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(v0.9.0.9029) add uti to as.rsi()

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dr. M.S. (Matthijs) Berends
2020-02-20 13:19:23 +01:00
parent a5db82c2fb
commit c6184a0fb8
71 changed files with 1129 additions and 800 deletions
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65
man/as.rsi.Rd
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@ -12,11 +12,25 @@
\usage{
as.rsi(x, ...)
\method{as.rsi}{mic}(x, mo, ab, guideline = "EUCAST", ...)
\method{as.rsi}{mic}(
x,
mo,
ab = deparse(substitute(x)),
guideline = "EUCAST",
uti = FALSE,
...
)
\method{as.rsi}{disk}(x, mo, ab, guideline = "EUCAST", ...)
\method{as.rsi}{disk}(
x,
mo,
ab = deparse(substitute(x)),
guideline = "EUCAST",
uti = FALSE,
...
)
\method{as.rsi}{data.frame}(x, col_mo = NULL, guideline = "EUCAST", ...)
\method{as.rsi}{data.frame}(x, col_mo = NULL, guideline = "EUCAST", uti = NULL, ...)
is.rsi(x)
@ -33,6 +47,8 @@ is.rsi.eligible(x, threshold = 0.05)
\item{guideline}{defaults to the latest included EUCAST guideline, run \code{unique(rsi_translation$guideline)} for all options}
\item{uti}{(Urinary Tract Infection) A vector with \link{logical}s (\code{TRUE} or \code{FALSE}) to specify whether a UTI specific interpretation from the guideline should be chosen. For using \code{\link[=as.rsi]{as.rsi()}} on a \link{data.frame}, this can also be a column containing \link{logical}s or when left blank, the data set will be search for a 'specimen' and rows containing 'urin' in that column will be regarded isolates from a UTI. See \emph{Examples}.}
\item{col_mo}{column name of the IDs of the microorganisms (see \code{\link[=as.mo]{as.mo()}}), defaults to the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
\item{threshold}{maximum fraction of invalid antimicrobial interpretations of \code{x}, please see \emph{Examples}}
@ -82,8 +98,41 @@ On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://
\examples{
# For INTERPRETING disk diffusion and MIC values -----------------------
# a whole data set, even with combined MIC values and disk zones
df <- data.frame(microorganism = "E. coli",
AMP = as.mic(8),
CIP = as.mic(0.256),
GEN = as.disk(18),
TOB = as.disk(16),
NIT = as.mic(32))
as.rsi(df)
# single values
# the dplyr way
library(dplyr)
df \%>\%
mutate_at(vars(AMP:TOB), as.rsi, mo = "E. coli")
df \%>\%
mutate_at(vars(AMP:TOB), as.rsi, mo = .$microorganism)
# to include information about urinary tract infections (UTI)
data.frame(mo = "E. coli",
NIT = c("<= 2", 32),
from_the_bladder = c(TRUE, FALSE)) \%>\%
as.rsi(uti = "from_the_bladder")
data.frame(mo = "E. coli",
NIT = c("<= 2", 32),
specimen = c("urine", "blood")) \%>\%
as.rsi() # automatically determines urine isolates
df \%>\%
mutate_at(vars(AMP:TOB), as.rsi, mo = "E. coli", uti = TRUE)
# for single values
as.rsi(x = as.mic(2),
mo = as.mo("S. pneumoniae"),
ab = "AMP",
@ -93,14 +142,6 @@ as.rsi(x = as.disk(18),
mo = "Strep pneu", # `mo` will be coerced with as.mo()
ab = "ampicillin", # and `ab` with as.ab()
guideline = "EUCAST")
# a whole data set, even with combined MIC values and disk zones
df <- data.frame(microorganism = "E. coli",
AMP = as.mic(8),
CIP = as.mic(0.256),
GEN = as.disk(18),
TOB = as.disk(16))
as.rsi(df)
# For CLEANING existing R/SI values ------------------------------------