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(v1.4.0.9029) grey background for backticks, like readr pkg

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dr. M.S. (Matthijs) Berends
2020-12-01 16:59:57 +01:00
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docs/reference/first_isolate.html
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</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9026</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.4.0.9029</span>
</span>
</div>
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<p>All isolates with a microbial ID of <code>NA</code> will be excluded as first isolate.</p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Why this is so important</h3>
<p>To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode <a href='https:/pubmed.ncbi.nlm.nih.gov/17304462/'>(ref)</a>. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all <em>S. aureus</em> isolates would be overestimated, because you included this MRSA more than once. It would be <a href='https://en.wikipedia.org/wiki/Selection_bias'>selection bias</a>.</p>
<p>To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode <a href='https://pubmed.ncbi.nlm.nih.gov/17304462/'>(Hindler <em>et al.</em> 2007)</a>. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all <em>S. aureus</em> isolates would be overestimated, because you included this MRSA more than once. It would be <a href='https://en.wikipedia.org/wiki/Selection_bias'>selection bias</a>.</p>
<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a><code>filter_*()</code> shortcuts</h3>
<p>The functions <code>filter_first_isolate()</code> and <code>filter_first_weighted_isolate()</code> are helper functions to quickly filter on first isolates.</p>
<p>The function <code>filter_first_isolate()</code> is essentially equal to either:</p><pre> <span class='va'>x</span><span class='op'>[</span><span class='fu'>first_isolate</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>...</span><span class='op'>)</span>, <span class='op'>]</span>
<span class='va'>x</span> <span class='op'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span><span class='op'>(</span><span class='fu'>first_isolate</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>...</span><span class='op'>)</span><span class='op'>)</span>
</pre>