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(v0.8.0.9036) complete documentation rewrite
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</button>
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<span class="navbar-brand">
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<a class="navbar-link" href="../index.html">AMR (for R)</a>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9036</span>
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</span>
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</div>
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@ -237,26 +237,50 @@
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<p>Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type.</p>
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</div>
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<pre class="usage"><span class='fu'>first_isolate</span>(<span class='no'>x</span>, <span class='kw'>col_date</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>col_patient_id</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>col_testcode</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>col_specimen</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_icu</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>col_keyantibiotics</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>episode_days</span> <span class='kw'>=</span> <span class='fl'>365</span>,
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<span class='kw'>testcodes_exclude</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>icu_exclude</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
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<span class='kw'>specimen_group</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"keyantibiotics"</span>, <span class='kw'>ignore_I</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
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<span class='kw'>points_threshold</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>include_unknown</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='no'>...</span>)
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<pre class="usage"><span class='fu'>first_isolate</span>(
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<span class='no'>x</span>,
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<span class='kw'>col_date</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_patient_id</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_testcode</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_specimen</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_icu</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_keyantibiotics</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>episode_days</span> <span class='kw'>=</span> <span class='fl'>365</span>,
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<span class='kw'>testcodes_exclude</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>icu_exclude</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
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<span class='kw'>specimen_group</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"keyantibiotics"</span>,
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<span class='kw'>ignore_I</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
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<span class='kw'>points_threshold</span> <span class='kw'>=</span> <span class='fl'>2</span>,
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<span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
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<span class='kw'>include_unknown</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
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<span class='no'>...</span>
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)
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<span class='fu'>filter_first_isolate</span>(<span class='no'>x</span>, <span class='kw'>col_date</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>col_patient_id</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='no'>...</span>)
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<span class='fu'>filter_first_isolate</span>(
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<span class='no'>x</span>,
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<span class='kw'>col_date</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_patient_id</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='no'>...</span>
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)
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<span class='fu'>filter_first_weighted_isolate</span>(<span class='no'>x</span>, <span class='kw'>col_date</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_patient_id</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>col_keyantibiotics</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='no'>...</span>)</pre>
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<span class='fu'>filter_first_weighted_isolate</span>(
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<span class='no'>x</span>,
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<span class='kw'>col_date</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_patient_id</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='kw'>col_keyantibiotics</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
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<span class='no'>...</span>
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)</pre>
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<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
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<table class="ref-arguments">
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<colgroup><col class="name" /><col class="desc" /></colgroup>
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<tr>
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<th>x</th>
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<td><p>a <code>data.frame</code> containing isolates.</p></td>
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<td><p>a <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></code> containing isolates.</p></td>
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</tr>
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<tr>
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<th>col_date</th>
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@ -268,7 +292,7 @@
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</tr>
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<tr>
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<th>col_mo</th>
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<td><p>column name of the IDs of the microorganisms (see <code><a href='as.mo.html'>as.mo</a></code>), defaults to the first column of class <code>mo</code>. Values will be coerced using <code><a href='as.mo.html'>as.mo</a></code>.</p></td>
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<td><p>column name of the IDs of the microorganisms (see <code><a href='as.mo.html'>as.mo()</a></code>), defaults to the first column of class <code><a href='as.mo.html'>mo</a></code>. Values will be coerced using <code><a href='as.mo.html'>as.mo()</a></code>.</p></td>
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</tr>
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<tr>
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<th>col_testcode</th>
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</tr>
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<tr>
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<th>col_keyantibiotics</th>
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<td><p>column name of the key antibiotics to determine first <em>weighted</em> isolates, see <code><a href='key_antibiotics.html'>key_antibiotics</a></code>. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use <code>col_keyantibiotics = FALSE</code> to prevent this.</p></td>
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<td><p>column name of the key antibiotics to determine first <em>weighted</em> isolates, see <code><a href='key_antibiotics.html'>key_antibiotics()</a></code>. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' (case insensitive). Use <code>col_keyantibiotics = FALSE</code> to prevent this.</p></td>
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</tr>
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<tr>
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<th>episode_days</th>
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</tr>
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<tr>
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<th>...</th>
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<td><p>parameters passed on to the <code>first_isolate</code> function</p></td>
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<td><p>parameters passed on to the <code>first_isolate()</code> function</p></td>
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</tr>
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</table>
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<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
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<p>Methodology of this function is based on: <strong>M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition</strong>, 2014, <em>Clinical and Laboratory Standards Institute (CLSI)</em>. <a href='https://clsi.org/standards/products/microbiology/documents/m39/'>https://clsi.org/standards/products/microbiology/documents/m39/</a>.</p>
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<p>Methodology of this function is based on:</p>
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<p><strong>M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition</strong>, 2014, <em>Clinical and Laboratory Standards Institute (CLSI)</em>. <a href='https://clsi.org/standards/products/microbiology/documents/m39/'>https://clsi.org/standards/products/microbiology/documents/m39/</a>.</p>
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<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
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<p>Logical vector</p>
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<p>A <code><a href='https://rdrr.io/r/base/logical.html'>logical</a></code> vector</p>
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<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
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<p><strong>WHY THIS IS SO IMPORTANT</strong> <br />
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To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode <a href='https://www.ncbi.nlm.nih.gov/pubmed/17304462'>[1]</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>
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To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode [1](https://www.ncbi.nlm.nih.gov/pubmed/17304462). 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>
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<p>All isolates with a microbial ID of <code>NA</code> will be excluded as first isolate.</p>
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<p>The functions <code>filter_first_isolate</code> and <code>filter_first_weighted_isolate</code> are helper functions to quickly filter on first isolates. The function <code>filter_first_isolate</code> is essentially equal to:</p><pre>
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x %>%
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<p>The functions <code>filter_first_isolate()</code> and <code>filter_first_weighted_isolate()</code> are helper functions to quickly filter on first isolates. The function <code>filter_first_isolate()</code> is essentially equal to:</p><pre> x %>%
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mutate(only_firsts = first_isolate(x, ...)) %>%
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filter(only_firsts == TRUE) %>%
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select(-only_firsts)
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</pre><p>The function <code>filter_first_weighted_isolate</code> is essentially equal to:</p><pre>
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x %>%
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</pre>
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<p>The function <code>filter_first_weighted_isolate()</code> is essentially equal to:</p><pre> x %>%
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mutate(keyab = key_antibiotics(.)) %>%
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mutate(only_weighted_firsts = first_isolate(x,
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col_keyantibiotics = "keyab", ...)) %>%
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@ -357,11 +382,13 @@ To conduct an analysis of antimicrobial resistance, you should only include the
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<p>There are two ways to determine whether isolates can be included as first <em>weighted</em> isolates which will give generally the same results: <br /></p>
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<p><strong>1. Using</strong> <code>type = "keyantibiotics"</code> <strong>and parameter</strong> <code>ignore_I</code> <br />
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Any difference from S to R (or vice versa) will (re)select an isolate as a first weighted isolate. With <code>ignore_I = FALSE</code>, also differences from I to S|R (or vice versa) will lead to this. This is a reliable method and 30-35 times faster than method 2. Read more about this in the <code><a href='key_antibiotics.html'>key_antibiotics</a></code> function. <br /></p>
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<p><strong>2. Using</strong> <code>type = "points"</code> <strong>and parameter</strong> <code>points_threshold</code> <br />
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A difference from I to S|R (or vice versa) means 0.5 points, a difference from S to R (or vice versa) means 1 point. When the sum of points exceeds <code>points_threshold</code>, which default to <code>2</code>, an isolate will be (re)selected as a first weighted isolate.</p>
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<p>There are two ways to determine whether isolates can be included as first <em>weighted</em> isolates which will give generally the same results:</p><ol>
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<li><p>Using <code>type = "keyantibiotics"</code> and parameter <code>ignore_I</code></p>
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<p>Any difference from S to R (or vice versa) will (re)select an isolate as a first weighted isolate. With <code>ignore_I = FALSE</code>, also differences from I to S|R (or vice versa) will lead to this. This is a reliable method and 30-35 times faster than method 2. Read more about this in the <code><a href='key_antibiotics.html'>key_antibiotics()</a></code> function.</p></li>
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<li><p>Using <code>type = "points"</code> and parameter <code>points_threshold</code></p>
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<p>A difference from I to S|R (or vice versa) means 0.5 points, a difference from S to R (or vice versa) means 1 point. When the sum of points exceeds <code>points_threshold</code>, which default to <code>2</code>, an isolate will be (re)selected as a first weighted isolate.</p></li>
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</ol>
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<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
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@ -369,7 +396,7 @@ To conduct an analysis of antimicrobial resistance, you should only include the
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<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
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<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
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<div class='dont-index'><p><code><a href='key_antibiotics.html'>key_antibiotics</a></code></p></div>
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<div class='dont-index'><p><code><a href='key_antibiotics.html'>key_antibiotics()</a></code></p></div>
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<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
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<pre class="examples"><span class='co'># `example_isolates` is a dataset available in the AMR package.</span>
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