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(v1.1.0.9019) mo_source fix
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@ -39,7 +39,7 @@
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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">1.1.0.9015</span>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.1.0.9019</span>
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</span>
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</div>
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@ -186,7 +186,7 @@
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<h1 data-toc-skip>How to determine multi-drug resistance (MDR)</h1>
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<h4 class="author">Matthijs S. Berends</h4>
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<h4 class="date">20 May 2020</h4>
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<h4 class="date">25 May 2020</h4>
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<small class="dont-index">Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/MDR.Rmd"><code>vignettes/MDR.Rmd</code></a></small>
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<div class="hidden name"><code>MDR.Rmd</code></div>
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@ -235,9 +235,9 @@ The German national guideline - Mueller et al. (2015) Antimicrobial Resistance a
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<div class="sourceCode" id="cb2"><html><body><pre class="r"><span class="no">example_isolates</span> <span class="kw">%>%</span>
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<span class="fu"><a href="../reference/mdro.html">mdro</a></span>() <span class="kw">%>%</span>
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<span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>() <span class="co"># show frequency table of the result</span>
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<span class="co"># [34mNOTE: Using column `[1mmo[22m` as input for `col_mo`.[39m</span>
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<span class="co"># [34mNOTE: Auto-guessing columns suitable for analysis...[39m[34mOK.[39m</span>
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<span class="co"># [34mNOTE: Reliability would be improved if these antimicrobial results would be available too: ceftaroline ([1mCPT[22m), fusidic acid ([1mFUS[22m), telavancin ([1mTLV[22m), daptomycin ([1mDAP[22m), quinupristin/dalfopristin ([1mQDA[22m), minocycline ([1mMNO[22m), gentamicin-high ([1mGEH[22m), streptomycin-high ([1mSTH[22m), doripenem ([1mDOR[22m), levofloxacin ([1mLVX[22m), netilmicin ([1mNET[22m), ticarcillin/clavulanic acid ([1mTCC[22m), ertapenem ([1mETP[22m), cefotetan ([1mCTT[22m), aztreonam ([1mATM[22m), ampicillin/sulbactam ([1mSAM[22m), polymyxin B ([1mPLB[22m)[39m</span>
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<span class="co"># NOTE: Using column `mo` as input for `col_mo`.</span>
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<span class="co"># NOTE: Auto-guessing columns suitable for analysis...OK.</span>
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<span class="co"># NOTE: Reliability would be improved if these antimicrobial results would be available too: ceftaroline (CPT), fusidic acid (FUS), telavancin (TLV), daptomycin (DAP), quinupristin/dalfopristin (QDA), minocycline (MNO), gentamicin-high (GEH), streptomycin-high (STH), doripenem (DOR), levofloxacin (LVX), netilmicin (NET), ticarcillin/clavulanic acid (TCC), ertapenem (ETP), cefotetan (CTT), aztreonam (ATM), ampicillin/sulbactam (SAM), polymyxin B (PLB)</span>
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<span class="co"># Warning in mdro(.): NA introduced for isolates where the available percentage of</span>
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<span class="co"># antimicrobial classes was below 50% (set with `pct_required_classes`)</span></pre></body></html></div>
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<p><strong>Frequency table</strong></p>
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@ -302,26 +302,26 @@ Unique: 2</p>
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<p>The data set now looks like this:</p>
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<div class="sourceCode" id="cb5"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span>(<span class="no">my_TB_data</span>)
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<span class="co"># rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin</span>
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<span class="co"># 1 R R R R S S</span>
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<span class="co"># 2 S S S I R S</span>
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<span class="co"># 3 S R S I S I</span>
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<span class="co"># 4 S R S S S R</span>
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<span class="co"># 5 R S R S S R</span>
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<span class="co"># 6 I S R R R R</span>
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<span class="co"># 1 S S R R S S</span>
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<span class="co"># 2 R R S R S R</span>
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<span class="co"># 3 R S S R S S</span>
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<span class="co"># 4 R S S S S R</span>
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<span class="co"># 5 S R R S R R</span>
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<span class="co"># 6 R R R R R R</span>
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<span class="co"># kanamycin</span>
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<span class="co"># 1 I</span>
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<span class="co"># 1 R</span>
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<span class="co"># 2 S</span>
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<span class="co"># 3 R</span>
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<span class="co"># 4 I</span>
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<span class="co"># 5 I</span>
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<span class="co"># 6 S</span></pre></body></html></div>
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<span class="co"># 3 S</span>
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<span class="co"># 4 S</span>
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<span class="co"># 5 R</span>
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<span class="co"># 6 R</span></pre></body></html></div>
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<p>We can now add the interpretation of MDR-TB to our data set. You can use:</p>
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<div class="sourceCode" id="cb6"><html><body><pre class="r"><span class="fu"><a href="../reference/mdro.html">mdro</a></span>(<span class="no">my_TB_data</span>, <span class="kw">guideline</span> <span class="kw">=</span> <span class="st">"TB"</span>)</pre></body></html></div>
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<p>or its shortcut <code><a href="../reference/mdro.html">mdr_tb()</a></code>:</p>
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<div class="sourceCode" id="cb7"><html><body><pre class="r"><span class="no">my_TB_data</span>$<span class="no">mdr</span> <span class="kw"><-</span> <span class="fu"><a href="../reference/mdro.html">mdr_tb</a></span>(<span class="no">my_TB_data</span>)
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<span class="co"># [34mNOTE: No column found as input for `col_mo`, [1massuming all records contain [3mMycobacterium tuberculosis.[23m[22m[39m</span>
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<span class="co"># [34mNOTE: Auto-guessing columns suitable for analysis...[39m[34mOK.[39m</span>
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<span class="co"># [34mNOTE: Reliability would be improved if these antimicrobial results would be available too: capreomycin ([1mCAP[22m), rifabutin ([1mRIB[22m), rifapentine ([1mRFP[22m)[39m</span></pre></body></html></div>
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<span class="co"># NOTE: No column found as input for `col_mo`, assuming all records contain Mycobacterium tuberculosis.</span>
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<span class="co"># NOTE: Auto-guessing columns suitable for analysis...OK.</span>
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<span class="co"># NOTE: Reliability would be improved if these antimicrobial results would be available too: capreomycin (CAP), rifabutin (RIB), rifapentine (RFP)</span></pre></body></html></div>
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<p>Create a frequency table of the results:</p>
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<div class="sourceCode" id="cb8"><html><body><pre class="r"><span class="fu"><a href="https://rdrr.io/pkg/cleaner/man/freq.html">freq</a></span>(<span class="no">my_TB_data</span>$<span class="no">mdr</span>)</pre></body></html></div>
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<p><strong>Frequency table</strong></p>
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@ -343,40 +343,40 @@ Unique: 5</p>
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<tr class="odd">
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<td align="left">1</td>
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<td align="left">Mono-resistant</td>
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<td align="right">3288</td>
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<td align="right">65.76%</td>
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<td align="right">3288</td>
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<td align="right">65.76%</td>
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<td align="right">3239</td>
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<td align="right">64.78%</td>
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<td align="right">3239</td>
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<td align="right">64.78%</td>
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</tr>
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<tr class="even">
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<td align="left">2</td>
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<td align="left">Negative</td>
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<td align="right">631</td>
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<td align="right">12.62%</td>
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<td align="right">3919</td>
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<td align="right">78.38%</td>
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<td align="right">655</td>
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<td align="right">13.10%</td>
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<td align="right">3894</td>
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<td align="right">77.88%</td>
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</tr>
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<tr class="odd">
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<td align="left">3</td>
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<td align="left">Multi-drug-resistant</td>
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<td align="right">582</td>
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<td align="right">11.64%</td>
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<td align="right">4501</td>
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<td align="right">90.02%</td>
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<td align="right">593</td>
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<td align="right">11.86%</td>
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<td align="right">4487</td>
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<td align="right">89.74%</td>
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</tr>
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<tr class="even">
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<td align="left">4</td>
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<td align="left">Poly-resistant</td>
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<td align="right">298</td>
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<td align="right">5.96%</td>
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<td align="right">4799</td>
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<td align="right">95.98%</td>
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<td align="right">304</td>
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<td align="right">6.08%</td>
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<td align="right">4791</td>
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<td align="right">95.82%</td>
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</tr>
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<tr class="odd">
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<td align="left">5</td>
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<td align="left">Extensively drug-resistant</td>
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<td align="right">201</td>
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<td align="right">4.02%</td>
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<td align="right">209</td>
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<td align="right">4.18%</td>
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<td align="right">5000</td>
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<td align="right">100.00%</td>
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</tr>
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