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@ -1,9 +1,9 @@
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/ab_selectors.R
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\name{antibiotic_class_selectors}
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\alias{antibiotic_class_selectors}
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\alias{ab_class}
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\alias{ab_selector}
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% Please edit documentation in R/amr_selectors.R
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\name{antimicrobial_class_selectors}
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\alias{antimicrobial_class_selectors}
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\alias{amr_class}
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\alias{amr_selector}
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\alias{aminoglycosides}
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\alias{aminopenicillins}
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\alias{antifungals}
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@ -36,73 +36,110 @@
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\alias{administrable_per_os}
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\alias{administrable_iv}
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\alias{not_intrinsic_resistant}
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\title{Antibiotic Selectors}
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\title{Antimicrobial Selectors}
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\usage{
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ab_class(ab_class, only_sir_columns = FALSE, only_treatable = TRUE, ...)
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amr_class(
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amr_class,
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only_sir_columns = FALSE,
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only_treatable = TRUE,
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return_all = TRUE,
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...
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)
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ab_selector(filter, only_sir_columns = FALSE, only_treatable = TRUE, ...)
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amr_selector(
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filter,
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only_sir_columns = FALSE,
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only_treatable = TRUE,
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return_all = TRUE,
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...
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)
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aminoglycosides(only_sir_columns = FALSE, only_treatable = TRUE, ...)
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aminoglycosides(
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only_sir_columns = FALSE,
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only_treatable = TRUE,
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return_all = TRUE,
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...
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)
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aminopenicillins(only_sir_columns = FALSE, ...)
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aminopenicillins(only_sir_columns = FALSE, return_all = TRUE, ...)
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antifungals(only_sir_columns = FALSE, ...)
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antifungals(only_sir_columns = FALSE, return_all = TRUE, ...)
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antimycobacterials(only_sir_columns = FALSE, ...)
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antimycobacterials(only_sir_columns = FALSE, return_all = TRUE, ...)
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betalactams(only_sir_columns = FALSE, only_treatable = TRUE, ...)
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betalactams(
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only_sir_columns = FALSE,
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only_treatable = TRUE,
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return_all = TRUE,
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...
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)
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betalactams_with_inhibitor(only_sir_columns = FALSE, ...)
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betalactams_with_inhibitor(only_sir_columns = FALSE, return_all = TRUE, ...)
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carbapenems(only_sir_columns = FALSE, only_treatable = TRUE, ...)
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carbapenems(
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only_sir_columns = FALSE,
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only_treatable = TRUE,
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return_all = TRUE,
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...
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)
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cephalosporins(only_sir_columns = FALSE, ...)
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cephalosporins(only_sir_columns = FALSE, return_all = TRUE, ...)
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cephalosporins_1st(only_sir_columns = FALSE, ...)
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cephalosporins_1st(only_sir_columns = FALSE, return_all = TRUE, ...)
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cephalosporins_2nd(only_sir_columns = FALSE, ...)
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cephalosporins_2nd(only_sir_columns = FALSE, return_all = TRUE, ...)
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cephalosporins_3rd(only_sir_columns = FALSE, ...)
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cephalosporins_3rd(only_sir_columns = FALSE, return_all = TRUE, ...)
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cephalosporins_4th(only_sir_columns = FALSE, ...)
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cephalosporins_4th(only_sir_columns = FALSE, return_all = TRUE, ...)
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cephalosporins_5th(only_sir_columns = FALSE, ...)
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cephalosporins_5th(only_sir_columns = FALSE, return_all = TRUE, ...)
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fluoroquinolones(only_sir_columns = FALSE, ...)
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fluoroquinolones(only_sir_columns = FALSE, return_all = TRUE, ...)
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glycopeptides(only_sir_columns = FALSE, ...)
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glycopeptides(only_sir_columns = FALSE, return_all = TRUE, ...)
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lincosamides(only_sir_columns = FALSE, only_treatable = TRUE, ...)
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lincosamides(
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only_sir_columns = FALSE,
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only_treatable = TRUE,
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return_all = TRUE,
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...
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)
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lipoglycopeptides(only_sir_columns = FALSE, ...)
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lipoglycopeptides(only_sir_columns = FALSE, return_all = TRUE, ...)
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macrolides(only_sir_columns = FALSE, ...)
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macrolides(only_sir_columns = FALSE, return_all = TRUE, ...)
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nitrofurans(only_sir_columns = FALSE, ...)
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nitrofurans(only_sir_columns = FALSE, return_all = TRUE, ...)
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oxazolidinones(only_sir_columns = FALSE, ...)
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oxazolidinones(only_sir_columns = FALSE, return_all = TRUE, ...)
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penicillins(only_sir_columns = FALSE, ...)
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penicillins(only_sir_columns = FALSE, return_all = TRUE, ...)
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phenicols(only_sir_columns = FALSE, ...)
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phenicols(only_sir_columns = FALSE, return_all = TRUE, ...)
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polymyxins(only_sir_columns = FALSE, only_treatable = TRUE, ...)
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polymyxins(
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only_sir_columns = FALSE,
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only_treatable = TRUE,
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return_all = TRUE,
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...
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)
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quinolones(only_sir_columns = FALSE, ...)
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quinolones(only_sir_columns = FALSE, return_all = TRUE, ...)
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rifamycins(only_sir_columns = FALSE, ...)
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rifamycins(only_sir_columns = FALSE, return_all = TRUE, ...)
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streptogramins(only_sir_columns = FALSE, ...)
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streptogramins(only_sir_columns = FALSE, return_all = TRUE, ...)
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tetracyclines(only_sir_columns = FALSE, ...)
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tetracyclines(only_sir_columns = FALSE, return_all = TRUE, ...)
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trimethoprims(only_sir_columns = FALSE, ...)
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trimethoprims(only_sir_columns = FALSE, return_all = TRUE, ...)
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ureidopenicillins(only_sir_columns = FALSE, ...)
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ureidopenicillins(only_sir_columns = FALSE, return_all = TRUE, ...)
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administrable_per_os(only_sir_columns = FALSE, ...)
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administrable_per_os(only_sir_columns = FALSE, return_all = TRUE, ...)
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administrable_iv(only_sir_columns = FALSE, ...)
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administrable_iv(only_sir_columns = FALSE, return_all = TRUE, ...)
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not_intrinsic_resistant(
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only_sir_columns = FALSE,
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@ -112,12 +149,14 @@ not_intrinsic_resistant(
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)
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}
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\arguments{
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\item{ab_class}{an antimicrobial class or a part of it, such as \code{"carba"} and \code{"carbapenems"}. The columns \code{group}, \code{atc_group1} and \code{atc_group2} of the \link{antibiotics} data set will be searched (case-insensitive) for this value.}
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\item{amr_class}{an antimicrobial class or a part of it, such as \code{"carba"} and \code{"carbapenems"}. The columns \code{group}, \code{atc_group1} and \code{atc_group2} of the \link{antibiotics} data set will be searched (case-insensitive) for this value.}
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\item{only_sir_columns}{a \link{logical} to indicate whether only columns of class \code{sir} must be selected (default is \code{FALSE}), see \code{\link[=as.sir]{as.sir()}}}
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\item{only_treatable}{a \link{logical} to indicate whether antimicrobial drugs should be excluded that are only for laboratory tests (default is \code{TRUE}), such as gentamicin-high (\code{GEH}) and imipenem/EDTA (\code{IPE})}
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\item{return_all}{a \link{logical} to indicate whether all matched columns must be returned (default is \code{TRUE}). With \code{FALSE}, only the first of each unique antimicrobial will be returned, e.g. if both columns \code{"genta"} and \code{"gentamicin"} exist in the data, only the first hit for gentamicin will be returned.}
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\item{...}{ignored, only in place to allow future extensions}
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\item{filter}{an \link{expression} to be evaluated in the \link{antibiotics} data set, such as \code{name \%like\% "trim"}}
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@ -127,27 +166,34 @@ not_intrinsic_resistant(
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\item{version_expertrules}{the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be "3.3", "3.2", or "3.1".}
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}
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\value{
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When used inside selecting or filtering, this returns a \link{character} vector of column names, with additional class \code{"ab_selector"}. When used individually, this returns an \link[=as.ab]{'ab' vector} with all possible antimicrobials that the function would be able to select or filter.
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When used inside selecting or filtering, this returns a \link{character} vector of column names, with additional class \code{"amr_selector"}. When used individually, this returns an \link[=as.ab]{'ab' vector} with all possible antimicrobials that the function would be able to select or filter.
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}
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\description{
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These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group (according to the \link{antibiotics} data set), without the need to define the columns or antibiotic abbreviations.
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These functions allow for filtering rows and selecting columns based on antimicrobial test results that are of a specific antimicrobial class or group, without the need to define the columns or antimicrobial abbreviations.
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In short, if you have a column name that resembles an antimicrobial drug, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "kefzol", "CZO" and "J01DB04" will all be picked up by \code{\link[=cephalosporins]{cephalosporins()}}.
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In short, if you have a column name that resembles an antimicrobial drug, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "kefzol", "CZO" and "J01DB04" will all be picked up using:
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\if{html}{\out{<div class="sourceCode r">}}\preformatted{library(dplyr)
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my_data_with_all_these_columns \%>\%
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select(cephalosporins())
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}\if{html}{\out{</div>}}
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}
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\details{
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These functions can be used in data set calls for selecting columns and filtering rows. They work with base \R, the Tidyverse, and \code{data.table}. They are heavily inspired by the \link[tidyselect:language]{Tidyverse selection helpers} such as \code{\link[tidyselect:everything]{everything()}}, but are not limited to \code{dplyr} verbs. Nonetheless, they are very convenient to use with \code{dplyr} functions such as \code{\link[dplyr:select]{select()}}, \code{\link[dplyr:filter]{filter()}} and \code{\link[dplyr:summarise]{summarise()}}, see \emph{Examples}.
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All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) according to the \link{antibiotics} data set. This means that a selector such as \code{\link[=aminoglycosides]{aminoglycosides()}} will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
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All selectors can also be used in \code{tidymodels} packages such as \code{recipe} and \code{parsnip}. See for more info \href{https://msberends.github.io/AMR/articles/AMR_with_tidymodels.html}{our tutorial} on using these AMR functions for predictive modelling.
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The \code{\link[=ab_class]{ab_class()}} function can be used to filter/select on a manually defined antibiotic class. It searches for results in the \link{antibiotics} data set within the columns \code{group}, \code{atc_group1} and \code{atc_group2}.
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All columns in the data in which these functions are called will be searched for known antimicrobial names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) according to the \link{antibiotics} data set. This means that a selector such as \code{\link[=aminoglycosides]{aminoglycosides()}} will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
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The \code{\link[=ab_selector]{ab_selector()}} function can be used to internally filter the \link{antibiotics} data set on any results, see \emph{Examples}. It allows for filtering on a (part of) a certain name, and/or a group name or even a minimum of DDDs for oral treatment. This function yields the highest flexibility, but is also the least user-friendly, since it requires a hard-coded filter to set.
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The \code{\link[=amr_class]{amr_class()}} function can be used to filter/select on a manually defined antimicrobial class. It searches for results in the \link{antibiotics} data set within the columns \code{group}, \code{atc_group1} and \code{atc_group2}.
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The \code{\link[=administrable_per_os]{administrable_per_os()}} and \code{\link[=administrable_iv]{administrable_iv()}} functions also rely on the \link{antibiotics} data set - antibiotic columns will be matched where a DDD (defined daily dose) for resp. oral and IV treatment is available in the \link{antibiotics} data set.
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The \code{\link[=amr_selector]{amr_selector()}} function can be used to internally filter the \link{antibiotics} data set on any results, see \emph{Examples}. It allows for filtering on a (part of) a certain name, and/or a group name or even a minimum of DDDs for oral treatment. This function yields the highest flexibility, but is also the least user-friendly, since it requires a hard-coded filter to set.
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The \code{\link[=not_intrinsic_resistant]{not_intrinsic_resistant()}} function can be used to only select antibiotic columns that pose no intrinsic resistance for the microorganisms in the data set. For example, if a data set contains only microorganism codes or names of \emph{E. coli} and \emph{K. pneumoniae} and contains a column "vancomycin", this column will be removed (or rather, unselected) using this function. It currently applies \href{https://www.eucast.org/expert_rules_and_expected_phenotypes}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021) to determine intrinsic resistance, using the \code{\link[=eucast_rules]{eucast_rules()}} function internally. Because of this determination, this function is quite slow in terms of performance.
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The \code{\link[=administrable_per_os]{administrable_per_os()}} and \code{\link[=administrable_iv]{administrable_iv()}} functions also rely on the \link{antibiotics} data set - antimicrobials will be matched where a DDD (defined daily dose) for resp. oral and IV treatment is available in the \link{antibiotics} data set.
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The \code{\link[=not_intrinsic_resistant]{not_intrinsic_resistant()}} function can be used to only select antimicrobials that pose no intrinsic resistance for the microorganisms in the data set. For example, if a data set contains only microorganism codes or names of \emph{E. coli} and \emph{K. pneumoniae} and contains a column "vancomycin", this column will be removed (or rather, unselected) using this function. It currently applies \href{https://www.eucast.org/expert_rules_and_expected_phenotypes}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021) to determine intrinsic resistance, using the \code{\link[=eucast_rules]{eucast_rules()}} function internally. Because of this determination, this function is quite slow in terms of performance.
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}
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\section{Full list of supported (antibiotic) classes}{
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\section{Full list of supported (antimicrobial) classes}{
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\itemize{
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\item \code{\link[=aminoglycosides]{aminoglycosides()}} can select: \cr amikacin (AMK), amikacin/fosfomycin (AKF), apramycin (APR), arbekacin (ARB), astromicin (AST), bekanamycin (BEK), dibekacin (DKB), framycetin (FRM), gentamicin (GEN), gentamicin-high (GEH), habekacin (HAB), hygromycin (HYG), isepamicin (ISE), kanamycin (KAN), kanamycin-high (KAH), kanamycin/cephalexin (KAC), micronomicin (MCR), neomycin (NEO), netilmicin (NET), pentisomicin (PIM), plazomicin (PLZ), propikacin (PKA), ribostamycin (RST), sisomicin (SIS), streptoduocin (STR), streptomycin (STR1), streptomycin-high (STH), tobramycin (TOB), and tobramycin-high (TOH)
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@ -215,7 +261,7 @@ example_isolates \%>\% select(mo, aminoglycosides())
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# e.g., for betalactams, but not the ones with an enzyme inhibitor:
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example_isolates \%>\% select(betalactams(), -betalactams_with_inhibitor())
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# select only antibiotic columns with DDDs for oral treatment
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# select only antimicrobials with DDDs for oral treatment
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example_isolates \%>\% select(administrable_per_os())
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# get AMR for all aminoglycosides e.g., per ward:
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@ -235,11 +281,11 @@ example_isolates \%>\%
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summarise_at(not_intrinsic_resistant(),
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resistance)
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# get susceptibility for antibiotics whose name contains "trim":
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# get susceptibility for antimicrobials whose name contains "trim":
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example_isolates \%>\%
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filter(first_isolate()) \%>\%
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group_by(ward) \%>\%
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summarise(across(ab_selector(name \%like\% "trim"), susceptibility))
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summarise(across(amr_selector(name \%like\% "trim"), susceptibility))
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# this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
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example_isolates \%>\%
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@ -266,7 +312,7 @@ example_isolates \%>\%
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# this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
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example_isolates \%>\%
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select(mo, ab_class("mycobact"))
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select(mo, amr_class("mycobact"))
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# get bug/drug combinations for only glycopeptides in Gram-positives:
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example_isolates \%>\%
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@ -296,7 +342,7 @@ example_isolates[, carbapenems()]
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# select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
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example_isolates[, c("mo", aminoglycosides())]
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# select only antibiotic columns with DDDs for oral treatment
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# select only antimicrobials with DDDs for oral treatment
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example_isolates[, administrable_per_os()]
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# filter using any() or all()
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@ -307,7 +353,7 @@ subset(example_isolates, any(carbapenems() == "R"))
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example_isolates[any(carbapenems()), ]
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example_isolates[all(carbapenems()), ]
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# filter with multiple antibiotic selectors using c()
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# filter with multiple antimicrobial selectors using c()
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example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]
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# filter + select in one go: get penicillins in carbapenem-resistant strains
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@ -320,10 +366,10 @@ example_isolates[any(carbapenems() == "R"), penicillins()]
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# and erythromycin is not a penicillin:
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example_isolates[, penicillins() & administrable_per_os()]
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# ab_selector() applies a filter in the `antibiotics` data set and is thus
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# very flexible. For instance, to select antibiotic columns with an oral DDD
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# amr_selector() applies a filter in the `antibiotics` data set and is thus
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# very flexible. For instance, to select antimicrobials with an oral DDD
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# of at least 1 gram:
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example_isolates[, ab_selector(oral_ddd > 1 & oral_units == "g")]
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example_isolates[, amr_selector(oral_ddd > 1 & oral_units == "g")]
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# data.table --------------------------------------------------------------
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