mirror of https://github.com/msberends/AMR.git
knitr format
This commit is contained in:
parent
a84101db08
commit
e70f2cd32c
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@ -1,6 +1,6 @@
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Package: AMR
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Version: 1.8.2.9141
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Date: 2023-02-22
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Version: 1.8.2.9142
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Date: 2023-02-23
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Title: Antimicrobial Resistance Data Analysis
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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data analysis and to work with microbial and antimicrobial properties by
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@ -131,7 +131,6 @@ S3method(plot,resistance_predict)
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S3method(plot,rsi)
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S3method(plot,sir)
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S3method(print,ab)
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S3method(print,antibiogram)
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S3method(print,av)
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S3method(print,bug_drug_combinations)
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S3method(print,custom_eucast_rules)
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2
NEWS.md
2
NEWS.md
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@ -1,4 +1,4 @@
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# AMR 1.8.2.9141
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# AMR 1.8.2.9142
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*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
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@ -45,7 +45,7 @@
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#' @param sep a separating character for antibiotic columns in combination antibiograms
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#' @param info a [logical] to indicate info should be printed - the default is `TRUE` only in interactive mode
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#' @param object an [antibiogram()] object
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#' @param ... when used in [print()]: arguments passed on to [knitr::kable()] (otherwise, has no use)
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#' @param ... when used in [R Markdown or Quarto][knitr::kable()]: arguments passed on to [knitr::kable()] (otherwise, has no use)
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#' @details This function returns a table with values between 0 and 100 for *susceptibility*, not resistance.
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#'
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#' **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 [first_isolate()] to determine them in your data set with one of the four available algorithms.
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@ -103,7 +103,7 @@
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#' "Study Group", "Control Group"))
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#' ```
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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 [ggplot2::autoplot()] or base \R [plot()]/[barplot()]) or printed into R Markdown / Quarto formats for reports using `print()`. Use functions from specific 'table reporting' packages to transform the output of [antibiogram()] to your needs, e.g. `flextable::as_flextable()` or `gt::gt()`.
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#' All types of antibiograms can be generated with the functions as described on this page, and can be plotted (using [ggplot2::autoplot()] or base \R [plot()]/[barplot()]) or directly used into R Markdown / Quarto formats for reports (in the last case, [knitr::kable()] will be applied automatically). Use functions from specific 'table reporting' packages to transform the output of [antibiogram()] to your needs, e.g. `flextable::as_flextable()` or `gt::gt()`.
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#'
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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 `only_all_tested` argument (default is `FALSE`). See this example for two antibiotics, Drug A and Drug B, about how [antibiogram()] works to calculate the %SI:
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#'
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@ -215,8 +215,11 @@
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#' antibiotics = ureidopenicillins(),
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#' ab_transform = "name")
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#'
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#' # in an Rmd file, you would just need print(ureido), but to be explicit:
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#' print(ureido, as_kable = TRUE, format = "markdown", italicise = TRUE)
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#' # in an Rmd file, you would just need to return `ureido` in a chunk,
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#' # but to be explicit here:
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#' if (requireNamespace("knitr")) {
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#' knitr::knit_print(ureido)
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#' }
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#'
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#'
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#' # Generate plots with ggplot2 or base R --------------------------------
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@ -489,7 +492,7 @@ antibiogram <- function(x,
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}
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if (NCOL(new_df) == edit_col + 1) {
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# only 1 antibiotic
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new_df[[edit_col]] <- paste0(new_df[[edit_col]], " (", unlist(lapply(strsplit(count_group, "-"), function(x) x[1])), ")")
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new_df[[edit_col]] <- paste0(new_df[[edit_col]], " (", unlist(lapply(strsplit(x = count_group, split = "-", fixed = TRUE), function(x) x[1])), ")")
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colnames(new_df)[edit_col] <- paste(colnames(new_df)[edit_col], "(N)")
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} else {
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# more than 1 antibiotic
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@ -574,48 +577,40 @@ autoplot.antibiogram <- function(object, ...) {
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)
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}
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#' @export
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#' @param as_kable a [logical] to indicate whether the printing should be done using [knitr::kable()] (which is the default in non-interactive sessions)
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#' @param italicise (only when `as_kable = TRUE`) a [logical] to indicate whether the microorganism names in the output table should be made italic, using [italicise_taxonomy()]. This only works when the output format is markdown, such as in HTML output.
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#' @param na (only when `as_kable = TRUE`) character to use for showing `NA` values
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#' @details Printing the antibiogram in non-interactive sessions will be done by [knitr::kable()], with support for [all their implemented formats][knitr::kable()], such as "markdown". The knitr format will be automatically determined if printed inside a knitr document (LaTeX, HTML, etc.).
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# will be exported in zzz.R
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#' @param italicise a [logical] to indicate whether the microorganism names in the [knitr][knitr::kable()] table should be made italic, using [italicise_taxonomy()]. This only works when the output format is markdown, such as in HTML output.
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#' @param na character to use for showing `NA` values
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#' @rdname antibiogram
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print.antibiogram <- function(x, as_kable = !interactive(), italicise = TRUE, na = getOption("knitr.kable.NA", default = ""), ...) {
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meet_criteria(as_kable, allow_class = "logical", has_length = 1)
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knit_print.antibiogram <- function(x, italicise = TRUE, na = getOption("knitr.kable.NA", default = ""), ...) {
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stop_ifnot_installed("knitr")
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meet_criteria(italicise, allow_class = "logical", has_length = 1)
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meet_criteria(na, allow_class = "character", has_length = 1, allow_NA = TRUE)
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if (isTRUE(as_kable) &&
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pkg_is_available("knitr") &&
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# be sure not to run kable in pkgdown for our website generation
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!(missing(as_kable) && identical(Sys.getenv("IN_PKGDOWN"), "true"))) {
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old_option <- getOption("knitr.kable.NA")
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options(knitr.kable.NA = na)
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on.exit(options(knitr.kable.NA = old_option))
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out <- knitr::kable(x, ...)
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format <- attributes(out)$format
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if (!is.null(format) && format %in% c("markdown", "pipe")) {
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# try to italicise the output
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rows_with_txt <- which(out %like% "[a-z]")
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rows_without_txt <- setdiff(seq_len(length(out)), rows_with_txt)
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out[rows_with_txt] <- gsub("^[|]", "| ", out[rows_with_txt])
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# put hyphen directly after second character
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out[rows_without_txt] <- gsub("^[|](.)", "|\\1-", out[rows_without_txt])
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out_ita <- italicise_taxonomy(as.character(out), type = "markdown")
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if (length(unique(nchar(out_ita))) != 1) {
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# so there has been alterations done by italicise_taxonomy()
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to_fill <- which(nchar(out_ita) < max(nchar(out_ita)))
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out_ita[intersect(to_fill, rows_with_txt)] <- gsub("(^[|].*?)([|])(.*)", "\\1 \\2\\3", out_ita[intersect(to_fill, rows_with_txt)], perl = TRUE)
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out_ita[intersect(to_fill, rows_without_txt)] <- gsub("(^[|].*?)([|])(.*)", "\\1--\\2\\3", out_ita[intersect(to_fill, rows_without_txt)], perl = TRUE)
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}
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attributes(out_ita) <- attributes(out)
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out <- out_ita
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old_option <- getOption("knitr.kable.NA")
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options(knitr.kable.NA = na)
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on.exit(options(knitr.kable.NA = old_option))
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out <- knitr::kable(x, ..., output = FALSE)
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format <- attributes(out)$format
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if (isTRUE(italicise) &&
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!is.null(format) &&
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format %in% c("markdown", "pipe")) {
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# try to italicise the output
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rows_with_txt <- which(out %like% "[a-z]")
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rows_without_txt <- setdiff(seq_len(length(out)), rows_with_txt)
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out[rows_with_txt] <- gsub("^[|]", "| ", out[rows_with_txt])
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# put hyphen directly after second character
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out[rows_without_txt] <- gsub("^[|](.)", "|\\1-", out[rows_without_txt])
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out_ita <- italicise_taxonomy(as.character(out), type = "markdown")
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if (length(unique(nchar(out_ita))) != 1) {
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# so there has been alterations done by italicise_taxonomy()
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to_fill <- which(nchar(out_ita) < max(nchar(out_ita)))
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out_ita[intersect(to_fill, rows_with_txt)] <- gsub("(^[|].*?)([|])(.*)", "\\1 \\2\\3", out_ita[intersect(to_fill, rows_with_txt)], perl = TRUE)
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out_ita[intersect(to_fill, rows_without_txt)] <- gsub("(^[|].*?)([|])(.*)", "\\1--\\2\\3", out_ita[intersect(to_fill, rows_without_txt)], perl = TRUE)
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}
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out
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} else {
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# remove 'antibiogram' class and print with default method
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class(x) <- class(x)[class(x) != "antibiogram"]
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print(x, ...)
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attributes(out_ita) <- attributes(out)
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out <- out_ita
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}
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res <- paste(c("", "", out), collapse = "\n")
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knitr::asis_output(res)
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}
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56
R/plot.R
56
R/plot.R
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@ -146,18 +146,18 @@ plot.mic <- function(x,
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legend_txt <- character(0)
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legend_col <- character(0)
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if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) {
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legend_txt <- "Susceptible"
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legend_txt <- c(legend_txt, "(S) Susceptible")
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legend_col <- colours_SIR[1]
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}
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if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
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legend_txt <- c(legend_txt, plot_name_of_I(cols_sub$guideline))
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legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
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legend_col <- c(legend_col, colours_SIR[2])
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}
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if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
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legend_txt <- c(legend_txt, "Resistant")
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legend_txt <- c(legend_txt, "(R) Resistant")
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legend_col <- c(legend_col, colours_SIR[3])
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}
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legend("top",
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x.intersp = 0.5,
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legend = translate_into_language(legend_txt, language = language),
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df <- as.data.frame(x, stringsAsFactors = TRUE)
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colnames(df) <- c("mic", "count")
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df$cols <- cols_sub$cols
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df$cols[df$cols == colours_SIR[1]] <- "Susceptible"
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df$cols[df$cols == colours_SIR[2]] <- plot_name_of_I(cols_sub$guideline)
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df$cols[df$cols == colours_SIR[3]] <- "Resistant"
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df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
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df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
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df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
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df$cols <- factor(translate_into_language(df$cols, language = language),
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levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
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language = language
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),
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ordered = TRUE
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levels = translate_into_language(c("(S) Susceptible",
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paste("(I)", plot_name_of_I(cols_sub$guideline)),
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"(R) Resistant"),
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language = language
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),
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ordered = TRUE
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)
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p <- ggplot2::ggplot(df)
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if (any(colours_SIR %in% cols_sub$cols)) {
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vals <- c(
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"Susceptible" = colours_SIR[1],
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"Susceptible, incr. exp." = colours_SIR[2],
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"Intermediate" = colours_SIR[2],
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"Resistant" = colours_SIR[3]
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"(S) Susceptible" = colours_SIR[1],
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"(I) Susceptible, incr. exp." = colours_SIR[2],
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"(I) Intermediate" = colours_SIR[2],
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"(R) Resistant" = colours_SIR[3]
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)
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names(vals) <- translate_into_language(names(vals), language = language)
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p <- p +
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legend_txt <- character(0)
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legend_col <- character(0)
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if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
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legend_txt <- "Resistant"
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legend_txt <- "(R) Resistant"
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legend_col <- colours_SIR[3]
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}
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if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
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legend_txt <- c(legend_txt, plot_name_of_I(cols_sub$guideline))
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legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
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legend_col <- c(legend_col, colours_SIR[2])
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}
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if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) {
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legend_txt <- c(legend_txt, "Susceptible")
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legend_txt <- c(legend_txt, "(S) Susceptible")
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legend_col <- c(legend_col, colours_SIR[1])
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}
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legend("top",
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colnames(df) <- c("disk", "count")
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df$cols <- cols_sub$cols
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df$cols[df$cols == colours_SIR[1]] <- "Susceptible"
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df$cols[df$cols == colours_SIR[2]] <- plot_name_of_I(cols_sub$guideline)
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df$cols[df$cols == colours_SIR[3]] <- "Resistant"
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df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
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df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
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df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
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df$cols <- factor(translate_into_language(df$cols, language = language),
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levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
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levels = translate_into_language(c("(S) Susceptible",
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paste("(I)", plot_name_of_I(cols_sub$guideline)),
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"(R) Resistant"),
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language = language
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),
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ordered = TRUE
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if (any(colours_SIR %in% cols_sub$cols)) {
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vals <- c(
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"Susceptible" = colours_SIR[1],
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"Susceptible, incr. exp." = colours_SIR[2],
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"Intermediate" = colours_SIR[2],
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"Resistant" = colours_SIR[3]
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"(S) Susceptible" = colours_SIR[1],
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"(I) Susceptible, incr. exp." = colours_SIR[2],
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"(I) Intermediate" = colours_SIR[2],
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"(R) Resistant" = colours_SIR[3]
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)
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names(vals) <- translate_into_language(names(vals), language = language)
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p <- p +
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BIN
R/sysdata.rda
BIN
R/sysdata.rda
Binary file not shown.
2
R/zzz.R
2
R/zzz.R
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s3_register("ggplot2::fortify", "sir")
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s3_register("ggplot2::fortify", "mic")
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s3_register("ggplot2::fortify", "disk")
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# Support for knitr / R Markdown
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s3_register("knitr::knit_print", "antibiogram")
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# Support vctrs package for use in e.g. dplyr verbs
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# S3: ab_selector
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s3_register("vctrs::vec_ptype2", "character.ab_selector")
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### Traditional Antibiogram
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```{r trad}
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print(
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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 = c(aminoglycosides(), carbapenems()))
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```
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### Combined Antibiogram
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```{r comb}
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print(
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antibiogram(example_isolates,
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antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
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)
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antibiogram(example_isolates,
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antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
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```
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### Syndromic Antibiogram
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```{r synd}
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print(
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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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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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### Weighted-Incidence Syndromic Combination Antibiogram (WISCA)
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```{r wisca}
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print(
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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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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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@ -11,7 +11,7 @@
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<meta name="author" content="AMR package developers" />
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<meta name="date" content="2023-02-18" />
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<meta name="date" content="2023-02-23" />
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<title>Generating antibiograms with the AMR package</title>
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@ -299,18 +299,24 @@ overflow-y: auto;
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border: 1px solid #ddd;
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border-radius: 4px;
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}
|
||||
.tabset-dropdown > .nav-tabs > li.active:before, .tabset-dropdown > .nav-tabs.nav-tabs-open:before {
|
||||
content: "\e259";
|
||||
.tabset-dropdown > .nav-tabs > li.active:before {
|
||||
content: "";
|
||||
font-family: 'Glyphicons Halflings';
|
||||
display: inline-block;
|
||||
padding: 10px;
|
||||
border-right: 1px solid #ddd;
|
||||
}
|
||||
.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before {
|
||||
content: "\e258";
|
||||
font-family: 'Glyphicons Halflings';
|
||||
content: "";
|
||||
border: none;
|
||||
}
|
||||
.tabset-dropdown > .nav-tabs.nav-tabs-open:before {
|
||||
content: "";
|
||||
font-family: 'Glyphicons Halflings';
|
||||
display: inline-block;
|
||||
padding: 10px;
|
||||
border-right: 1px solid #ddd;
|
||||
}
|
||||
.tabset-dropdown > .nav-tabs > li.active {
|
||||
display: block;
|
||||
}
|
||||
|
|
@ -353,7 +359,7 @@ display: none;
|
|||
<h1 class="title toc-ignore">Generating antibiograms with the AMR
|
||||
package</h1>
|
||||
<h4 class="author">AMR package developers</h4>
|
||||
<h4 class="date">2023-02-18</h4>
|
||||
<h4 class="date">2023-02-23</h4>
|
||||
|
||||
</div>
|
||||
|
||||
|
|
@ -364,35 +370,34 @@ package</h1>
|
|||
looks like:</p>
|
||||
<pre class="r"><code>example_isolates</code></pre>
|
||||
<pre><code>## # A tibble: 2,000 × 46
|
||||
## date patient age gender ward mo PEN OXA FLC AMX
|
||||
## <date> <chr> <dbl> <chr> <chr> <mo> <sir> <sir> <sir> <sir>
|
||||
## 1 2002-01-02 A77334 65 F Clinical B_ESCHR_COLI R NA NA NA
|
||||
## 2 2002-01-03 A77334 65 F Clinical B_ESCHR_COLI R NA NA NA
|
||||
## 3 2002-01-07 067927 45 F ICU B_STPHY_EPDR R NA R NA
|
||||
## 4 2002-01-07 067927 45 F ICU B_STPHY_EPDR R NA R NA
|
||||
## 5 2002-01-13 067927 45 F ICU B_STPHY_EPDR R NA R NA
|
||||
## 6 2002-01-13 067927 45 F ICU B_STPHY_EPDR R NA R NA
|
||||
## 7 2002-01-14 462729 78 M Clinical B_STPHY_AURS R NA S R
|
||||
## 8 2002-01-14 462729 78 M Clinical B_STPHY_AURS R NA S R
|
||||
## 9 2002-01-16 067927 45 F ICU B_STPHY_EPDR R NA R NA
|
||||
## 10 2002-01-17 858515 79 F ICU B_STPHY_EPDR R NA S NA
|
||||
## # … with 1,990 more rows, and 36 more variables: AMC <sir>, AMP <sir>,
|
||||
## # TZP <sir>, CZO <sir>, FEP <sir>, CXM <sir>, FOX <sir>, CTX <sir>,
|
||||
## # CAZ <sir>, CRO <sir>, GEN <sir>, TOB <sir>, AMK <sir>, KAN <sir>,
|
||||
## # TMP <sir>, SXT <sir>, NIT <sir>, FOS <sir>, LNZ <sir>, CIP <sir>,
|
||||
## # MFX <sir>, VAN <sir>, TEC <sir>, TCY <sir>, TGC <sir>, DOX <sir>,
|
||||
## # ERY <sir>, CLI <sir>, AZM <sir>, IPM <sir>, MEM <sir>, MTR <sir>,
|
||||
## # CHL <sir>, COL <sir>, MUP <sir>, RIF <sir></code></pre>
|
||||
## date patient age gender ward mo PEN
|
||||
## <date> <chr> <dbl> <chr> <chr> <mo> <sir>
|
||||
## 1 2002-01-02 A77334 65 F Clini… B_ESCHR_COLI R
|
||||
## 2 2002-01-03 A77334 65 F Clini… B_ESCHR_COLI R
|
||||
## 3 2002-01-07 067927 45 F ICU B_STPHY_EPDR R
|
||||
## 4 2002-01-07 067927 45 F ICU B_STPHY_EPDR R
|
||||
## 5 2002-01-13 067927 45 F ICU B_STPHY_EPDR R
|
||||
## 6 2002-01-13 067927 45 F ICU B_STPHY_EPDR R
|
||||
## 7 2002-01-14 462729 78 M Clini… B_STPHY_AURS R
|
||||
## 8 2002-01-14 462729 78 M Clini… B_STPHY_AURS R
|
||||
## 9 2002-01-16 067927 45 F ICU B_STPHY_EPDR R
|
||||
## 10 2002-01-17 858515 79 F ICU B_STPHY_EPDR R
|
||||
## # … with 1,990 more rows, and 39 more variables: OXA <sir>,
|
||||
## # FLC <sir>, AMX <sir>, AMC <sir>, AMP <sir>, TZP <sir>,
|
||||
## # CZO <sir>, FEP <sir>, CXM <sir>, FOX <sir>, CTX <sir>,
|
||||
## # CAZ <sir>, CRO <sir>, GEN <sir>, TOB <sir>, AMK <sir>,
|
||||
## # KAN <sir>, TMP <sir>, SXT <sir>, NIT <sir>, FOS <sir>,
|
||||
## # LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>, TEC <sir>,
|
||||
## # TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, …
|
||||
## # ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names</code></pre>
|
||||
<div id="traditional-antibiogram" class="section level3">
|
||||
<h3>Traditional Antibiogram</h3>
|
||||
<pre class="r"><code>print(
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = c(aminoglycosides(), carbapenems()))
|
||||
)</code></pre>
|
||||
<pre class="r"><code>antibiogram(example_isolates,
|
||||
antibiotics = c(aminoglycosides(), carbapenems()))</code></pre>
|
||||
<table>
|
||||
<thead>
|
||||
<tr class="header">
|
||||
<th align="left">Pathogen (N min-max)</th>
|
||||
<th align="left">Pathogeen (N min-max)</th>
|
||||
<th align="right">AMK</th>
|
||||
<th align="right">GEN</th>
|
||||
<th align="right">IPM</th>
|
||||
|
|
@ -403,7 +408,7 @@ looks like:</p>
|
|||
</thead>
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="left">CoNS (43-309)</td>
|
||||
<td align="left">CNS (43-309)</td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">86</td>
|
||||
<td align="right">52</td>
|
||||
|
|
@ -416,7 +421,7 @@ looks like:</p>
|
|||
<td align="right">100</td>
|
||||
<td align="right">98</td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">97</td>
|
||||
</tr>
|
||||
|
|
@ -426,70 +431,70 @@ looks like:</p>
|
|||
<td align="right">0</td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">0</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left"><em>K. pneumoniae</em> (0-58)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">90</td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">90</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left"><em>P. aeruginosa</em> (17-30)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left"><em>P. mirabilis</em> (0-34)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">94</td>
|
||||
<td align="right">94</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right">94</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left"><em>S. aureus</em> (2-233)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">99</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right">98</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left"><em>S. epidermidis</em> (8-163)</td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">79</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">51</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left"><em>S. hominis</em> (3-80)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">92</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right">85</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left"><em>S. pneumoniae</em> (11-117)</td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">0</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
|
|
@ -497,14 +502,12 @@ looks like:</p>
|
|||
</div>
|
||||
<div id="combined-antibiogram" class="section level3">
|
||||
<h3>Combined Antibiogram</h3>
|
||||
<pre class="r"><code>print(
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
|
||||
)</code></pre>
|
||||
<pre class="r"><code>antibiogram(example_isolates,
|
||||
antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))</code></pre>
|
||||
<table>
|
||||
<thead>
|
||||
<tr class="header">
|
||||
<th align="left">Pathogen (N min-max)</th>
|
||||
<th align="left">Pathogeen (N min-max)</th>
|
||||
<th align="right">TZP</th>
|
||||
<th align="right">TZP + GEN</th>
|
||||
<th align="right">TZP + TOB</th>
|
||||
|
|
@ -512,10 +515,10 @@ looks like:</p>
|
|||
</thead>
|
||||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="left">CoNS (29-274)</td>
|
||||
<td align="left">CNS (29-274)</td>
|
||||
<td align="right">30</td>
|
||||
<td align="right">97</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left"><em>E. coli</em> (416-461)</td>
|
||||
|
|
@ -531,31 +534,31 @@ looks like:</p>
|
|||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left"><em>P. aeruginosa</em> (27-30)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">100</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left"><em>P. mirabilis</em> (27-34)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">100</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left"><em>S. aureus</em> (7-231)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">100</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left"><em>S. epidermidis</em> (5-128)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">100</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left"><em>S. hominis</em> (0-74)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">100</td>
|
||||
</tr>
|
||||
|
|
@ -570,26 +573,14 @@ looks like:</p>
|
|||
</div>
|
||||
<div id="syndromic-antibiogram" class="section level3">
|
||||
<h3>Syndromic Antibiogram</h3>
|
||||
<pre class="r"><code>print(
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = c(aminoglycosides(), carbapenems()),
|
||||
syndromic_group = "ward")
|
||||
)</code></pre>
|
||||
<pre class="r"><code>antibiogram(example_isolates,
|
||||
antibiotics = c(aminoglycosides(), carbapenems()),
|
||||
syndromic_group = "ward")</code></pre>
|
||||
<table>
|
||||
<colgroup>
|
||||
<col width="29%" />
|
||||
<col width="33%" />
|
||||
<col width="6%" />
|
||||
<col width="6%" />
|
||||
<col width="6%" />
|
||||
<col width="6%" />
|
||||
<col width="6%" />
|
||||
<col width="6%" />
|
||||
</colgroup>
|
||||
<thead>
|
||||
<tr class="header">
|
||||
<th align="left">Syndromic Group</th>
|
||||
<th align="left">Pathogen (N min-max)</th>
|
||||
<th align="left">Syndroomgroep</th>
|
||||
<th align="left">Pathogeen (N min-max)</th>
|
||||
<th align="right">AMK</th>
|
||||
<th align="right">GEN</th>
|
||||
<th align="right">IPM</th>
|
||||
|
|
@ -601,33 +592,33 @@ looks like:</p>
|
|||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="left">Clinical</td>
|
||||
<td align="left">CoNS (23-205)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="left">CNS (23-205)</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">89</td>
|
||||
<td align="right">57</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">57</td>
|
||||
<td align="right">26</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">ICU</td>
|
||||
<td align="left">CoNS (10-73)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="left">CNS (10-73)</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">79</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left">Outpatient</td>
|
||||
<td align="left">CoNS (3-31)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="left">CNS (3-31)</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">84</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">Clinical</td>
|
||||
|
|
@ -635,7 +626,7 @@ looks like:</p>
|
|||
<td align="right">100</td>
|
||||
<td align="right">98</td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">98</td>
|
||||
</tr>
|
||||
|
|
@ -645,78 +636,78 @@ looks like:</p>
|
|||
<td align="right">100</td>
|
||||
<td align="right">99</td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">96</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">Clinical</td>
|
||||
<td align="left">K. <em>pneumoniae</em> (0-51)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">92</td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">92</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left">Clinical</td>
|
||||
<td align="left">P. <em>mirabilis</em> (0-30)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">Clinical</td>
|
||||
<td align="left">S. <em>aureus</em> (2-150)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">99</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right">97</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left">ICU</td>
|
||||
<td align="left">S. <em>aureus</em> (0-66)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">100</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">Clinical</td>
|
||||
<td align="left">S. <em>epidermidis</em> (4-79)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">82</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right">55</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left">ICU</td>
|
||||
<td align="left">S. <em>epidermidis</em> (4-75)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">72</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right">41</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">Clinical</td>
|
||||
<td align="left">S. <em>hominis</em> (1-45)</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">96</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right"></td>
|
||||
<td align="right">94</td>
|
||||
</tr>
|
||||
<tr class="odd">
|
||||
|
|
@ -724,9 +715,9 @@ looks like:</p>
|
|||
<td align="left">S. <em>pneumoniae</em> (5-78)</td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">0</td>
|
||||
</tr>
|
||||
<tr class="even">
|
||||
|
|
@ -734,9 +725,9 @@ looks like:</p>
|
|||
<td align="left">S. <em>pneumoniae</em> (5-30)</td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">0</td>
|
||||
<td align="right">NA</td>
|
||||
<td align="right"></td>
|
||||
<td align="right">0</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
|
|
@ -744,19 +735,17 @@ looks like:</p>
|
|||
</div>
|
||||
<div id="weighted-incidence-syndromic-combination-antibiogram-wisca" class="section level3">
|
||||
<h3>Weighted-Incidence Syndromic Combination Antibiogram (WISCA)</h3>
|
||||
<pre class="r"><code>print(
|
||||
antibiogram(example_isolates,
|
||||
antibiotics = c("AMC", "AMC+CIP", "TZP", "TZP+TOB"),
|
||||
mo_transform = "gramstain",
|
||||
minimum = 10, # this should be >= 30, but now just as example
|
||||
syndromic_group = ifelse(example_isolates$age >= 65 &
|
||||
example_isolates$gender == "M",
|
||||
"WISCA Group 1", "WISCA Group 2"))
|
||||
)</code></pre>
|
||||
<table>
|
||||
<pre class="r"><code>antibiogram(example_isolates,
|
||||
antibiotics = c("AMC", "AMC+CIP", "TZP", "TZP+TOB"),
|
||||
mo_transform = "gramstain",
|
||||
minimum = 10, # this should be >= 30, but now just as example
|
||||
syndromic_group = ifelse(example_isolates$age >= 65 &
|
||||
example_isolates$gender == "M",
|
||||
"WISCA Group 1", "WISCA Group 2"))</code></pre>
|
||||
<table style="width:100%;">
|
||||
<colgroup>
|
||||
<col width="24%" />
|
||||
<col width="34%" />
|
||||
<col width="22%" />
|
||||
<col width="35%" />
|
||||
<col width="5%" />
|
||||
<col width="14%" />
|
||||
<col width="5%" />
|
||||
|
|
@ -764,8 +753,8 @@ looks like:</p>
|
|||
</colgroup>
|
||||
<thead>
|
||||
<tr class="header">
|
||||
<th align="left">Syndromic Group</th>
|
||||
<th align="left">Pathogen (N min-max)</th>
|
||||
<th align="left">Syndroomgroep</th>
|
||||
<th align="left">Pathogeen (N min-max)</th>
|
||||
<th align="right">AMC</th>
|
||||
<th align="right">AMC + CIP</th>
|
||||
<th align="right">TZP</th>
|
||||
|
|
@ -775,7 +764,7 @@ looks like:</p>
|
|||
<tbody>
|
||||
<tr class="odd">
|
||||
<td align="left">WISCA Group 1</td>
|
||||
<td align="left">Gram-negative (261-285)</td>
|
||||
<td align="left">Gram-negatief (261-285)</td>
|
||||
<td align="right">76</td>
|
||||
<td align="right">95</td>
|
||||
<td align="right">89</td>
|
||||
|
|
@ -783,7 +772,7 @@ looks like:</p>
|
|||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">WISCA Group 2</td>
|
||||
<td align="left">Gram-negative (380-442)</td>
|
||||
<td align="left">Gram-negatief (380-442)</td>
|
||||
<td align="right">76</td>
|
||||
<td align="right">98</td>
|
||||
<td align="right">88</td>
|
||||
|
|
@ -791,7 +780,7 @@ looks like:</p>
|
|||
</tr>
|
||||
<tr class="odd">
|
||||
<td align="left">WISCA Group 1</td>
|
||||
<td align="left">Gram-positive (123-406)</td>
|
||||
<td align="left">Gram-positief (123-406)</td>
|
||||
<td align="right">76</td>
|
||||
<td align="right">89</td>
|
||||
<td align="right">81</td>
|
||||
|
|
@ -799,7 +788,7 @@ looks like:</p>
|
|||
</tr>
|
||||
<tr class="even">
|
||||
<td align="left">WISCA Group 2</td>
|
||||
<td align="left">Gram-positive (222-732)</td>
|
||||
<td align="left">Gram-positief (222-732)</td>
|
||||
<td align="right">76</td>
|
||||
<td align="right">89</td>
|
||||
<td align="right">88</td>
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
\alias{antibiogram}
|
||||
\alias{plot.antibiogram}
|
||||
\alias{autoplot.antibiogram}
|
||||
\alias{print.antibiogram}
|
||||
\alias{knit_print.antibiogram}
|
||||
\title{Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA)}
|
||||
\source{
|
||||
\itemize{
|
||||
|
|
@ -35,9 +35,8 @@ antibiogram(
|
|||
|
||||
\method{autoplot}{antibiogram}(object, ...)
|
||||
|
||||
\method{print}{antibiogram}(
|
||||
knit_print.antibiogram(
|
||||
x,
|
||||
as_kable = !interactive(),
|
||||
italicise = TRUE,
|
||||
na = getOption("knitr.kable.NA", default = ""),
|
||||
...
|
||||
|
|
@ -72,15 +71,13 @@ antibiogram(
|
|||
|
||||
\item{info}{a \link{logical} to indicate info should be printed - the default is \code{TRUE} only in interactive mode}
|
||||
|
||||
\item{...}{when used in \code{\link[=print]{print()}}: arguments passed on to \code{\link[knitr:kable]{knitr::kable()}} (otherwise, has no use)}
|
||||
\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)}
|
||||
|
||||
\item{object}{an \code{\link[=antibiogram]{antibiogram()}} object}
|
||||
|
||||
\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)}
|
||||
\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()}}. This only works when the output format is markdown, such as in HTML output.}
|
||||
|
||||
\item{italicise}{(only when \code{as_kable = TRUE}) a \link{logical} to indicate whether the microorganism names in the output table should be made italic, using \code{\link[=italicise_taxonomy]{italicise_taxonomy()}}. This only works when the output format is markdown, such as in HTML output.}
|
||||
|
||||
\item{na}{(only when \code{as_kable = TRUE}) character to use for showing \code{NA} values}
|
||||
\item{na}{character to use for showing \code{NA} values}
|
||||
}
|
||||
\description{
|
||||
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.
|
||||
|
|
@ -137,7 +134,7 @@ your_data \%>\%
|
|||
}\if{html}{\out{</div>}}
|
||||
}
|
||||
|
||||
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 using \code{print()}. 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()}.
|
||||
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 directly used into R Markdown / Quarto formats for reports (in the last case, \code{\link[knitr:kable]{knitr::kable()}} will be applied automatically). 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()}.
|
||||
|
||||
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 (default is \code{FALSE}). See this example for two antibiotics, Drug A and Drug B, about how \code{\link[=antibiogram]{antibiogram()}} works to calculate the \%SI:
|
||||
|
||||
|
|
@ -158,8 +155,6 @@ Note that for combination antibiograms, it is important to realise that suscepti
|
|||
<NA> <NA> - - - -
|
||||
--------------------------------------------------------------------
|
||||
}\if{html}{\out{</div>}}
|
||||
|
||||
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.).
|
||||
}
|
||||
\examples{
|
||||
# example_isolates is a data set available in the AMR package.
|
||||
|
|
@ -244,8 +239,11 @@ ureido <- antibiogram(example_isolates,
|
|||
antibiotics = ureidopenicillins(),
|
||||
ab_transform = "name")
|
||||
|
||||
# in an Rmd file, you would just need print(ureido), but to be explicit:
|
||||
print(ureido, as_kable = TRUE, format = "markdown", italicise = TRUE)
|
||||
# in an Rmd file, you would just need to return `ureido` in a chunk,
|
||||
# but to be explicit here:
|
||||
if (requireNamespace("knitr")) {
|
||||
knitr::knit_print(ureido)
|
||||
}
|
||||
|
||||
|
||||
# Generate plots with ggplot2 or base R --------------------------------
|
||||
|
|
|
|||
Loading…
Reference in New Issue