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(v2.1.1.9190) antibiotics deprecation in antibiogram()
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@ -18,23 +18,23 @@
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}
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}
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\usage{
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antibiogram(x, antibiotics = where(is.sir), mo_transform = "shortname",
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antibiogram(x, antimicrobials = where(is.sir), mo_transform = "shortname",
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ab_transform = "name", syndromic_group = NULL, add_total_n = FALSE,
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only_all_tested = FALSE, digits = ifelse(wisca, 1, 0),
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formatting_type = getOption("AMR_antibiogram_formatting_type",
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ifelse(wisca, 14, 18)), col_mo = NULL, language = get_AMR_locale(),
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minimum = 30, combine_SI = TRUE, sep = " + ", wisca = FALSE,
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simulations = 1000, conf_interval = 0.95, interval_side = "two-tailed",
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info = interactive())
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info = interactive(), ...)
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wisca(x, antibiotics = where(is.sir), ab_transform = "name",
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wisca(x, antimicrobials = where(is.sir), ab_transform = "name",
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syndromic_group = NULL, add_total_n = FALSE, only_all_tested = FALSE,
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digits = 1,
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formatting_type = getOption("AMR_antibiogram_formatting_type", 14),
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col_mo = NULL, language = get_AMR_locale(), minimum = 30,
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combine_SI = TRUE, sep = " + ", simulations = 1000,
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conf_interval = 0.95, interval_side = "two-tailed",
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info = interactive())
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info = interactive(), ...)
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retrieve_wisca_parameters(wisca_model, ...)
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@ -48,7 +48,7 @@ retrieve_wisca_parameters(wisca_model, ...)
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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 antimicrobial results (class 'sir', see \code{\link[=as.sir]{as.sir()}})}
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\item{antibiotics}{vector of any antimicrobial name or code (will be evaluated with \code{\link[=as.ab]{as.ab()}}, column name of \code{x}, or (any combinations of) \link[=antimicrobial_selectors]{antimicrobial selectors} such as \code{\link[=aminoglycosides]{aminoglycosides()}} or \code{\link[=carbapenems]{carbapenems()}}. For combination antibiograms, this can also be set to values separated with \code{"+"}, such as \code{"TZP+TOB"} or \code{"cipro + genta"}, given that columns resembling such antimicrobials exist in \code{x}. See \emph{Examples}.}
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\item{antimicrobials}{vector of any antimicrobial name or code (will be evaluated with \code{\link[=as.ab]{as.ab()}}, column name of \code{x}, or (any combinations of) \link[=antimicrobial_selectors]{antimicrobial selectors} such as \code{\link[=aminoglycosides]{aminoglycosides()}} or \code{\link[=carbapenems]{carbapenems()}}. For combination antibiograms, this can also be set to values separated with \code{"+"}, such as \code{"TZP+TOB"} or \code{"cipro + genta"}, given that columns resembling such antimicrobials exist in \code{x}. See \emph{Examples}.}
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\item{mo_transform}{a character to transform microorganism input - must be \code{"name"}, \code{"shortname"} (default), \code{"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", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "mycobank", "mycobank_parent", "mycobank_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed". Can also be \code{NULL} to not transform the input or \code{NA} to consider all microorganisms 'unknown'.}
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@ -84,10 +84,10 @@ retrieve_wisca_parameters(wisca_model, ...)
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\item{info}{a \link{logical} to indicate info should be printed - the default is \code{TRUE} only in interactive mode}
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\item{wisca_model}{the outcome of \code{\link[=wisca]{wisca()}} or \code{\link[=antibiogram]{antibiogram(..., wisca = TRUE)}}}
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\item{...}{when used in \link[knitr:kable]{R Markdown or Quarto}: arguments passed on to \code{\link[knitr:kable]{knitr::kable()}} (otherwise, has no use)}
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\item{wisca_model}{the outcome of \code{\link[=wisca]{wisca()}} or \code{\link[=antibiogram]{antibiogram(..., wisca = TRUE)}}}
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\item{object}{an \code{\link[=antibiogram]{antibiogram()}} object}
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\item{italicise}{a \link{logical} to indicate whether the microorganism names in the \link[knitr:kable]{knitr} table should be made italic, using \code{\link[=italicise_taxonomy]{italicise_taxonomy()}}.}
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@ -153,7 +153,7 @@ Case example: Susceptibility of \emph{Pseudomonas aeruginosa} to piperacillin/ta
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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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antimicrobials = "TZP")
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}\if{html}{\out{</div>}}
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\item \strong{Combination Antibiogram}
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@ -162,7 +162,7 @@ Case example: Additional susceptibility of \emph{Pseudomonas aeruginosa} to 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 = c("TZP", "TZP+TOB", "TZP+GEN"))
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antimicrobials = 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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@ -171,7 +171,7 @@ Case example: Susceptibility of \emph{Pseudomonas aeruginosa} to TZP among respi
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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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antimicrobials = 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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@ -181,12 +181,12 @@ WISCA can be applied to any antibiogram, see the section \emph{Explaining WISCA}
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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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antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
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wisca = TRUE)
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# this is equal to:
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wisca(your_data,
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antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
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antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"))
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}\if{html}{\out{</div>}}
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WISCA uses a sophisticated Bayesian decision model to combine both local and pooled antimicrobial resistance data. This approach not only evaluates local patterns but can also draw on multi-centre datasets to improve regimen accuracy, even in low-incidence infections like paediatric bloodstream infections (BSIs).
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@ -202,7 +202,7 @@ 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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group_by(has_sepsis, is_neonate, sex) \%>\%
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wisca(antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
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wisca(antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"))
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}\if{html}{\out{</div>}}
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}
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@ -218,12 +218,12 @@ At admission, no pathogen information is available.
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\item Code example:
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\if{html}{\out{<div class="sourceCode r">}}\preformatted{antibiogram(your_data,
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antibiotics = selected_regimens,
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antimicrobials = selected_regimens,
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mo_transform = NA) # all pathogens set to `NA`
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# preferred: use WISCA
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wisca(your_data,
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antibiotics = selected_regimens)
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antimicrobials = selected_regimens)
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}\if{html}{\out{</div>}}
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}
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\item \strong{Refinement with Gram Stain Results}
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@ -234,7 +234,7 @@ When a blood culture becomes positive, the Gram stain provides an initial and cr
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\item Code example:
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\if{html}{\out{<div class="sourceCode r">}}\preformatted{antibiogram(your_data,
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antibiotics = selected_regimens,
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antimicrobials = selected_regimens,
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mo_transform = "gramstain") # all pathogens set to Gram-pos/Gram-neg
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}\if{html}{\out{</div>}}
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}
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@ -246,7 +246,7 @@ After cultivation of the pathogen, full pathogen identification allows precise t
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\item Code example:
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\if{html}{\out{<div class="sourceCode r">}}\preformatted{antibiogram(your_data,
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antibiotics = selected_regimens,
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antimicrobials = selected_regimens,
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mo_transform = "shortname") # all pathogens set to 'G. species', e.g., E. coli
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}\if{html}{\out{</div>}}
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}
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@ -337,17 +337,17 @@ example_isolates
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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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antimicrobials = c(aminoglycosides(), carbapenems())
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)
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antibiogram(example_isolates,
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antibiotics = aminoglycosides(),
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antimicrobials = 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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antimicrobials = carbapenems(),
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ab_transform = "name",
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mo_transform = "name"
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)
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@ -355,15 +355,15 @@ antibiogram(example_isolates,
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# Combined antibiogram -------------------------------------------------
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# combined antibiotics yield higher empiric coverage
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# combined antimicrobials 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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antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
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mo_transform = "gramstain"
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)
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# names of antibiotics do not need to resemble columns exactly:
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# names of antimicrobials do not need to resemble columns exactly:
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antibiogram(example_isolates,
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antibiotics = c("Cipro", "cipro + genta"),
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antimicrobials = c("Cipro", "cipro + genta"),
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mo_transform = "gramstain",
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ab_transform = "name",
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sep = " & "
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@ -374,7 +374,7 @@ antibiogram(example_isolates,
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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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antimicrobials = c(aminoglycosides(), carbapenems()),
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syndromic_group = "ward"
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)
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@ -384,7 +384,7 @@ 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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antimicrobials = 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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@ -397,7 +397,7 @@ antibiogram(ex1,
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# WISCA are not stratified by species, but rather on syndromes
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antibiogram(example_isolates,
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antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
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antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
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syndromic_group = "ward",
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wisca = TRUE
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)
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@ -406,7 +406,7 @@ antibiogram(example_isolates,
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# Print the output for R Markdown / Quarto -----------------------------
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ureido <- antibiogram(example_isolates,
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antibiotics = ureidopenicillins(),
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antimicrobials = ureidopenicillins(),
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syndromic_group = "ward",
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wisca = TRUE
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)
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@ -421,11 +421,11 @@ if (requireNamespace("knitr")) {
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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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antimicrobials = 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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antimicrobials = 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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