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(v.1.5.0.9000) implementation of EUCAST rules v11 (2021)

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dr. M.S. (Matthijs) Berends
2021-01-12 22:08:04 +01:00
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man/antibiotics.Rd
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@ -4,9 +4,9 @@
\name{antibiotics}
\alias{antibiotics}
\alias{antivirals}
\title{Data sets with 557 antimicrobials}
\title{Data sets with 558 antimicrobials}
\format{
\subsection{For the \link{antibiotics} data set: a \link{data.frame} with 455 observations and 14 variables:}{
\subsection{For the \link{antibiotics} data set: a \link{data.frame} with 456 observations and 14 variables:}{
\itemize{
\item \code{ab}\cr Antibiotic ID as used in this package (such as \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
\item \code{atc}\cr ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC, like \code{J01CR02}

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man/as.mo.Rd
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@ -143,16 +143,16 @@ If the unlying code needs breaking changes, they will occur gradually. For examp
With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}
\ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300px" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
where:
\itemize{
\item \eqn{x} is the user input;
\item \eqn{n} is a taxonomic name (genus, species, and subspecies);
\item \eqn{l_n}{l_n} is the length of \eqn{n};
\item lev is the \href{https://en.wikipedia.org/wiki/Levenshtein_distance}{Levenshtein distance function}, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};
\item \eqn{p_n}{p_n} is the human pathogenic prevalence group of \eqn{n}, as described below;
\item \eqn{k_n}{p_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
\item \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
\item \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
\item \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
\item \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;}}{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};}
\item \ifelse{html}{\out{<i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
\item \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
}
The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella},\\\emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium},\emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.

2
man/as.rsi.Rd
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@ -67,7 +67,7 @@ is.rsi.eligible(x, threshold = 0.05)
\item{conserve_capped_values}{a logical to indicate that MIC values starting with \code{">"} (but not \code{">="}) must always return "R" , and that MIC values starting with \code{"<"} (but not \code{"<="}) must always return "S"}
\item{add_intrinsic_resistance}{\emph{(only useful when using a EUCAST guideline)} a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in \emph{Klebsiella} species. Determination is based on the \link{intrinsic_resistant} data set, that itself is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} from 2020.}
\item{add_intrinsic_resistance}{\emph{(only useful when using a EUCAST guideline)} a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in \emph{Klebsiella} species. Determination is based on the \link{intrinsic_resistant} data set, that itself is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} (2020).}
\item{reference_data}{a \link{data.frame} to be used for interpretation, which defaults to the \link{rsi_translation} data set. Changing this argument allows for using own interpretation guidelines. This argument must contain a data set that is equal in structure to the \link{rsi_translation} data set (same column names and column types). Please note that the \code{guideline} argument will be ignored when \code{reference_data} is manually set.}

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man/dosage.Rd Normal file
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@ -0,0 +1,40 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{dosage}
\alias{dosage}
\title{Data set with treatment dosages as defined by EUCAST}
\format{
A \link{data.frame} with 135 observations and 9 variables:
\itemize{
\item \code{ab}\cr Antibiotic ID as used in this package (such as \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
\item \code{name}\cr Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO
\item \code{type}\cr Type of the dosage, either "high_dosage", "standard_dosage" or "uncomplicated_uti"
\item \code{dose}\cr Dose, such as "2 g" or "25 mg/kg"
\item \code{dose_times}\cr Dose, such as "2 g" or "25 mg/kg"
\item \code{administration}\cr Route of administration, either "im", "iv" or "oral"
\item \code{notes}\cr Additional dosage notes
\item \code{original_txt}\cr Original text in the PDF file of EUCAST
\item \code{eucast_version}\cr Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply
}
}
\usage{
dosage
}
\description{
EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with \code{\link[=eucast_dosage]{eucast_dosage()}}.
}
\details{
\href{https://www.eucast.org/clinical_breakpoints/}{'EUCAST Clinical Breakpoint Tables' v11.0} (2021) are based on the dosages in this data set.
}
\section{Reference data publicly available}{
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
\section{Read more on our website!}{
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
}
\keyword{datasets}

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man/eucast_rules.Rd
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@ -3,6 +3,7 @@
\name{eucast_rules}
\alias{eucast_rules}
\alias{EUCAST}
\alias{eucast_dosage}
\title{Apply EUCAST rules}
\source{
\itemize{
@ -12,6 +13,7 @@ Leclercq et al. \strong{EUCAST expert rules in antimicrobial susceptibility test
\item EUCAST Intrinsic Resistance and Unusual Phenotypes. Version 3.2, 2020. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf}{(link)}
\item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_9.0_Breakpoint_Tables.xlsx}{(link)}
\item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 10.0, 2020. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_10.0_Breakpoint_Tables.xlsx}{(link)}
\item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 11.0, 2021. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_11.0_Breakpoint_Tables.xlsx}{(link)}
}
}
\usage{
@ -26,6 +28,8 @@ eucast_rules(
ampc_cephalosporin_resistance = NA,
...
)
eucast_dosage(ab, administration = "iv", version_breakpoints = 11)
}
\arguments{
\item{x}{data with antibiotic columns, such as \code{amox}, \code{AMX} and \code{AMC}}
@ -38,19 +42,23 @@ eucast_rules(
\item{verbose}{a \link{logical} to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time.}
\item{version_breakpoints}{the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: 10.0.}
\item{version_breakpoints}{the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: 11.0, 10.0.}
\item{version_expertrules}{the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Currently supported: 3.1, 3.2.}
\item{ampc_cephalosporin_resistance}{a character value that should be applied for AmpC de-repressed cephalosporin-resistant mutants, defaults to \code{NA}. Currently only works when \code{version_expertrules} is \code{3.2}; '\emph{EUCAST Expert Rules v3.2 on Enterobacterales}' states that susceptible (S) results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these agents. A value of \code{NA} for this argument will remove results for these agents, while e.g. a value of \code{"R"} will make the results for these agents resistant. Use \code{NULL} to not alter the results for AmpC de-repressed cephalosporin-resistant mutants. \cr For \emph{EUCAST Expert Rules} v3.2, this rule applies to: \emph{Enterobacter, Klebsiella aerogenes, Citrobacter braakii, freundii, gillenii, murliniae, rodenticum, sedlakii, werkmanii, youngae, Hafnia alvei, Serratia, Morganella morganii, Providencia}.}
\item{...}{column name of an antibiotic, please see section \emph{Antibiotics} below}
\item{ab}{any (vector of) text that can be coerced to a valid antibiotic code with \code{\link[=as.ab]{as.ab()}}}
\item{administration}{route of administration, either "im", "iv" or "oral"}
}
\value{
The input of \code{x}, possibly with edited values of antibiotics. Or, if \code{verbose = TRUE}, a \link{data.frame} with all original and new values of the affected bug-drug combinations.
}
\description{
Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{https://eucast.org}), see \emph{Source}.
Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{https://eucast.org}), see \emph{Source}. Use \code{\link[=eucast_dosage]{eucast_dosage()}} to get advised dosages of a certain bug-drug combination, which is based on the \link{dosage} data set.
To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see Details.
}
@ -140,4 +148,6 @@ b
# containing all details about the transformations:
c <- eucast_rules(a, verbose = TRUE)
}
eucast_dosage(c("tobra", "genta", "cipro"), "iv")
}

3
man/filter_ab_class.Rd
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@ -104,10 +104,11 @@ if (require("dplyr")) {
filter_aminoglycosides("R", "all") \%>\%
filter_fluoroquinolones("R", "all")
# with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:
# with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal:
# (though the row names on the first are more correct)
example_isolates \%>\% filter_carbapenems("R", "all")
example_isolates \%>\% filter(across(carbapenems(), ~. == "R"))
example_isolates \%>\% filter(across(carbapenems(), function(x) x == "R"))
}
}
}

2
man/first_isolate.Rd
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@ -50,7 +50,7 @@ filter_first_weighted_isolate(
)
}
\arguments{
\item{x}{a \link{data.frame} containing isolates. Can be left blank when used inside \code{dplyr} verbs, such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}.}
\item{x}{a \link{data.frame} containing isolates. Can be left blank for automatic determination.}
\item{col_date}{column name of the result date (or date that is was received on the lab), defaults to the first column with a date class}

2
man/intrinsic_resistant.Rd
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@ -20,7 +20,7 @@ Data set containing defined intrinsic resistance by EUCAST of all bug-drug combi
\details{
The repository of this \code{AMR} package contains a file comprising this exact data set: \url{https://github.com/msberends/AMR/blob/master/data-raw/intrinsic_resistant.txt}. This file \strong{allows for machine reading EUCAST guidelines about intrinsic resistance}, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically.
This data set is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} from 2020.
This data set is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} (2020).
}
\section{Reference data publicly available}{

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man/isolate_identifier.Rd Normal file
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@ -0,0 +1,39 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/isolate_identifier.R
\name{isolate_identifier}
\alias{isolate_identifier}
\title{Create identifier of an isolate}
\usage{
isolate_identifier(x, col_mo = NULL, cols_ab = NULL)
}
\arguments{
\item{x}{data with antibiotic columns, such as \code{amox}, \code{AMX} and \code{AMC}}
\item{col_mo}{column name of the IDs of the microorganisms (see \code{\link[=as.mo]{as.mo()}}), defaults to the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
\item{cols_ab}{a character vector of column names of \code{x}, or (a combination with) an \href{[ab_class()]}{antibiotic selector function}, such as \code{\link[=carbapenems]{carbapenems()}} and \code{\link[=aminoglysides]{aminoglysides()}}}
}
\description{
This function will paste the microorganism code with all antimicrobial results into one string for each row in a data set. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available.
}
\section{Maturing lifecycle}{
\if{html}{\figure{lifecycle_maturing.svg}{options: style=margin-bottom:5px} \cr}
The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome \href{https://github.com/msberends/AMR/issues}{to suggest changes at our repository} or \link[=AMR]{write us an email (see section 'Contact Us')}.
}
\section{Read more on our website!}{
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
}
\examples{
# automatic selection of microorganism and antibiotics (i.e., all <rsi> columns, see ?as.rsi)
x <- isolate_identifier(example_isolates)
# ignore microorganism codes, only use antimicrobial results
x <- isolate_identifier(example_isolates, col_mo = FALSE, cols_ab = c("AMX", "TZP", "GEN", "TOB"))
# select antibiotics from certain antibiotic classes
x <- isolate_identifier(example_isolates, cols_ab = c(carbapenems(), aminoglycosides()))
}

2
man/mdro.Rd
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@ -40,7 +40,7 @@ mdr_cmi2012(x, guideline = "CMI2012", ...)
eucast_exceptional_phenotypes(x, guideline = "EUCAST", ...)
}
\arguments{
\item{x}{a \link{data.frame} with antibiotics columns, like \code{AMX} or \code{amox}. Can be left blank when used inside \code{dplyr} verbs, such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}.}
\item{x}{a \link{data.frame} with antibiotics columns, like \code{AMX} or \code{amox}. Can be left blank for automatic determination.}
\item{guideline}{a specific guideline to follow. When left empty, the publication by Magiorakos \emph{et al.} (2012, Clinical Microbiology and Infection) will be followed, please see \emph{Details}.}

9
man/microorganisms.Rd
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@ -32,7 +32,12 @@ microorganisms
A data set containing the microbial taxonomy of six kingdoms from the Catalogue of Life. MO codes can be looked up using \code{\link[=as.mo]{as.mo()}}.
}
\details{
Manually added were:
Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.
For example, \emph{Staphylococcus pettenkoferi} was newly named in Diagnostic Microbiology and Infectious Disease in 2002 (PMID 12106949), but it was not before 2007 that a publication in IJSEM followed (PMID 17625191). Consequently, the AMR package returns 2007 for \code{mo_year("S. pettenkoferi")}.
\subsection{Manually additions}{
For convenience, some entries were added manually:
\itemize{
\item 11 entries of \emph{Streptococcus} (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri)
\item 2 entries of \emph{Staphylococcus} (coagulase-negative (CoNS) and coagulase-positive (CoPS))
@ -43,6 +48,8 @@ Manually added were:
\item 6 families under the Enterobacterales order, according to Adeolu \emph{et al.} (2016, PMID 27620848), that are not (yet) in the Catalogue of Life
\item 7,411 species from the DSMZ (Deutsche Sammlung von Mikroorganismen und Zellkulturen) since the DSMZ contain the latest taxonomic information based on recent publications
}
}
\subsection{Direct download}{
This data set is available as 'flat file' for use even without \R - you can find the file here:

4
man/microorganisms.codes.Rd
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@ -3,9 +3,9 @@
\docType{data}
\name{microorganisms.codes}
\alias{microorganisms.codes}
\title{Data set with 5,583 common microorganism codes}
\title{Data set with 5,580 common microorganism codes}
\format{
A \link{data.frame} with 5,583 observations and 2 variables:
A \link{data.frame} with 5,580 observations and 2 variables:
\itemize{
\item \code{code}\cr Commonly used code of a microorganism
\item \code{mo}\cr ID of the microorganism in the \link{microorganisms} data set

24
man/mo_matching_score.Rd
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@ -18,16 +18,16 @@ This algorithm is used by \code{\link[=as.mo]{as.mo()}} and all the \code{\link[
With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}
\ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300px" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
where:
\itemize{
\item \eqn{x} is the user input;
\item \eqn{n} is a taxonomic name (genus, species, and subspecies);
\item \eqn{l_n}{l_n} is the length of \eqn{n};
\item lev is the \href{https://en.wikipedia.org/wiki/Levenshtein_distance}{Levenshtein distance function}, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};
\item \eqn{p_n}{p_n} is the human pathogenic prevalence group of \eqn{n}, as described below;
\item \eqn{k_n}{p_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
\item \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
\item \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
\item \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
\item \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;}}{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};}
\item \ifelse{html}{\out{<i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
\item \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
}
The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella},\\\emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium},\emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
@ -43,6 +43,16 @@ The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stabl
If the unlying code needs breaking changes, they will occur gradually. For example, a argument will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
}
\section{Reference data publicly available}{
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
}
\section{Read more on our website!}{
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
}
\examples{
as.mo("E. coli")
mo_uncertainties()

25
man/mo_property.Rd
View File

@ -18,6 +18,7 @@
\alias{mo_gramstain}
\alias{mo_is_gram_negative}
\alias{mo_is_gram_positive}
\alias{mo_is_yeast}
\alias{mo_is_intrinsic_resistant}
\alias{mo_snomed}
\alias{mo_ref}
@ -62,6 +63,8 @@ mo_is_gram_negative(x, language = get_locale(), ...)
mo_is_gram_positive(x, language = get_locale(), ...)
mo_is_yeast(x, language = get_locale(), ...)
mo_is_intrinsic_resistant(x, ab, language = get_locale(), ...)
mo_snomed(x, language = get_locale(), ...)
@ -85,7 +88,7 @@ mo_url(x, open = FALSE, language = get_locale(), ...)
mo_property(x, property = "fullname", language = get_locale(), ...)
}
\arguments{
\item{x}{any character (vector) that can be coerced to a valid microorganism code with \code{\link[=as.mo]{as.mo()}}. Can be left blank for auto-guessing the column containing microorganism codes when used inside \code{dplyr} verbs, such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}, please see \emph{Examples}.}
\item{x}{any character (vector) that can be coerced to a valid microorganism code with \code{\link[=as.mo]{as.mo()}}. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, please see \emph{Examples}.}
\item{language}{language of the returned text, defaults to system language (see \code{\link[=get_locale]{get_locale()}}) and can be overwritten by setting the option \code{AMR_locale}, e.g. \code{options(AMR_locale = "de")}, see \link{translate}. Also used to translate text like "no growth". Use \code{language = NULL} or \code{language = ""} to prevent translation.}
@ -123,7 +126,9 @@ Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and so
The Gram stain - \code{\link[=mo_gramstain]{mo_gramstain()}} - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, \href{https://pubmed.ncbi.nlm.nih.gov/11837318}{PMID 11837318}), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value \code{NA}. Functions \code{\link[=mo_is_gram_negative]{mo_is_gram_negative()}} and \code{\link[=mo_is_gram_positive]{mo_is_gram_positive()}} always return \code{TRUE} or \code{FALSE} (except when the input is \code{NA} or the MO code is \code{UNKNOWN}), thus always return \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
Intrinsic resistance - \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} - will be determined based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} from 2020. The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} can be vectorised over arguments \code{x} (input for microorganisms) and over \code{ab} (input for antibiotics).
Determination of yeasts - \code{\link[=mo_is_yeast]{mo_is_yeast()}} - will be based on the taxonomic phylum, class and order. Budding yeasts are true fungi of the phylum Ascomycetes, class Saccharomycetes (also called Hemiascomycetes). The true yeasts are separated into one main order Saccharomycetales. For all microorganisms that are in one of those two groups, the function will return \code{TRUE}. It returns \code{FALSE} for all other taxonomic entries.
Intrinsic resistance - \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} - will be determined based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} (2020). The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} can be vectorised over arguments \code{x} (input for microorganisms) and over \code{ab} (input for antibiotics).
All output will be \link{translate}d where possible.
@ -141,16 +146,16 @@ If the unlying code needs breaking changes, they will occur gradually. For examp
With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}
\ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300px" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
where:
\itemize{
\item \eqn{x} is the user input;
\item \eqn{n} is a taxonomic name (genus, species, and subspecies);
\item \eqn{l_n}{l_n} is the length of \eqn{n};
\item lev is the \href{https://en.wikipedia.org/wiki/Levenshtein_distance}{Levenshtein distance function}, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};
\item \eqn{p_n}{p_n} is the human pathogenic prevalence group of \eqn{n}, as described below;
\item \eqn{k_n}{p_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
\item \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
\item \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
\item \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
\item \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a>, which counts any insertion, deletion and substitution as 1 that is needed to change <i>x</i> into <i>n</i>;}}{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};}
\item \ifelse{html}{\out{<i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
\item \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
}
The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella},\\\emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium},\emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
@ -268,6 +273,8 @@ mo_fullname("S. pyogenes",
# other --------------------------------------------------------------------
mo_is_yeast(c("Candida", "E. coli")) # TRUE, FALSE
# gram stains and intrinsic resistance can also be used as a filter in dplyr verbs
if (require("dplyr")) {
example_isolates \%>\%

2
man/resistance_predict.Rd
View File

@ -47,7 +47,7 @@ ggplot_rsi_predict(
)
}
\arguments{
\item{x}{a \link{data.frame} containing isolates. Can be left blank when used inside \code{dplyr} verbs, such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}.}
\item{x}{a \link{data.frame} containing isolates. Can be left blank for automatic determination.}
\item{col_ab}{column name of \code{x} containing antimicrobial interpretations (\code{"R"}, \code{"I"} and \code{"S"})}