* Removed `as.integer()` for MIC values, since MIC are not integer values and running `table()` on MIC values will consequently fail for not being able to retrieve the level position (as that's how normally `as.integer()` on `factor`s work)
* `droplevels()` on MIC will now return a common `factor` at default and will lose the `<mic>` class. Use `droplevels(..., as.mic = TRUE)` to keep the `<mic>` class.
<p>Update March 2022: All functions in this package are considered to be
stable. Updates to the AMR interpretation rules (such as by EUCAST and
CLSI), the microbial taxonomy, and the antibiotic dosages will all be
updated every 6 to 12 months.</p>
<p>Update March 2022: All functions in this package are considered to be stable. Updates to the AMR interpretation rules (such as by EUCAST and CLSI), the microbial taxonomy, and the antibiotic dosages will all be updated every 6 to 12 months.</p>
</blockquote>
<divclass="section level3">
<h3id="what-is-amr-for-r">What is <code>AMR</code> (for R)?<aclass="anchor"aria-label="anchor"href="#what-is-amr-for-r"></a>
</h3>
<p><code>AMR</code> is a free, open-source and independent <ahref="https://www.r-project.org"class="external-link">R package</a> (see <ahref="#copyright">Copyright</a>) to simplify the analysis and prediction
of Antimicrobial Resistance (AMR) and to work with microbial and
antimicrobial data and properties, by using evidence-based methods.
<strong>Our aim is to provide a standard</strong> for clean and
reproducible AMR data analysis, that can therefore empower
epidemiological analyses to continuously enable surveillance and
treatment evaluation in any setting.</p>
<p>After installing this package, R knows <ahref="./reference/microorganisms.html"><strong>~71,000 distinct
microbial species</strong></a> and all <ahref="./reference/antibiotics.html"><strong>~570 antibiotic, antimycotic
and antiviral drugs</strong></a> by name and code (including ATC,
WHONET/EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about
valid R/SI and MIC values. It supports any data format, including
Swedish. Antimicrobial drug (group) names and colloquial microorganism
names are provided in these languages.</p>
<p>This package is <ahref="https://en.wikipedia.org/wiki/Dependency_hell"class="external-link">fully independent
of any other R package</a> and works on Windows, macOS and Linux with
all versions of R since R-3.0 (April 2013). <strong>It was designed to
work in any setting, including those with very limited
resources</strong>. It was created for both routine data analysis and
academic research at the Faculty of Medical Sciences of the <ahref="https://www.rug.nl"class="external-link">University of Groningen</a>, in collaboration
with non-profit organisations <ahref="https://www.certe.nl"class="external-link">Certe
Medical Diagnostics and Advice Foundation</a> and <ahref="https://www.umcg.nl"class="external-link">University Medical Center Groningen</a>. This
R package formed the basis of two PhD theses (<ahref="https://doi.org/10.33612/diss.177417131"class="external-link">DOI
10.33612/diss.177417131</a> and <ahref="https://doi.org/10.33612/diss.192486375"class="external-link">DOI
10.33612/diss.192486375</a>) but is <ahref="./news">actively and
durably maintained</a> by two public healthcare organisations in the
Netherlands.</p>
<p><code>AMR</code> is a free, open-source and independent <ahref="https://www.r-project.org"class="external-link">R package</a> (see <ahref="#copyright">Copyright</a>) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. <strong>Our aim is to provide a standard</strong> for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.</p>
<p>After installing this package, R knows <ahref="./reference/microorganisms.html"><strong>~71,000 distinct microbial species</strong></a> and all <ahref="./reference/antibiotics.html"><strong>~570 antibiotic, antimycotic and antiviral drugs</strong></a> by name and code (including ATC, WHONET/EARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.</p>
<p>The <code>AMR</code> package is available in <imgsrc="lang_da.svg"style="height: 11px !important; vertical-align: initial !important;"> Danish, <imgsrc="lang_nl.svg"style="height: 11px !important; vertical-align: initial !important;"> Dutch, <imgsrc="lang_en.svg"style="height: 11px !important; vertical-align: initial !important;"> English, <imgsrc="lang_fr.svg"style="height: 11px !important; vertical-align: initial !important;"> French, <imgsrc="lang_de.svg"style="height: 11px !important; vertical-align: initial !important;"> German, <imgsrc="lang_it.svg"style="height: 11px !important; vertical-align: initial !important;"> Italian, <imgsrc="lang_pt.svg"style="height: 11px !important; vertical-align: initial !important;"> Portuguese, <imgsrc="lang_ru.svg"style="height: 11px !important; vertical-align: initial !important;"> Russian, <imgsrc="lang_es.svg"style="height: 11px !important; vertical-align: initial !important;"> Spanish and <imgsrc="lang_sv.svg"style="height: 11px !important; vertical-align: initial !important;"> Swedish. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.</p>
<p>This package is <ahref="https://en.wikipedia.org/wiki/Dependency_hell"class="external-link">fully independent of any other R package</a> and works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). <strong>It was designed to work in any setting, including those with very limited resources</strong>. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the <ahref="https://www.rug.nl"class="external-link">University of Groningen</a>, in collaboration with non-profit organisations <ahref="https://www.certe.nl"class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <ahref="https://www.umcg.nl"class="external-link">University Medical Center Groningen</a>. This R package formed the basis of two PhD theses (<ahref="https://doi.org/10.33612/diss.177417131"class="external-link">DOI 10.33612/diss.177417131</a> and <ahref="https://doi.org/10.33612/diss.192486375"class="external-link">DOI 10.33612/diss.192486375</a>) but is <ahref="./news">actively and durably maintained</a> by two public healthcare organisations in the Netherlands.</p>
<strong>Used in 175 countries</strong><br> Since its first public
release in early 2018, this R package has been used in almost all
countries in the world. Click the map to enlarge and to see the country
names.
<ahref="./countries_large.png"target="_blank"><imgsrc="./countries.png"class="countries_map"></a><strong>Used in 175 countries</strong><br> Since its first public release in early 2018, this R package has been used in almost all countries in the world. Click the map to enlarge and to see the country names.
</p>
</div>
<divclass="section level5">
<h5id="with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side">With <code>AMR</code> (for R), there’s always a knowledgeable
microbiologist by your side!<aclass="anchor"aria-label="anchor"href="#with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side"></a>
<h5id="with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side">With <code>AMR</code> (for R), there’s always a knowledgeable microbiologist by your side!<aclass="anchor"aria-label="anchor"href="#with-amr-for-r-theres-always-a-knowledgeable-microbiologist-by-your-side"></a>
<p>With only having defined a row filter on Gram-negative bacteria with
intrinsic resistance to cefotaxime (<code><ahref="reference/mo_property.html">mo_is_gram_negative()</a></code>
and <code><ahref="reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>) and a column selection on
two antibiotic groups (<code><ahref="reference/antibiotic_class_selectors.html">aminoglycosides()</a></code> and
<code><ahref="reference/antibiotic_class_selectors.html">carbapenems()</a></code>), the reference data about <ahref="./reference/microorganisms.html">all microorganisms</a> and <ahref="./reference/antibiotics.html">all antibiotics</a> in the
<code>AMR</code> package make sure you get what you meant:</p>
<p>With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (<code><ahref="reference/mo_property.html">mo_is_gram_negative()</a></code> and <code><ahref="reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>) and a column selection on two antibiotic groups (<code><ahref="reference/antibiotic_class_selectors.html">aminoglycosides()</a></code> and <code><ahref="reference/antibiotic_class_selectors.html">carbapenems()</a></code>), the reference data about <ahref="./reference/microorganisms.html">all microorganisms</a> and <ahref="./reference/antibiotics.html">all antibiotics</a> in the <code>AMR</code> package make sure you get what you meant:</p>
<tableclass="table">
<thead><trclass="header">
<thalign="left">bacteria</th>
@ -395,14 +338,9 @@ two antibiotic groups (<code><a href="reference/antibiotic_class_selectors.html"
<p>The development of this package is part of, related to, or made
possible by:</p>
<p>The development of this package is part of, related to, or made possible by:</p>
<divalign="center">
<p><ahref="https://www.rug.nl"title="University of Groningen"class="external-link"><imgsrc="./logo_rug.png"class="partner_logo"></a>
<ahref="https://www.umcg.nl"title="University Medical Center Groningen"class="external-link"><imgsrc="./logo_umcg.png"class="partner_logo"></a>
<ahref="https://www.certe.nl"title="Certe Medical Diagnostics and Advice Foundation"class="external-link"><imgsrc="./logo_certe.png"class="partner_logo"></a>
<p><ahref="https://www.rug.nl"title="University of Groningen"class="external-link"><imgsrc="./logo_rug.png"class="partner_logo"></a><ahref="https://www.umcg.nl"title="University Medical Center Groningen"class="external-link"><imgsrc="./logo_umcg.png"class="partner_logo"></a><ahref="https://www.certe.nl"title="Certe Medical Diagnostics and Advice Foundation"class="external-link"><imgsrc="./logo_certe.png"class="partner_logo"></a><ahref="https://www.deutschland-nederland.eu"title="EurHealth-1-Health"class="external-link"><imgsrc="./logo_eh1h.png"class="partner_logo"></a><ahref="https://www.deutschland-nederland.eu"title="INTERREG"class="external-link"><imgsrc="./logo_interreg.png"class="partner_logo"></a></p>
</div>
</div>
</div>
@ -411,33 +349,21 @@ possible by:</p>
</h3>
<p>This package can be used for:</p>
<ul>
<li>Reference for the taxonomy of microorganisms, since the package
contains all microbial (sub)species from the <ahref="http://www.catalogueoflife.org"class="external-link">Catalogue of Life</a> and <ahref="https://lpsn.dsmz.de"class="external-link">List of Prokaryotic names with Standing in
<li>Interpreting raw MIC and disk diffusion values, based on the latest
CLSI or EUCAST guidelines (<ahref="./reference/as.rsi.html">manual</a>)</li>
<li>Retrieving antimicrobial drug names, doses and forms of
administration from clinical health care records (<ahref="./reference/ab_from_text.html">manual</a>)</li>
<li>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the <ahref="http://www.catalogueoflife.org"class="external-link">Catalogue of Life</a> and <ahref="https://lpsn.dsmz.de"class="external-link">List of Prokaryotic names with Standing in Nomenclature</a> (<ahref="./reference/mo_property.html">manual</a>)</li>
<li>Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines (<ahref="./reference/as.rsi.html">manual</a>)</li>
<li>Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records (<ahref="./reference/ab_from_text.html">manual</a>)</li>
<li>Determining first isolates to be used for AMR data analysis (<ahref="./reference/first_isolate.html">manual</a>)</li>
<li>Calculating (empirical) susceptibility of both mono therapy and combination therapies (<ahref="./articles/AMR.html">tutorial</a>)</li>
<li>Predicting future antimicrobial resistance using regression models (<ahref="./articles/resistance_predict.html">tutorial</a>)</li>
<li>Getting properties for any microorganism (like Gram stain, species, genus or family) (<ahref="./reference/mo_property.html">manual</a>)</li>
<li>Getting properties for any antibiotic (like name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name) (<ahref="./reference/ab_property.html">manual</a>)</li>
<li>Getting SNOMED codes of a microorganism, or getting properties of a
microorganism based on a SNOMED code (<ahref="./reference/mo_property.html">manual</a>)</li>
<li>Getting LOINC codes of an antibiotic, or getting properties of an
antibiotic based on a LOINC code (<ahref="./reference/ab_property.html">manual</a>)</li>
<li>Machine reading the EUCAST and CLSI guidelines from 2011-2021 to
translate MIC values and disk diffusion diameters to R/SI (<ahref="./articles/datasets.html">link</a>)</li>
<li>Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code (<ahref="./reference/mo_property.html">manual</a>)</li>
<li>Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code (<ahref="./reference/ab_property.html">manual</a>)</li>
<li>Machine reading the EUCAST and CLSI guidelines from 2011-2021 to translate MIC values and disk diffusion diameters to R/SI (<ahref="./articles/datasets.html">link</a>)</li>
<li>Principal component analysis for AMR (<ahref="./articles/PCA.html">tutorial</a>)</li>
</ul>
</div>
@ -448,24 +374,17 @@ translate MIC values and disk diffusion diameters to R/SI (<a href="./articles/d
<h4id="latest-released-version">Latest released version<aclass="anchor"aria-label="anchor"href="#latest-released-version"></a>
<p>This package is available <ahref="https://cran.r-project.org/package=AMR"class="external-link">here on the official R
network (CRAN)</a>. Install this package in R from CRAN by using the
command:</p>
<p>This package is available <ahref="https://cran.r-project.org/package=AMR"class="external-link">here on the official R network (CRAN)</a>. Install this package in R from CRAN by using the command:</p>
<p>It will be downloaded and installed automatically. For RStudio, click
on the menu <em>Tools</em>><em>Install Packages…</em> and then type
in “AMR” and press <kbd>Install</kbd>.</p>
<p><strong>Note:</strong> Not all functions on this website may be
available in this latest release. To use all functions and data sets
mentioned on this website, install the latest development version.</p>
<p>It will be downloaded and installed automatically. For RStudio, click on the menu <em>Tools</em>><em>Install Packages…</em> and then type in “AMR” and press <kbd>Install</kbd>.</p>
<p><strong>Note:</strong> Not all functions on this website may be available in this latest release. To use all functions and data sets mentioned on this website, install the latest development version.</p>
</div>
<divclass="section level4">
<h4id="latest-development-version">Latest development version<aclass="anchor"aria-label="anchor"href="#latest-development-version"></a>
<p>Automatically, using the <ahref="https://ropensci.org/r-universe/"class="external-link">rOpenSci R-universe
platform</a>, by adding <ahref="https://msberends.r-universe.dev"class="external-link">our
R-universe address</a> to your list of repositories (‘repos’):</p>
<p>Automatically, using the <ahref="https://ropensci.org/r-universe/"class="external-link">rOpenSci R-universe platform</a>, by adding <ahref="https://msberends.r-universe.dev"class="external-link">our R-universe address</a> to your list of repositories (‘repos’):</p>
<p>After this, you can install and update this <code>AMR</code> package
like any official release (e.g., using
<code>install.packages("AMR")</code> or in RStudio via <em>Tools</em>
><em>Check for Package Updates…</em>).</p>
<p>After this, you can install and update this <code>AMR</code> package like any official release (e.g., using <code>install.packages("AMR")</code> or in RStudio via <em>Tools</em>><em>Check for Package Updates…</em>).</p>
</li>
</ol>
<p>You can also download the latest build from our repository: <ahref="https://github.com/msberends/AMR/raw/main/data-raw/AMR_latest.tar.gz"class="external-link uri">https://github.com/msberends/AMR/raw/main/data-raw/AMR_latest.tar.gz</a></p>
@ -492,8 +406,7 @@ like any official release (e.g., using
<p>To find out how to conduct AMR data analysis, please <ahref="./articles/AMR.html">continue reading here to get started</a> or
click a link in the <ahref="https://msberends.github.io/AMR/articles/">‘How to’ menu</a>.</p>
<p>To find out how to conduct AMR data analysis, please <ahref="./articles/AMR.html">continue reading here to get started</a> or click a link in the <ahref="https://msberends.github.io/AMR/articles/">‘How to’ menu</a>.</p>
This supplementation is needed until the <ahref="https://github.com/Sp2000/colplus"class="external-link">CoL+ project</a> is finished,
which we await. With <code><ahref="reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code> can be
checked which version of the CoL is included in this package.</p>
<p>This package contains the complete taxonomic tree of almost all ~71,000 microorganisms from the authoritative and comprehensive Catalogue of Life (CoL, <ahref="http://www.catalogueoflife.org"class="external-link">www.catalogueoflife.org</a>), supplemented by data from the List of Prokaryotic names with Standing in Nomenclature (LPSN, <ahref="https://lpsn.dsmz.de"class="external-link">lpsn.dsmz.de</a>). This supplementation is needed until the <ahref="https://github.com/Sp2000/colplus"class="external-link">CoL+ project</a> is finished, which we await. With <code><ahref="reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code> can be checked which version of the CoL is included in this package.</p>
<p>Read more about which data from the Catalogue of Life <ahref="./reference/catalogue_of_life.html">in our manual</a>.</p>
<p>This package contains <strong>all ~570 antibiotic, antimycotic and
antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC)
codes, ATC groups and Defined Daily Dose (DDD, oral and IV) from the
World Health Organization Collaborating Centre for Drug Statistics
Methodology (WHOCC, <ahref="https://www.whocc.no"class="external-link uri">https://www.whocc.no</a>) and the <ahref="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm"class="external-link">Pharmaceuticals
Community Register of the European Commission</a>.</p>
<p><strong>NOTE: The WHOCC copyright does not allow use for commercial
purposes, unlike any other info from this package. See <ahref="https://www.whocc.no/copyright_disclaimer/"class="external-link uri">https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
<p>This package contains <strong>all ~570 antibiotic, antimycotic and antiviral drugs</strong> and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD, oral and IV) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, <ahref="https://www.whocc.no"class="external-link uri">https://www.whocc.no</a>) and the <ahref="https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm"class="external-link">Pharmaceuticals Community Register of the European Commission</a>.</p>
<p><strong>NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See <ahref="https://www.whocc.no/copyright_disclaimer/"class="external-link uri">https://www.whocc.no/copyright_disclaimer/</a>.</strong></p>
<p>Read more about the data from WHOCC <ahref="./reference/WHOCC.html">in our manual</a>.</p>
<p>We support WHONET and EARS-Net data. Exported files from WHONET can
be imported into R and can be analysed easily using this package. For
education purposes, we created an <ahref="./reference/WHONET.html">example data set <code>WHONET</code></a>
with the exact same structure as a WHONET export file. Furthermore, this
package also contains a <ahref="./reference/antibiotics.html">data set
antibiotics</a> with all EARS-Net antibiotic abbreviations, and knows
almost all WHONET abbreviations for microorganisms. When using WHONET
data as input for analysis, all input parameters will be set
automatically.</p>
<p>Read our tutorial about <ahref="./articles/WHONET.html">how to work
with WHONET data here</a>.</p>
<p>We support WHONET and EARS-Net data. Exported files from WHONET can be imported into R and can be analysed easily using this package. For education purposes, we created an <ahref="./reference/WHONET.html">example data set <code>WHONET</code></a> with the exact same structure as a WHONET export file. Furthermore, this package also contains a <ahref="./reference/antibiotics.html">data set antibiotics</a> with all EARS-Net antibiotic abbreviations, and knows almost all WHONET abbreviations for microorganisms. When using WHONET data as input for analysis, all input parameters will be set automatically.</p>
<p>Read our tutorial about <ahref="./articles/WHONET.html">how to work with WHONET data here</a>.</p>
</div>
<divclass="section level4">
<h4id="overview-of-functions">Overview of functions<aclass="anchor"aria-label="anchor"href="#overview-of-functions"></a>
</h4>
<p>The <code>AMR</code> package basically does four important
things:</p>
<p>The <code>AMR</code> package basically does four important things:</p>
<olstyle="list-style-type: decimal">
<li>
<p>It <strong>cleanses existing data</strong> by providing new
<em>classes</em> for microoganisms, antibiotics and antimicrobial
results (both S/I/R and MIC). By installing this package, you teach R
everything about microbiology that is needed for analysis. These
functions all use intelligent rules to guess results that you would
expect:</p>
<p>It <strong>cleanses existing data</strong> by providing new <em>classes</em> for microoganisms, antibiotics and antimicrobial results (both S/I/R and MIC). By installing this package, you teach R everything about microbiology that is needed for analysis. These functions all use intelligent rules to guess results that you would expect:</p>
<ul>
<li>Use <code><ahref="reference/as.mo.html">as.mo()</a></code> to get a microbial ID. The IDs are human
readable for the trained eye - the ID of <em>Klebsiella pneumoniae</em>
is “B_KLBSL_PNMN” (B stands for Bacteria) and the ID of <em>S.
aureus</em> is “B_STPHY_AURS”. The function takes almost any text as
input that looks like the name or code of a microorganism like “E.
coli”, “esco” or “esccol” and tries to find expected results using
intelligent rules combined with the included Catalogue of Life data set.
It only takes milliseconds to find results, please see our <ahref="./articles/benchmarks.html">benchmarks</a>. Moreover, it can group
<em>Staphylococci</em> into coagulase negative and positive (CoNS and
CoPS, see <ahref="./reference/as.mo.html#source">source</a>) and can
categorise <em>Streptococci</em> into Lancefield groups (like
beta-haemolytic <em>Streptococcus</em> Group B, <ahref="./reference/as.mo.html#source">source</a>).</li>
<li>Use <code><ahref="reference/as.ab.html">as.ab()</a></code> to get an antibiotic ID. Like microbial
IDs, these IDs are also human readable based on those used by EARS-Net.
For example, the ID of amoxicillin is <code>AMX</code> and the ID of
gentamicin is <code>GEN</code>. The <code><ahref="reference/as.ab.html">as.ab()</a></code> function also
uses intelligent rules to find results like accepting misspelling, trade
names and abbrevations used in many laboratory systems. For instance,
the values “Furabid”, “Furadantin”, “nitro” all return the ID of
Nitrofurantoine. To accomplish this, the package contains a database
with most LIS codes, official names, trade names, ATC codes, defined
daily doses (DDD) and drug categories of antibiotics.</li>
<li>Use <code><ahref="reference/as.rsi.html">as.rsi()</a></code> to get antibiotic interpretations based on
raw MIC values (in mg/L) or disk diffusion values (in mm), or transform
existing values to valid antimicrobial results. It produces just S, I or
R based on your input and warns about invalid values. Even values like
“<=0.002; S” (combined MIC/RSI) will result in “S”.</li>
<li>Use <code><ahref="reference/as.mic.html">as.mic()</a></code> to cleanse your MIC values. It produces a
so-called factor (called <em>ordinal</em> in SPSS) with valid MIC values
as levels. A value like “<=0.002; S” (combined MIC/RSI) will result
in “<=0.002”.</li>
<li>Use <code><ahref="reference/as.mo.html">as.mo()</a></code> to get a microbial ID. The IDs are human readable for the trained eye - the ID of <em>Klebsiella pneumoniae</em> is “B_KLBSL_PNMN” (B stands for Bacteria) and the ID of <em>S. aureus</em> is “B_STPHY_AURS”. The function takes almost any text as input that looks like the name or code of a microorganism like “E. coli”, “esco” or “esccol” and tries to find expected results using intelligent rules combined with the included Catalogue of Life data set. It only takes milliseconds to find results, please see our <ahref="./articles/benchmarks.html">benchmarks</a>. Moreover, it can group <em>Staphylococci</em> into coagulase negative and positive (CoNS and CoPS, see <ahref="./reference/as.mo.html#source">source</a>) and can categorise <em>Streptococci</em> into Lancefield groups (like beta-haemolytic <em>Streptococcus</em> Group B, <ahref="./reference/as.mo.html#source">source</a>).</li>
<li>Use <code><ahref="reference/as.ab.html">as.ab()</a></code> to get an antibiotic ID. Like microbial IDs, these IDs are also human readable based on those used by EARS-Net. For example, the ID of amoxicillin is <code>AMX</code> and the ID of gentamicin is <code>GEN</code>. The <code><ahref="reference/as.ab.html">as.ab()</a></code> function also uses intelligent rules to find results like accepting misspelling, trade names and abbrevations used in many laboratory systems. For instance, the values “Furabid”, “Furadantin”, “nitro” all return the ID of Nitrofurantoine. To accomplish this, the package contains a database with most LIS codes, official names, trade names, ATC codes, defined daily doses (DDD) and drug categories of antibiotics.</li>
<li>Use <code><ahref="reference/as.rsi.html">as.rsi()</a></code> to get antibiotic interpretations based on raw MIC values (in mg/L) or disk diffusion values (in mm), or transform existing values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like “<=0.002; S” (combined MIC/RSI) will result in “S”.</li>
<li>Use <code><ahref="reference/as.mic.html">as.mic()</a></code> to cleanse your MIC values. It produces a so-called factor (called <em>ordinal</em> in SPSS) with valid MIC values as levels. A value like “<=0.002; S” (combined MIC/RSI) will result in “<=0.002”.</li>
</ul>
</li>
<li>
<p>It <strong>enhances existing data</strong> and <strong>adds new
data</strong> from data sets included in this package.</p>
<p>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</p>
<ul>
<li>Use <code><ahref="reference/eucast_rules.html">eucast_rules()</a></code> to apply <ahref="https://www.eucast.org/expert_rules_and_intrinsic_resistance/"class="external-link">EUCAST
expert rules to isolates</a> (not the translation from MIC to R/SI
values, use <code><ahref="reference/as.rsi.html">as.rsi()</a></code> for that).</li>
<li>Use <code><ahref="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of
every patient <ahref="https://clsi.org/standards/products/microbiology/documents/m39/"class="external-link">using
guidelines from the CLSI</a> (Clinical and Laboratory Standards
Institute).
<li>Use <code><ahref="reference/eucast_rules.html">eucast_rules()</a></code> to apply <ahref="https://www.eucast.org/expert_rules_and_intrinsic_resistance/"class="external-link">EUCAST expert rules to isolates</a> (not the translation from MIC to R/SI values, use <code><ahref="reference/as.rsi.html">as.rsi()</a></code> for that).</li>
<li>Use <code><ahref="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of every patient <ahref="https://clsi.org/standards/products/microbiology/documents/m39/"class="external-link">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
<ul>
<li>You can also identify first <em>weighted</em> isolates of every
patient, an adjusted version of the CLSI guideline. This takes into
account key antibiotics of every strain and compares them.</li>
<li>You can also identify first <em>weighted</em> isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them.</li>
</ul>
</li>
<li>Use <code><ahref="reference/mdro.html">mdro()</a></code> to determine which micro-organisms are
multi-drug resistant organisms (MDRO). It supports a variety of
international guidelines, such as the MDR-paper by Magiorakos <em>et
<code><ahref="reference/ab_property.html">ab_loinc()</a></code> and <code><ahref="reference/ab_property.html">ab_tradenames()</a></code> to look up
values. The <code>ab_*</code> functions use <code><ahref="reference/as.ab.html">as.ab()</a></code>
internally so they support the same intelligent rules to guess the most
probable result. For example, <code>ab_name("Fluclox")</code>,
<code>ab_name("Floxapen")</code> and <code>ab_name("J01CF05")</code>
will all return <code>"Flucloxacillin"</code>. These functions can again
be used to add new variables to your data.</li>
<li>Use <code><ahref="reference/mdro.html">mdro()</a></code> to determine which micro-organisms are multi-drug resistant organisms (MDRO). It supports a variety of international guidelines, such as the MDR-paper by Magiorakos <em>et al.</em> (2012, <ahref="https://www.ncbi.nlm.nih.gov/pubmed/?term=21793988"class="external-link">PMID 21793988</a>), the exceptional phenotype definitions of EUCAST and the WHO guideline on multi-drug resistant TB. It also supports the national guidelines of the Netherlands and Germany.</li>
<li>The <ahref="./reference/microorganisms.html">data set microorganisms</a> contains the complete taxonomic tree of ~70,000 microorganisms. Furthermore, some colloquial names and all Gram stains are available, which enables resistance analysis of e.g.different antibiotics per Gram stain. The package also contains functions to look up values in this data set like <code><ahref="reference/mo_property.html">mo_genus()</a></code>, <code><ahref="reference/mo_property.html">mo_family()</a></code>, <code><ahref="reference/mo_property.html">mo_gramstain()</a></code> or even <code><ahref="reference/mo_property.html">mo_phylum()</a></code>. Use <code><ahref="reference/mo_property.html">mo_snomed()</a></code> to look up any SNOMED CT code associated with a microorganism. As all these function use <code><ahref="reference/as.mo.html">as.mo()</a></code> internally, they also use the same intelligent rules for determination. For example, <code>mo_genus("MRSA")</code> and <code>mo_genus("S. aureus")</code> will both return <code>"Staphylococcus"</code>. They also come with support for German, Danish, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.</li>
<li>The <ahref="./reference/antibiotics.html">data set antibiotics</a> contains ~450 antimicrobial drugs with their EARS-Net code, ATC code, PubChem compound ID, LOINC code, official name, common LIS codes and DDDs of both oral and parenteral administration. It also contains all (thousands of) trade names found in PubChem. Use functions like <code><ahref="reference/ab_property.html">ab_name()</a></code>, <code><ahref="reference/ab_property.html">ab_group()</a></code>, <code><ahref="reference/ab_property.html">ab_atc()</a></code>, <code><ahref="reference/ab_property.html">ab_loinc()</a></code> and <code><ahref="reference/ab_property.html">ab_tradenames()</a></code> to look up values. The <code>ab_*</code> functions use <code><ahref="reference/as.ab.html">as.ab()</a></code> internally so they support the same intelligent rules to guess the most probable result. For example, <code>ab_name("Fluclox")</code>, <code>ab_name("Floxapen")</code> and <code>ab_name("J01CF05")</code> will all return <code>"Flucloxacillin"</code>. These functions can again be used to add new variables to your data.</li>
</ul>
</li>
<li>
<p>It <strong>analyses the data</strong> with convenient functions
that use well-known methods.</p>
<p>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</p>
<ul>
<li>Calculate the microbial susceptibility or resistance (and even
co-resistance) with the <code><ahref="reference/proportion.html">susceptibility()</a></code> and
<code><ahref="reference/proportion.html">resistance()</a></code> functions, or be even more specific with the
<code><ahref="reference/proportion.html">proportion_I()</a></code>, <code><ahref="reference/proportion.html">proportion_SI()</a></code> and
<code><ahref="reference/proportion.html">proportion_S()</a></code> functions. Similarly, the <em>number</em> of
isolates can be determined with the <code><ahref="reference/count.html">count_resistant()</a></code>,
<code><ahref="reference/count.html">count_susceptible()</a></code> and <code><ahref="reference/count.html">count_all()</a></code> functions.
All these functions can be used with the <code>dplyr</code> package
(e.g.in conjunction with <code><ahref="https://dplyr.tidyverse.org/reference/summarise.html"class="external-link">summarise()</a></code>)</li>
<li>Plot AMR results with <code><ahref="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for
the <code>ggplot2</code> package</li>
<li>Predict antimicrobial resistance for the nextcoming years using
logistic regression models with the <code><ahref="reference/resistance_predict.html">resistance_predict()</a></code>
function</li>
<li>Calculate the microbial susceptibility or resistance (and even co-resistance) with the <code><ahref="reference/proportion.html">susceptibility()</a></code> and <code><ahref="reference/proportion.html">resistance()</a></code> functions, or be even more specific with the <code><ahref="reference/proportion.html">proportion_R()</a></code>, <code><ahref="reference/proportion.html">proportion_IR()</a></code>, <code><ahref="reference/proportion.html">proportion_I()</a></code>, <code><ahref="reference/proportion.html">proportion_SI()</a></code> and <code><ahref="reference/proportion.html">proportion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><ahref="reference/count.html">count_resistant()</a></code>, <code><ahref="reference/count.html">count_susceptible()</a></code> and <code><ahref="reference/count.html">count_all()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g.in conjunction with <code><ahref="https://dplyr.tidyverse.org/reference/summarise.html"class="external-link">summarise()</a></code>)</li>
<li>Plot AMR results with <code><ahref="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for the <code>ggplot2</code> package</li>
<li>Predict antimicrobial resistance for the nextcoming years using logistic regression models with the <code><ahref="reference/resistance_predict.html">resistance_predict()</a></code> function</li>
</ul>
</li>
<li>
<p>It <strong>teaches the user</strong> how to use all the above
actions.</p>
<p>It <strong>teaches the user</strong> how to use all the above actions.</p>
<ul>
<li>Aside from this website with many tutorials, the package itself
contains extensive help pages with many examples for all functions.</li>
<li>Aside from this website with many tutorials, the package itself contains extensive help pages with many examples for all functions.</li>
data set</a>. This data set contains 2,000 microbial isolates with their
full antibiograms. It reflects reality and can be used to practice AMR
data analysis.</li>
<li>The <ahref="./reference/WHONET.html"><code>WHONET</code> data
set</a>. This data set only contains fake data, but with the exact same
structure as files exported by WHONET. Read more about WHONET <ahref="./articles/WHONET.html">on its tutorial page</a>.</li>
<li>The <ahref="./reference/example_isolates.html"><code>example_isolates</code> data set</a>. This data set contains 2,000 microbial isolates with their full antibiograms. It reflects reality and can be used to practice AMR data analysis.</li>
<li>The <ahref="./reference/WHONET.html"><code>WHONET</code> data set</a>. This data set only contains fake data, but with the exact same structure as files exported by WHONET. Read more about WHONET <ahref="./articles/WHONET.html">on its tutorial page</a>.</li>
</ul>
</li>
</ul>
@ -686,9 +484,7 @@ structure as files exported by WHONET. Read more about WHONET <a href="./article
<p>This R package is free, open-source software and licensed under the
<ahref="./LICENSE-text.html">GNU General Public License v2.0
(GPL-2)</a>. In a nutshell, this means that this package:</p>
<p>This R package is free, open-source software and licensed under the <ahref="./LICENSE-text.html">GNU General Public License v2.0 (GPL-2)</a>. In a nutshell, this means that this package:</p>
<ul>
<li><p>May be used for commercial purposes</p></li>
<li><p>May be used for private purposes</p></li>
@ -696,18 +492,15 @@ structure as files exported by WHONET. Read more about WHONET <a href="./article
<li>
<p>May be modified, although:</p>
<ul>
<li>Modifications <strong>must</strong> be released under the same
license when distributing the package</li>
<li>Modifications <strong>must</strong> be released under the same license when distributing the package</li>
<li>Changes made to the code <strong>must</strong> be documented</li>
</ul>
</li>
<li>
<p>May be distributed, although:</p>
<ul>
<li>Source code <strong>must</strong> be made available when the package
is distributed</li>
<li>A copy of the license and copyright notice <strong>must</strong> be
included with the package.</li>
<li>Source code <strong>must</strong> be made available when the package is distributed</li>
<li>A copy of the license and copyright notice <strong>must</strong> be included with the package.</li>
</ul>
</li>
<li><p>Comes with a LIMITATION of liability</p></li>
@ -763,14 +556,12 @@ included with the package.</li>
<footer><divclass="copyright">
<p></p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
Erwin E. A. Hassing.</p>
<p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein, Erwin E. A. Hassing.</p>
</div>
<divclass="pkgdown">
<p></p>
<p>Site built with <ahref="https://pkgdown.r-lib.org/"class="external-link">pkgdown</a>
2.0.2.</p>
<p>Site built with <ahref="https://pkgdown.r-lib.org/"class="external-link">pkgdown</a> 2.0.3.</p>
<p>The international guideline for multi-drug resistant tuberculosis - World Health Organization "Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis" (<ahref="https://www.who.int/publications/i/item/9789241548809"class="external-link">link</a>)</p></li>
<li><p><code>guideline = "MRGN"</code></p>
<p>The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7; doi: <ahref="https://doi.org/10.1186/s13756-015-0047-6"class="external-link">10.1186/s13756-015-0047-6</a></p></li>
<p>The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7; <ahref="https://doi.org/10.1186/s13756-015-0047-6"class="external-link">doi:10.1186/s13756-015-0047-6</a></p></li>
<li><p><code>guideline = "BRMO"</code></p>
<p>The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)" (<ahref="https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh"class="external-link">link</a>)</p></li>
</ul><p>Please suggest your own (country-specific) guidelines by letting us know: <ahref="https://github.com/msberends/AMR/issues/new"class="external-link">https://github.com/msberends/AMR/issues/new</a>.</p>
@ -356,7 +356,7 @@ A microorganism is categorised as <em>Susceptible, Increased exposure</em> when
</div>
<divclass="pkgdown">
<p></p><p>Site built with <ahref="https://pkgdown.r-lib.org/"class="external-link">pkgdown</a> 2.0.2.</p>
<p></p><p>Site built with <ahref="https://pkgdown.r-lib.org/"class="external-link">pkgdown</a> 2.0.3.</p>
<li><p>Becker K <em>et al.</em><strong>Implications of identifying the recently defined members of the <em>S. aureus</em> complex, <em>S. argenteus</em> and <em>S. schweitzeri</em>: A position paper of members of the ESCMID Study Group for staphylococci and Staphylococcal Diseases (ESGS).</strong> 2019. Clin Microbiol Infect; doi: <ahref="https://doi.org/10.1016/j.cmi.2019.02.028"class="external-link">10.1016/j.cmi.2019.02.028</a></p></li>
<li><p>Becker K <em>et al.</em><strong>Emergence of coagulase-negative staphylococci</strong> 2020. Expert Rev Anti Infect Ther. 18(4):349-366; doi: <ahref="https://doi.org/10.1080/14787210.2020.1730813"class="external-link">10.1080/14787210.2020.1730813</a></p></li>
<li><p>Lancefield RC <strong>A serological differentiation of human and other groups of hemolytic streptococci</strong>. 1933. J Exp Med. 57(4): 571-95; doi: <ahref="https://doi.org/10.1084/jem.57.4.571"class="external-link">10.1084/jem.57.4.571</a></p></li>
<li><p>Becker K <em>et al.</em><strong>Implications of identifying the recently defined members of the <em>S. aureus</em> complex, <em>S. argenteus</em> and <em>S. schweitzeri</em>: A position paper of members of the ESCMID Study Group for staphylococci and Staphylococcal Diseases (ESGS).</strong> 2019. Clin Microbiol Infect; <ahref="https://doi.org/10.1016/j.cmi.2019.02.028"class="external-link">doi:10.1016/j.cmi.2019.02.028</a></p></li>
<li><p>Becker K <em>et al.</em><strong>Emergence of coagulase-negative staphylococci</strong> 2020. Expert Rev Anti Infect Ther. 18(4):349-366; <ahref="https://doi.org/10.1080/14787210.2020.1730813"class="external-link">doi:10.1080/14787210.2020.1730813</a></p></li>
<li><p>Lancefield RC <strong>A serological differentiation of human and other groups of hemolytic streptococci</strong>. 1933. J Exp Med. 57(4): 571-95; <ahref="https://doi.org/10.1084/jem.57.4.571"class="external-link">doi:10.1084/jem.57.4.571</a></p></li>
<li><p>Catalogue of Life: 2019 Annual Checklist, <ahref="http://www.catalogueoflife.org"class="external-link">http://www.catalogueoflife.org</a></p></li>
<li><p>List of Prokaryotic names with Standing in Nomenclature (5 October 2021), doi: <ahref="https://doi.org/10.1099/ijsem.0.004332"class="external-link">10.1099/ijsem.0.004332</a></p></li>
<li><p>List of Prokaryotic names with Standing in Nomenclature (5 October 2021), <ahref="https://doi.org/10.1099/ijsem.0.004332"class="external-link">doi:10.1099/ijsem.0.004332</a></p></li>
<li><p>US Edition of SNOMED CT from 1 September 2020, retrieved from the Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS), OID 2.16.840.1.114222.4.11.1009, version 12; url: <ahref="https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009"class="external-link">https://phinvads.cdc.gov/vads/ViewValueSet.action?oid=2.16.840.1.114222.4.11.1009</a></p></li>
</ol></div>
<divid="reference-data-publicly-available">
@ -437,7 +437,7 @@ This package contains the complete taxonomic tree of almost all microorganisms (
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<p></p><p>Site built with <ahref="https://pkgdown.r-lib.org/"class="external-link">pkgdown</a> 2.0.2.</p>
<p></p><p>Site built with <ahref="https://pkgdown.r-lib.org/"class="external-link">pkgdown</a> 2.0.3.</p>
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