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N for only 1 AB in

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dr. M.S. (Matthijs) Berends 2023-02-22 16:26:13 +01:00
parent 551aaf6517
commit a84101db08
4 changed files with 35 additions and 30 deletions
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2
DESCRIPTION
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@ -1,5 +1,5 @@
Package: AMR
Version: 1.8.2.9140
Version: 1.8.2.9141
Date: 2023-02-22
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)

2
NEWS.md
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@ -1,4 +1,4 @@
# AMR 1.8.2.9140
# AMR 1.8.2.9141
*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*

36
R/antibiogram.R
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@ -188,12 +188,11 @@
#' # with a custom language, though this will be determined automatically
#' # (i.e., this table will be in Spanish on Spanish systems)
#' antibiogram(ex1,
#' antibiotics = aminoglycosides(),
#' ab_transform = "name",
#' syndromic_group = ifelse(ex1$ward == "ICU",
#' "UCI", "No UCI"
#' ),
#' language = "es"
#' antibiotics = aminoglycosides(),
#' ab_transform = "name",
#' syndromic_group = ifelse(ex1$ward == "ICU",
#' "UCI", "No UCI"),
#' language = "es"
#' )
#'
#'
@ -201,13 +200,13 @@
#'
#' # the data set could contain a filter for e.g. respiratory specimens/ICU
#' 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"
#' )
#' 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"
#' )
#' )
#'
#' # Print the output for R Markdown / Quarto -----------------------------
@ -488,8 +487,15 @@ antibiogram <- function(x,
count_group <- n_per_mo$count[match(new_df[[1]], n_per_mo$mo)]
edit_col <- 1
}
new_df[[edit_col]] <- paste0(new_df[[edit_col]], " (", count_group, ")")
colnames(new_df)[edit_col] <- paste(colnames(new_df)[edit_col], "(N min-max)")
if (NCOL(new_df) == edit_col + 1) {
# only 1 antibiotic
new_df[[edit_col]] <- paste0(new_df[[edit_col]], " (", unlist(lapply(strsplit(count_group, "-"), function(x) x[1])), ")")
colnames(new_df)[edit_col] <- paste(colnames(new_df)[edit_col], "(N)")
} else {
# more than 1 antibiotic
new_df[[edit_col]] <- paste0(new_df[[edit_col]], " (", count_group, ")")
colnames(new_df)[edit_col] <- paste(colnames(new_df)[edit_col], "(N min-max)")
}
}
out <- as_original_data_class(new_df, class(x), extra_class = "antibiogram")

25
man/antibiogram.Rd
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@ -217,12 +217,11 @@ ex1 <- example_isolates[which(mo_genus() == "Escherichia"), ]
# with a custom language, though this will be determined automatically
# (i.e., this table will be in Spanish on Spanish systems)
antibiogram(ex1,
antibiotics = aminoglycosides(),
ab_transform = "name",
syndromic_group = ifelse(ex1$ward == "ICU",
"UCI", "No UCI"
),
language = "es"
antibiotics = aminoglycosides(),
ab_transform = "name",
syndromic_group = ifelse(ex1$ward == "ICU",
"UCI", "No UCI"),
language = "es"
)
@ -230,13 +229,13 @@ antibiogram(ex1,
# the data set could contain a filter for e.g. respiratory specimens/ICU
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"
)
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"
)
)
# Print the output for R Markdown / Quarto -----------------------------