mirror of https://github.com/msberends/AMR.git
254 lines
12 KiB
R
254 lines
12 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/antibiogram.R
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\name{antibiogram}
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\alias{antibiogram}
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\alias{plot.antibiogram}
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\alias{autoplot.antibiogram}
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\alias{print.antibiogram}
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\title{Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA)}
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\source{
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\itemize{
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\item Klinker KP \emph{et al.} (2021). \strong{Antimicrobial stewardship and antibiograms: importance of moving beyond traditional antibiograms}. \emph{Therapeutic Advances in Infectious Disease}, May 5;8:20499361211011373; \doi{10.1177/20499361211011373}
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\item Barbieri E \emph{et al.} (2021). \strong{Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach} \emph{Antimicrobial Resistance & Infection Control} May 1;10(1):74; \doi{10.1186/s13756-021-00939-2}
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\item \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 5th Edition}, 2022, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
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}
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}
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\usage{
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antibiogram(
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x,
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antibiotics = where(is.sir),
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mo_transform = "shortname",
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ab_transform = NULL,
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syndromic_group = NULL,
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add_total_n = TRUE,
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only_all_tested = FALSE,
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digits = 0,
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col_mo = NULL,
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language = get_AMR_locale(),
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minimum = 30,
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combine_SI = TRUE,
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sep = " + "
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)
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\method{plot}{antibiogram}(x, ...)
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\method{autoplot}{antibiogram}(object, ...)
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\method{print}{antibiogram}(x, as_kable = !interactive(), ...)
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}
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\arguments{
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\item{x}{a \link{data.frame} containing at least a column with microorganisms and columns with antibiotic results (class 'sir', see \code{\link[=as.sir]{as.sir()}})}
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\item{antibiotics}{vector of column names, or (any combinations of) \link[=antibiotic_class_selectors]{antibiotic selectors} such as \code{\link[=aminoglycosides]{aminoglycosides()}} or \code{\link[=carbapenems]{carbapenems()}}. For combination antibiograms, this can also be column names separated with \code{"+"}, such as "TZP+TOB" given that the data set contains columns "TZP" and "TOB". See \emph{Examples}.}
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\item{mo_transform}{a character to transform microorganism input - must be "name", "shortname", "gramstain", or one of the column names of the \link{microorganisms} data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence" or "snomed". Can also be \code{NULL} to not transform the input.}
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\item{ab_transform}{a character to transform antibiotic input - must be one of the column names of the \link{antibiotics} data set: "ab", "cid", "name", "group", "atc", "atc_group1", "atc_group2", "abbreviations", "synonyms", "oral_ddd", "oral_units", "iv_ddd", "iv_units" or "loinc". Can also be \code{NULL} to not transform the input.}
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\item{syndromic_group}{a column name of \code{x}, or values calculated to split rows of \code{x}, e.g. by using \code{\link[=ifelse]{ifelse()}} or \code{\link[dplyr:case_when]{case_when()}}. See \emph{Examples}.}
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\item{add_total_n}{a \link{logical} to indicate whether total available numbers per pathogen should be added to the table (defaults to \code{TRUE}). This will add the lowest and highest number of available isolate per antibiotic (e.g, if for \emph{E. coli} 200 isolates are available for ciprofloxacin and 150 for amoxicillin, the returned number will be "150-200").}
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\item{only_all_tested}{(for combination antibiograms): a \link{logical} to indicate that isolates must be tested for all antibiotics, see \emph{Details}}
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\item{digits}{number of digits to use for rounding}
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\item{col_mo}{column name of the names or codes 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()}}.}
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\item{language}{language to translate text, which defaults to the system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}})}
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\item{minimum}{the minimum allowed number of available (tested) isolates. Any isolate count lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see \emph{Source}.}
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\item{combine_SI}{a \link{logical} to indicate whether all susceptibility should be determined by results of either S or I, instead of only S (defaults to \code{TRUE})}
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\item{sep}{a separating character for antibiotic columns in combination antibiograms}
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\item{...}{method extensions}
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\item{object}{an \code{\link[=antibiogram]{antibiogram()}} object}
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\item{as_kable}{a \link{logical} to indicate whether the printing should be done using \code{\link[knitr:kable]{knitr::kable()}} (which is the default in non-interactive sessions)}
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}
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\description{
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Generate an antibiogram, and communicate the results in plots or tables. These functions follow the logic of Klinker \emph{et al.} and Barbieri \emph{et al.} (see \emph{Source}), and allow reporting in e.g. R Markdown and Quarto as well.
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}
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\details{
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This function returns a table with values between 0 and 100 for \emph{susceptibility}, not resistance.
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\strong{Remember that you should filter your data to let it contain only first isolates!} This is needed to exclude duplicates and to reduce selection bias. Use \code{\link[=first_isolate]{first_isolate()}} to determine them in your data set with one of the four available algorithms.
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There are four antibiogram types, as proposed by Klinker \emph{et al.} (2021, \doi{10.1177/20499361211011373}), and they are all supported by \code{\link[=antibiogram]{antibiogram()}}:
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\enumerate{
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\item \strong{Traditional Antibiogram}
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Case example: Susceptibility of \emph{Pseudomonas aeruginosa} to piperacillin/tazobactam (TZP)
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Code example:
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\if{html}{\out{<div class="sourceCode r">}}\preformatted{antibiogram(your_data,
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antibiotics = "TZP")
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}\if{html}{\out{</div>}}
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\item \strong{Combination Antibiogram}
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Case example: Additional susceptibility of \emph{Pseudomonas aeruginosa} to TZP + tobramycin versus TZP alone
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Code example:
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\if{html}{\out{<div class="sourceCode r">}}\preformatted{antibiogram(your_data,
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antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
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}\if{html}{\out{</div>}}
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\item \strong{Syndromic Antibiogram}
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Case example: Susceptibility of \emph{Pseudomonas aeruginosa} to TZP among respiratory specimens (obtained among ICU patients only)
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Code example:
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\if{html}{\out{<div class="sourceCode r">}}\preformatted{antibiogram(your_data,
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antibiotics = penicillins(),
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syndromic_group = "ward")
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}\if{html}{\out{</div>}}
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\item \strong{Weighted-Incidence Syndromic Combination Antibiogram (WISCA)}
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Case example: Susceptibility of \emph{Pseudomonas aeruginosa} to TZP among respiratory specimens (obtained among ICU patients only) for male patients age >=65 years with heart failure
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Code example:
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\if{html}{\out{<div class="sourceCode r">}}\preformatted{library(dplyr)
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your_data \%>\%
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filter(ward == "ICU" & specimen_type == "Respiratory") \%>\%
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antibiogram(antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
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syndromic_group = ifelse(.$age >= 65 &
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.$gender == "Male" &
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.$condition == "Heart Disease",
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"Study Group", "Control Group"))
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}\if{html}{\out{</div>}}
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}
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All types of antibiograms can be generated with the functions as described on this page, and can be plotted (using \code{\link[ggplot2:autoplot]{ggplot2::autoplot()}} or base \R \code{\link[=plot]{plot()}}/\code{\link[=barplot]{barplot()}}) or printed into R Markdown / Quarto formats for reports. Use functions from specific 'table reporting' packages to transform the output of \code{\link[=antibiogram]{antibiogram()}} to your needs, e.g. \code{flextable::as_flextable()} or \code{gt::gt()}.
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Note that for combination antibiograms, it is important to realise that susceptibility can be calculated in two ways, which can be set with the \code{only_all_tested} argument (defaults to \code{FALSE}). See this example for two antibiotics, Drug A and Drug B, about how \code{\link[=antibiogram]{antibiogram()}} works to calculate the \%SI:
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\if{html}{\out{<div class="sourceCode">}}\preformatted{--------------------------------------------------------------------
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only_all_tested = FALSE only_all_tested = TRUE
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----------------------- -----------------------
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Drug A Drug B include as include as include as include as
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numerator denominator numerator denominator
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-------- -------- ---------- ----------- ---------- -----------
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S or I S or I X X X X
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R S or I X X X X
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<NA> S or I X X - -
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S or I R X X X X
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R R - X - X
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<NA> R - - - -
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S or I <NA> X X - -
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R <NA> - - - -
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<NA> <NA> - - - -
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--------------------------------------------------------------------
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}\if{html}{\out{</div>}}
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Printing the antibiogram in non-interactive sessions will be done by \code{\link[knitr:kable]{knitr::kable()}}, with support for \link[knitr:kable]{all their implemented formats}, such as "markdown". The knitr format will be automatically determined if printed inside a knitr document (LaTeX, HTML, etc.).
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}
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\examples{
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# example_isolates is a data set available in the AMR package.
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# run ?example_isolates for more info.
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example_isolates
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\donttest{
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# Traditional antibiogram ----------------------------------------------
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antibiogram(example_isolates,
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antibiotics = c(aminoglycosides(), carbapenems())
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)
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antibiogram(example_isolates,
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antibiotics = aminoglycosides(),
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ab_transform = "atc",
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mo_transform = "gramstain"
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)
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antibiogram(example_isolates,
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antibiotics = carbapenems(),
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ab_transform = "name",
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mo_transform = "name"
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)
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# Combined antibiogram -------------------------------------------------
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# combined antibiotics yield higher empiric coverage
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antibiogram(example_isolates,
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antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
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mo_transform = "gramstain"
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)
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antibiogram(example_isolates,
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antibiotics = c("TZP", "TZP+TOB"),
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mo_transform = "gramstain",
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ab_transform = "name",
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sep = " & "
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)
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# Syndromic antibiogram ------------------------------------------------
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# the data set could contain a filter for e.g. respiratory specimens
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antibiogram(example_isolates,
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antibiotics = c(aminoglycosides(), carbapenems()),
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syndromic_group = "ward"
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)
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# now define a data set with only E. coli
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ex1 <- example_isolates[which(mo_genus() == "Escherichia"), ]
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# with a custom language, though this will be determined automatically
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# (i.e., this table will be in Spanish on Spanish systems)
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antibiogram(ex1,
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antibiotics = aminoglycosides(),
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ab_transform = "name",
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syndromic_group = ifelse(ex1$ward == "ICU",
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"UCI", "No UCI"
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),
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language = "es"
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)
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# Weighted-incidence syndromic combination antibiogram (WISCA) ---------
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# the data set could contain a filter for e.g. respiratory specimens/ICU
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antibiogram(example_isolates,
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antibiotics = c("AMC", "AMC+CIP", "TZP", "TZP+TOB"),
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mo_transform = "gramstain",
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minimum = 10, # this should be >=30, but now just as example
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syndromic_group = ifelse(example_isolates$age >= 65 &
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example_isolates$gender == "M",
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"WISCA Group 1", "WISCA Group 2"
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)
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)
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# Generate plots with ggplot2 or base R --------------------------------
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ab1 <- antibiogram(example_isolates,
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antibiotics = c("AMC", "CIP", "TZP", "TZP+TOB"),
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mo_transform = "gramstain"
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)
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ab2 <- antibiogram(example_isolates,
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antibiotics = c("AMC", "CIP", "TZP", "TZP+TOB"),
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mo_transform = "gramstain",
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syndromic_group = "ward"
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)
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plot(ab1)
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if (requireNamespace("ggplot2")) {
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ggplot2::autoplot(ab1)
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}
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plot(ab2)
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if (requireNamespace("ggplot2")) {
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ggplot2::autoplot(ab2)
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}
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}
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}
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