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@ -9,7 +9,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
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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="">2.1.1.9183</small>
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9186</small>
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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">
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@ -60,10 +60,10 @@ Adhering to previously described approaches (see Source) and especially the Baye
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<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">antibiogram</span><span class="op">(</span><span class="va">x</span>, antibiotics <span class="op">=</span> <span class="fu"><a href="https://tidyselect.r-lib.org/reference/where.html" class="external-link">where</a></span><span class="op">(</span><span class="va">is.sir</span><span class="op">)</span>, mo_transform <span class="op">=</span> <span class="st">"shortname"</span>,</span>
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<span> ab_transform <span class="op">=</span> <span class="st">"name"</span>, syndromic_group <span class="op">=</span> <span class="cn">NULL</span>, add_total_n <span class="op">=</span> <span class="cn">FALSE</span>,</span>
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<span> only_all_tested <span class="op">=</span> <span class="cn">FALSE</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">wisca</span>, <span class="fl">1</span>, <span class="fl">0</span><span class="op">)</span>,</span>
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<span> formatting_type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"AMR_antibiogram_formatting_type"</span>, <span class="fl">14</span><span class="op">)</span>,</span>
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<span> col_mo <span class="op">=</span> <span class="cn">NULL</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>, minimum <span class="op">=</span> <span class="fl">30</span>,</span>
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<span> combine_SI <span class="op">=</span> <span class="cn">TRUE</span>, sep <span class="op">=</span> <span class="st">" + "</span>, wisca <span class="op">=</span> <span class="cn">FALSE</span>, simulations <span class="op">=</span> <span class="fl">1000</span>,</span>
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<span> conf_interval <span class="op">=</span> <span class="fl">0.95</span>, interval_side <span class="op">=</span> <span class="st">"two-tailed"</span>,</span>
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<span> formatting_type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"AMR_antibiogram_formatting_type"</span>,</span>
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<span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="va">wisca</span>, <span class="fl">14</span>, <span class="fl">18</span><span class="op">)</span><span class="op">)</span>, col_mo <span class="op">=</span> <span class="cn">NULL</span>, language <span class="op">=</span> <span class="fu"><a href="translate.html">get_AMR_locale</a></span><span class="op">(</span><span class="op">)</span>,</span>
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<span> minimum <span class="op">=</span> <span class="fl">30</span>, combine_SI <span class="op">=</span> <span class="cn">TRUE</span>, sep <span class="op">=</span> <span class="st">" + "</span>, wisca <span class="op">=</span> <span class="cn">FALSE</span>,</span>
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<span> simulations <span class="op">=</span> <span class="fl">1000</span>, conf_interval <span class="op">=</span> <span class="fl">0.95</span>, interval_side <span class="op">=</span> <span class="st">"two-tailed"</span>,</span>
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<span> info <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/interactive.html" class="external-link">interactive</a></span><span class="op">(</span><span class="op">)</span><span class="op">)</span></span>
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<span></span>
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<span><span class="fu">wisca</span><span class="op">(</span><span class="va">x</span>, antibiotics <span class="op">=</span> <span class="fu"><a href="https://tidyselect.r-lib.org/reference/where.html" class="external-link">where</a></span><span class="op">(</span><span class="va">is.sir</span><span class="op">)</span>, ab_transform <span class="op">=</span> <span class="st">"name"</span>,</span>
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@ -114,7 +114,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
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<dt id="arg-ab-transform">ab_transform<a class="anchor" aria-label="anchor" href="#arg-ab-transform"></a></dt>
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<dd><p>a character to transform antimicrobial input - must be one of the column names of the <a href="antibiotics.html">antibiotics</a> data set (defaults to <code>"name"</code>): "ab", "cid", "name", "group", "atc", "atc_group1", "atc_group2", "abbreviations", "synonyms", "oral_ddd", "oral_units", "iv_ddd", "iv_units", or "loinc". Can also be <code>NULL</code> to not transform the input.</p></dd>
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<dd><p>a character to transform antimicrobial input - must be one of the column names of the <a href="antimicrobials.html">antimicrobials</a> data set (defaults to <code>"name"</code>): "ab", "cid", "name", "group", "atc", "atc_group1", "atc_group2", "abbreviations", "synonyms", "oral_ddd", "oral_units", "iv_ddd", "iv_units", or "loinc". Can also be <code>NULL</code> to not transform the input.</p></dd>
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<dt id="arg-syndromic-group">syndromic_group<a class="anchor" aria-label="anchor" href="#arg-syndromic-group"></a></dt>
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@ -206,7 +206,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
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<h3 id="formatting-type">Formatting Type<a class="anchor" aria-label="anchor" href="#formatting-type"></a></h3>
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<p>The formatting of the 'cells' of the table can be set with the argument <code>formatting_type</code>. In these examples, <code>5</code> is the antimicrobial coverage (<code>4-6</code> indicates the confidence level), <code>15</code> the number of susceptible isolates, and <code>300</code> the number of tested (i.e., available) isolates:</p><ol><li><p>5</p></li>
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<p>The formatting of the 'cells' of the table can be set with the argument <code>formatting_type</code>. In these examples, <code>5</code> indicates the antimicrobial coverage (<code>4-6</code> the confidence level), <code>15</code> the number of susceptible isolates, and <code>300</code> the number of tested (i.e., available) isolates:</p><ol><li><p>5</p></li>
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<li><p>15</p></li>
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<li><p>300</p></li>
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<li><p>15/300</p></li>
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@ -219,16 +219,16 @@ Adhering to previously described approaches (see Source) and especially the Baye
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<li><p>5 (N=15/300)</p></li>
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<li><p>5% (N=15/300)</p></li>
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<li><p>5 (4-6)</p></li>
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<li><p>5% (4-6%) - <strong>default</strong></p></li>
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<li><p>5% (4-6%) - <strong>default for WISCA</strong></p></li>
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<li><p>5 (4-6,300)</p></li>
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<li><p>5% (4-6%,300)</p></li>
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<li><p>5 (4-6,N=300)</p></li>
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<li><p>5% (4-6%,N=300)</p></li>
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<li><p>5% (4-6%,N=300) - <strong>default for non-WISCA</strong></p></li>
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<li><p>5 (4-6,15/300)</p></li>
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<li><p>5% (4-6%,15/300)</p></li>
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<li><p>5 (4-6,N=15/300)</p></li>
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<li><p>5% (4-6%,N=15/300)</p></li>
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</ol><p>The default is <code>14</code>, which can be set globally with the package option <code><a href="AMR-options.html">AMR_antibiogram_formatting_type</a></code>, e.g. <code>options(AMR_antibiogram_formatting_type = 5)</code>. Do note that for WISCA, the total numbers of tested and susceptible isolates are less useful to report, since these are included in the Bayesian model and apparent from the susceptibility and its confidence level.</p>
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</ol><p>The default can be set globally with the package option <code><a href="AMR-options.html">AMR_antibiogram_formatting_type</a></code>, e.g. <code>options(AMR_antibiogram_formatting_type = 5)</code>. Do note that for WISCA, the total numbers of tested and susceptible isolates are less useful to report, since these are included in the Bayesian model and apparent from the susceptibility and its confidence level.</p>
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<p>Set <code>digits</code> (defaults to <code>0</code>) to alter the rounding of the susceptibility percentages.</p>
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</div>
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@ -414,16 +414,16 @@ $$p_i = \frac{x_i}{\sum_{j=1}^K x_j}$$</p>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># An Antibiogram (non-WISCA / 95% CI): 10 × 7</span></span>
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<span class="r-out co"><span class="r-pr">#></span> Pathogen Amikacin Gentamicin Imipenem Kanamycin Meropenem Tobramycin</span>
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<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;"><chr></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;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> </span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> CoNS 0% (0-8%) 86% (82-9… 52% (37… 0% (0-8%) 52% (37-… 22% (12-3…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> CoNS 0% (0-8%,N… 86% (82-9… 52% (37… 0% (0-8%… 52% (37-… 22% (12-3…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> E. coli 100% (98-1… 98% (96-9… 100% (9… <span style="color: #BB0000;">NA</span> 100% (99… 97% (96-9…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> E. faecalis 0% (0-9%) 0% (0-9%) 100% (9… 0% (0-9%) <span style="color: #BB0000;">NA</span> 0% (0-9%) </span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> E. faecalis 0% (0-9%,N… 0% (0-9%,… 100% (9… 0% (0-9%… <span style="color: #BB0000;">NA</span> 0% (0-9%,…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> K. pneumoniae <span style="color: #BB0000;">NA</span> 90% (79-9… 100% (9… <span style="color: #BB0000;">NA</span> 100% (93… 90% (79-9…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> P. aeruginosa <span style="color: #BB0000;">NA</span> 100% (88-… <span style="color: #BB0000;">NA</span> 0% (0-12… <span style="color: #BB0000;">NA</span> 100% (88-…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> P. mirabilis <span style="color: #BB0000;">NA</span> 94% (80-9… 94% (79… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> 94% (80-9…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> S. aureus <span style="color: #BB0000;">NA</span> 99% (97-1… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> 98% (92-1…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> S. epidermidis 0% (0-8%) 79% (71-8… <span style="color: #BB0000;">NA</span> 0% (0-8%) <span style="color: #BB0000;">NA</span> 51% (40-6…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> S. epidermidis 0% (0-8%,N… 79% (71-8… <span style="color: #BB0000;">NA</span> 0% (0-8%… <span style="color: #BB0000;">NA</span> 51% (40-6…</span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> S. hominis <span style="color: #BB0000;">NA</span> 92% (84-9… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> 85% (74-9…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> S. pneumoniae 0% (0-3%) 0% (0-3%) <span style="color: #BB0000;">NA</span> 0% (0-3%) <span style="color: #BB0000;">NA</span> 0% (0-3%) </span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> S. pneumoniae 0% (0-3%,N… 0% (0-3%,… <span style="color: #BB0000;">NA</span> 0% (0-3%… <span style="color: #BB0000;">NA</span> 0% (0-3%,…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span></span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
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<span class="r-in"><span></span></span>
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@ -435,10 +435,10 @@ $$p_i = \frac{x_i}{\sum_{j=1}^K x_j}$$</p>
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<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;">ℹ For </span><span style="color: #0000BB; background-color: #EEEEEE;">aminoglycosides()</span><span style="color: #0000BB;"> using columns '</span><span style="color: #0000BB; font-weight: bold;">GEN</span><span style="color: #0000BB;">' (gentamicin), '</span><span style="color: #0000BB; font-weight: bold;">TOB</span><span style="color: #0000BB;">'</span></span>
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<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;"> (tobramycin), '</span><span style="color: #0000BB; font-weight: bold;">AMK</span><span style="color: #0000BB;">' (amikacin), and '</span><span style="color: #0000BB; font-weight: bold;">KAN</span><span style="color: #0000BB;">' (kanamycin)</span></span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># An Antibiogram (non-WISCA / 95% CI): 2 × 5</span></span>
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<span class="r-out co"><span class="r-pr">#></span> Pathogen J01GB01 J01GB03 J01GB04 J01GB06 </span>
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<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;"><chr></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;"><chr></span> </span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Gram-negative 96% (94-97%) 96% (95-98%) 0% (0-10%) 98% (96-99%)</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> Gram-positive 34% (31-38%) 63% (60-66%) 0% (0-1%) 0% (0-1%) </span>
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<span class="r-out co"><span class="r-pr">#></span> Pathogen J01GB01 J01GB03 J01GB04 J01GB06 </span>
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<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;"><chr></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;"><chr></span> </span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Gram-negative 96% (94-97%,N=686) 96% (95-98%,N=684) 0% (0-10%,N=35) 98% (96-…</span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> Gram-positive 34% (31-38%,N=665) 63% (60-66%,N=1170) 0% (0-1%,N=436) 0% (0-1%…</span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
|
||||
<span class="r-in"><span></span></span>
|
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@ -449,13 +449,13 @@ $$p_i = \frac{x_i}{\sum_{j=1}^K x_j}$$</p>
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<span class="r-in"><span><span class="op">)</span></span></span>
|
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<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;">ℹ For </span><span style="color: #0000BB; background-color: #EEEEEE;">carbapenems()</span><span style="color: #0000BB;"> using columns '</span><span style="color: #0000BB; font-weight: bold;">IPM</span><span style="color: #0000BB;">' (imipenem) and '</span><span style="color: #0000BB; font-weight: bold;">MEM</span><span style="color: #0000BB;">' (meropenem)</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># An Antibiogram (non-WISCA / 95% CI): 5 × 3</span></span>
|
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<span class="r-out co"><span class="r-pr">#></span> Pathogen Imipenem Meropenem </span>
|
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<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;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> </span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Coagulase-negative Staphylococcus (CoNS) 52% (37-67%) 52% (37-67%) </span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> Enterococcus faecalis 100% (91-100%) <span style="color: #BB0000;">NA</span> </span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> Escherichia coli 100% (99-100%) 100% (99-100%)</span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae 100% (93-100%) 100% (93-100%)</span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">5</span> Proteus mirabilis 94% (79-99%) <span style="color: #BB0000;">NA</span> </span>
|
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<span class="r-out co"><span class="r-pr">#></span> Pathogen Imipenem Meropenem </span>
|
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<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;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> </span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Coagulase-negative Staphylococcus (CoNS) 52% (37-67%,N=48) 52% (37-67%,N=4…</span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> Enterococcus faecalis 100% (91-100%,N=38) <span style="color: #BB0000;">NA</span> </span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> Escherichia coli 100% (99-100%,N=422) 100% (99-100%,N…</span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">4</span> Klebsiella pneumoniae 100% (93-100%,N=51) 100% (93-100%,N…</span>
|
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">5</span> Proteus mirabilis 94% (79-99%,N=32) <span style="color: #BB0000;">NA</span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
|
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<span class="r-in"><span></span></span>
|
||||
@ -470,8 +470,8 @@ $$p_i = \frac{x_i}{\sum_{j=1}^K x_j}$$</p>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># An Antibiogram (non-WISCA / 95% CI): 2 × 4</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Pathogen Piperacillin/tazobac…¹ Piperacillin/tazobac…² Piperacillin/tazobac…³</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;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Gram-neg… 88% (85-91%) 99% (97-99%) 98% (97-99%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> Gram-pos… 86% (82-89%) 98% (96-98%) 95% (93-97%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Gram-neg… 88% (85-91%,N=641) 99% (97-99%,N=691) 98% (97-99%,N=693) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> Gram-pos… 86% (82-89%,N=345) 98% (96-98%,N=1044) 95% (93-97%,N=550) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ abbreviated names: ¹`Piperacillin/tazobactam`,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ²`Piperacillin/tazobactam + Gentamicin`,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ³`Piperacillin/tazobactam + Tobramycin`</span></span>
|
||||
@ -486,10 +486,10 @@ $$p_i = \frac{x_i}{\sum_{j=1}^K x_j}$$</p>
|
||||
<span class="r-in"><span> sep <span class="op">=</span> <span class="st">" & "</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;"># An Antibiogram (non-WISCA / 95% CI): 2 × 3</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Pathogen Ciprofloxacin `Ciprofloxacin & Gentamicin`</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;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Gram-negative 91% (88-93%) 99% (97-99%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> Gram-positive 77% (74-80%) 93% (91-94%) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> Pathogen Ciprofloxacin `Ciprofloxacin & Gentamicin`</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;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Gram-negative 91% (88-93%,N=684) 99% (97-99%,N=694) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> Gram-positive 77% (74-80%,N=724) 93% (91-94%,N=847) </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
|
||||
<span class="r-in"><span></span></span>
|
||||
@ -519,8 +519,8 @@ $$p_i = \frac{x_i}{\sum_{j=1}^K x_j}$$</p>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> Clinical S. epider… <span style="color: #BB0000;">NA</span> 82% (72-9… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">11</span> ICU S. epider… <span style="color: #BB0000;">NA</span> 72% (60-8… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">12</span> Clinical S. hominis <span style="color: #BB0000;">NA</span> 96% (85-9… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">13</span> Clinical S. pneumo… 0% (0-5… 0% (0-5%) <span style="color: #BB0000;">NA</span> 0% (0-5%) <span style="color: #BB0000;">NA</span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">14</span> ICU S. pneumo… 0% (0-1… 0% (0-12%) <span style="color: #BB0000;">NA</span> 0% (0-12… <span style="color: #BB0000;">NA</span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">13</span> Clinical S. pneumo… 0% (0-5… 0% (0-5%,… <span style="color: #BB0000;">NA</span> 0% (0-5%… <span style="color: #BB0000;">NA</span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">14</span> ICU S. pneumo… 0% (0-1… 0% (0-12%… <span style="color: #BB0000;">NA</span> 0% (0-12… <span style="color: #BB0000;">NA</span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 1 more variable: Tobramycin <chr></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
|
||||
@ -542,10 +542,10 @@ $$p_i = \frac{x_i}{\sum_{j=1}^K x_j}$$</p>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;">ℹ For </span><span style="color: #0000BB; background-color: #EEEEEE;">aminoglycosides()</span><span style="color: #0000BB;"> using columns '</span><span style="color: #0000BB; font-weight: bold;">GEN</span><span style="color: #0000BB;">' (gentamicin), '</span><span style="color: #0000BB; font-weight: bold;">TOB</span><span style="color: #0000BB;">'</span></span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #0000BB;"> (tobramycin), '</span><span style="color: #0000BB; font-weight: bold;">AMK</span><span style="color: #0000BB;">' (amikacin), and '</span><span style="color: #0000BB; font-weight: bold;">KAN</span><span style="color: #0000BB;">' (kanamycin)</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># An Antibiogram (non-WISCA / 95% CI): 2 × 5</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> `Grupo sindrómico` Patógeno Amikacina Gentamicina Tobramicina </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;"><chr></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;"><chr></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> No UCI E. coli 100% (97-100%) 98% (96-99%) 98% (96-99%)</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> UCI E. coli 100% (93-100%) 99% (95-100%) 96% (92-99%)</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> `Grupo sindrómico` Patógeno Amikacina Gentamicina Tobramicina</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;"><chr></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;"><chr></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> No UCI E. coli 100% (97-100%,N=119) 98% (96-99%,N=32… 98% (96-99…</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> UCI E. coli 100% (93-100%,N=52) 99% (95-100%,N=1… 96% (92-99…</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Use `plot()` or `ggplot2::autoplot()` to create a plot of this antibiogram,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># or use it directly in R Markdown or https://quarto.org, see ?antibiogram</span></span>
|
||||
<span class="r-in"><span></span></span>
|
||||
|
||||
Reference in New Issue
Block a user