></code>
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</li>
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<li>Intermediate log2 levels used for MIC plotting are now more common values instead of following a strict dilution range</li>
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</ul></div>
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<div class="section level3">
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<h3 id="other-2-1-1-9044">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9044"></a></h3>
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<h3 id="other-2-1-1-9045">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9045"></a></h3>
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<ul><li>Added Jordan Stull, Matthew Saab, and Javier Sanchez as contributors, to thank them for their valuable input</li>
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</ul></div>
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</div>
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resistance_predict: resistance_predict.html
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welcome_to_AMR: welcome_to_AMR.html
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WHONET: WHONET.html
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last_built: 2024-06-10T13:13Z
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last_built: 2024-06-12T08:38Z
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urls:
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reference: https://msberends.github.io/AMR/reference
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article: https://msberends.github.io/AMR/articles
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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|
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|
||||
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@@ -10,7 +10,7 @@
|
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||||
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||||
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|
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+11
-11
@@ -10,7 +10,7 @@
|
||||
|
||||
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
|
||||
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||||
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|
||||
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||||
@@ -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">#></span> birth_date age age_exact age_at_y2k</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 1965-12-05 58 58.51366 34</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 1980-03-01 44 44.27596 19</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 1949-11-01 74 74.60656 50</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 1947-02-14 77 77.31967 52</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 1940-02-19 84 84.30601 59</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 1988-01-10 36 36.41530 11</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 1997-08-27 26 26.78689 2</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 1978-01-26 46 46.37158 21</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 1972-06-17 51 51.98087 27</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 1986-08-10 37 37.83333 13</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 1965-12-05 58 58.51913 34</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 1980-03-01 44 44.28142 19</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 1949-11-01 74 74.61202 50</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 1947-02-14 77 77.32514 52</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 1940-02-19 84 84.31148 59</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 1988-01-10 36 36.42077 11</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 1997-08-27 26 26.79235 2</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 1978-01-26 46 46.37705 21</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 1972-06-17 51 51.98634 27</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 1986-08-10 37 37.83880 13</span>
|
||||
</code></pre></div>
|
||||
</div>
|
||||
</main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
|
||||
|
||||
@@ -10,7 +10,7 @@
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||||
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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||||
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||||
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
|
||||
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9045</small>
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
|
||||
@@ -12,7 +12,7 @@ In short, if you have a column name that resembles an antimicrobial drug, it wil
|
||||
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||||
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||||
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||||
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||||
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||||
@@ -10,7 +10,7 @@
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
|
||||
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||||
|
||||
@@ -10,7 +10,7 @@
|
||||
|
||||
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||||
|
||||
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|
||||
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||||
|
||||
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||||
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||||
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|
||||
|
||||
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||||
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|
||||
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|
||||
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||||
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||||
@@ -10,7 +10,7 @@
|
||||
|
||||
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|
||||
|
||||
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|
||||
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|
||||
|
||||
|
||||
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|
||||
@@ -307,7 +307,7 @@
|
||||
<span class="r-msg co"><span class="r-pr">#></span> all the details of the breakpoint interpretations. Note that some</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> microorganisms might not have breakpoints for each antimicrobial drug in</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> EUCAST 2023.</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> Interpreting MIC values: for AMX, EUCAST 2023...</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> Interpreting MIC values: 'AMX' (amoxicillin), EUCAST 2023...</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> NOTE </span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> • Multiple breakpoints available for amoxicillin (AMX) in Streptococcus</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> pneumoniae - assuming body site 'Meningitis'.</span>
|
||||
|
||||
@@ -10,7 +10,7 @@
|
||||
|
||||
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|
||||
|
||||
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|
||||
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|
||||
|
||||
|
||||
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
|
||||
|
||||
+16
-16
@@ -24,7 +24,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
|
||||
|
||||
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|
||||
|
||||
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9044</small>
|
||||
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|
||||
|
||||
|
||||
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|
||||
@@ -603,19 +603,19 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 13 × 14</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> datetime index ab_user mo_user ab mo input</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><dttm></span> <span style="color: #949494; font-style: italic;"><int></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;"><ab></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><dbl></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 2024-06-10 <span style="color: #949494;">13:14:36</span> 1 TOB Escherich… TOB B_[ORD]_ENTRBCTR 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> 2024-06-10 <span style="color: #949494;">13:14:36</span> 1 GEN Escherich… GEN B_[ORD]_ENTRBCTR 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> 2024-06-10 <span style="color: #949494;">13:14:36</span> 1 CIP Escherich… CIP B_[ORD]_ENTRBCTR 0.256</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 2024-06-10 <span style="color: #949494;">13:14:36</span> 1 AMP Escherich… AMP B_[ORD]_ENTRBCTR 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> 2024-06-10 <span style="color: #949494;">13:14:32</span> 1 AMX B_STRPT_P… AMX B_STRPT_PNMN 0.01 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 2024-06-10 <span style="color: #949494;">13:14:32</span> 2 AMX B_STRPT_P… AMX B_STRPT_PNMN 2 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 2024-06-10 <span style="color: #949494;">13:14:32</span> 3 AMX B_STRPT_P… AMX B_STRPT_PNMN 4 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 2024-06-10 <span style="color: #949494;">13:14:32</span> 4 AMX B_STRPT_P… AMX B_STRPT_PNMN 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 2024-06-10 <span style="color: #949494;">13:14:31</span> 1 AMX B_STRPT_P… AMX B_STRPT_PNMN 2 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 2024-06-10 <span style="color: #949494;">13:14:31</span> 1 TOB Escherich… TOB B_[ORD]_ENTRBCTR 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">11</span> 2024-06-10 <span style="color: #949494;">13:14:31</span> 1 GEN Escherich… GEN B_[ORD]_ENTRBCTR 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">12</span> 2024-06-10 <span style="color: #949494;">13:14:31</span> 1 AMP Escherich… AMP B_[ORD]_ENTRBCTR 20 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">13</span> 2024-06-10 <span style="color: #949494;">13:14:31</span> 1 ampicillin Strep pneu AMP B_STRPT_PNMN 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 2024-06-12 <span style="color: #949494;">08:38:59</span> 1 TOB Escherich… TOB B_[ORD]_ENTRBCTR 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> 2024-06-12 <span style="color: #949494;">08:38:59</span> 1 GEN Escherich… GEN B_[ORD]_ENTRBCTR 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> 2024-06-12 <span style="color: #949494;">08:38:59</span> 1 CIP Escherich… CIP B_[ORD]_ENTRBCTR 0.256</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 2024-06-12 <span style="color: #949494;">08:38:59</span> 1 AMP Escherich… AMP B_[ORD]_ENTRBCTR 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> 2024-06-12 <span style="color: #949494;">08:38:55</span> 1 AMX B_STRPT_P… AMX B_STRPT_PNMN 0.01 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 2024-06-12 <span style="color: #949494;">08:38:55</span> 2 AMX B_STRPT_P… AMX B_STRPT_PNMN 2 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 2024-06-12 <span style="color: #949494;">08:38:55</span> 3 AMX B_STRPT_P… AMX B_STRPT_PNMN 4 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 2024-06-12 <span style="color: #949494;">08:38:55</span> 4 AMX B_STRPT_P… AMX B_STRPT_PNMN 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 2024-06-12 <span style="color: #949494;">08:38:54</span> 1 AMX B_STRPT_P… AMX B_STRPT_PNMN 2 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 2024-06-12 <span style="color: #949494;">08:38:54</span> 1 TOB Escherich… TOB B_[ORD]_ENTRBCTR 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">11</span> 2024-06-12 <span style="color: #949494;">08:38:54</span> 1 GEN Escherich… GEN B_[ORD]_ENTRBCTR 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">12</span> 2024-06-12 <span style="color: #949494;">08:38:54</span> 1 AMP Escherich… AMP B_[ORD]_ENTRBCTR 20 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">13</span> 2024-06-12 <span style="color: #949494;">08:38:54</span> 1 ampicillin Strep pneu AMP B_STRPT_PNMN 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 7 more variables: outcome <sir>, method <chr>, breakpoint_S_R <chr>,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># guideline <chr>, host <chr>, ref_table <chr>, uti <lgl></span></span>
|
||||
<span class="r-in"><span></span></span>
|
||||
@@ -782,7 +782,7 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
|
||||
<span class="r-msg co"><span class="r-pr">#></span> all the details of the breakpoint interpretations. Note that some</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> microorganisms might not have breakpoints for each antimicrobial drug in</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> EUCAST 2023.</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> Interpreting MIC values: column for NIT, EUCAST 2023...</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> Interpreting MIC values: column 'NIT' (nitrofurantoin), EUCAST 2023...</span>
|
||||
<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>in as.sir(): interpretation of nitrofurantoin (NIT) is only available for</span>
|
||||
<span class="r-wrn co"><span class="r-pr">#></span> (uncomplicated) urinary tract infections (UTI) for some microorganisms,</span>
|
||||
<span class="r-wrn co"><span class="r-pr">#></span> thus assuming uti = TRUE. See ?as.sir.</span>
|
||||
@@ -794,7 +794,7 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
|
||||
<span class="r-msg co"><span class="r-pr">#></span> all the details of the breakpoint interpretations. Note that some</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> microorganisms might not have breakpoints for each antimicrobial drug in</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> EUCAST 2023.</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> Interpreting MIC values: column for NIT, EUCAST 2023...</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> Interpreting MIC values: column 'NIT' (nitrofurantoin), EUCAST 2023...</span>
|
||||
<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>in as.sir(): interpretation of nitrofurantoin (NIT) is only available for</span>
|
||||
<span class="r-wrn co"><span class="r-pr">#></span> (uncomplicated) urinary tract infections (UTI) for some microorganisms,</span>
|
||||
<span class="r-wrn co"><span class="r-pr">#></span> thus assuming uti = TRUE. See ?as.sir.</span>
|
||||
|
||||
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@@ -16,7 +16,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
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[{"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\") #> ClaLine truncated
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[{"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\") #> ClaLine truncated
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Reference in new issue
Block a user