mirror of
https://github.com/msberends/AMR.git
synced 2024-12-26 08:06:12 +01:00
102 lines
4.2 KiB
R
102 lines
4.2 KiB
R
% Generated by roxygen2: do not edit by hand
|
|
% Please edit documentation in R/first_isolates.R
|
|
\name{first_isolate}
|
|
\alias{first_isolate}
|
|
\title{Determine first (weighted) isolates}
|
|
\usage{
|
|
first_isolate(tbl, col_date, col_patient_id, col_genus, col_species,
|
|
col_testcode = NA, col_specimen, col_icu, col_keyantibiotics = NA,
|
|
episode_days = 365, testcodes_exclude = "", icu_exclude = FALSE,
|
|
filter_specimen = NA, output_logical = TRUE, points_threshold = 2,
|
|
info = TRUE)
|
|
}
|
|
\arguments{
|
|
\item{tbl}{a \code{data.frame} containing isolates.}
|
|
|
|
\item{col_date}{column name of the result date (or date that is was received on the lab)}
|
|
|
|
\item{col_patient_id}{column name of the unique IDs of the patients}
|
|
|
|
\item{col_genus}{column name of the genus of the microorganisms}
|
|
|
|
\item{col_species}{column name of the species of the microorganisms}
|
|
|
|
\item{col_testcode}{column name of the test codes. Use \code{col_testcode = NA} to \strong{not} exclude certain test codes (like test codes for screening). In that case \code{testcodes_exclude} will be ignored.}
|
|
|
|
\item{col_specimen}{column name of the specimen type or group}
|
|
|
|
\item{col_icu}{column name of the logicals (\code{TRUE}/\code{FALSE}) whether a ward or department is an Intensive Care Unit (ICU)}
|
|
|
|
\item{col_keyantibiotics}{column name of the key antibiotics to determine first \emph{weighted} isolates, see \code{\link{key_antibiotics}}.}
|
|
|
|
\item{episode_days}{episode in days after which a genus/species combination will be determined as 'first isolate' again}
|
|
|
|
\item{testcodes_exclude}{character vector with test codes that should be excluded (caseINsensitive)}
|
|
|
|
\item{icu_exclude}{logical whether ICU isolates should be excluded}
|
|
|
|
\item{filter_specimen}{specimen group or type that should be excluded}
|
|
|
|
\item{output_logical}{return output as \code{logical} (will else the values \code{0} or \code{1})}
|
|
|
|
\item{points_threshold}{points until the comparison of key antibiotics will lead to inclusion of an isolate, see Details}
|
|
|
|
\item{info}{print progress}
|
|
}
|
|
\value{
|
|
A vector to add to table, see Examples.
|
|
}
|
|
\description{
|
|
Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type.
|
|
}
|
|
\details{
|
|
\strong{Why this is so important} \cr
|
|
To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode \href{https://www.ncbi.nlm.nih.gov/pubmed/17304462}{[1]}. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all \emph{S. aureus} isolates would be overestimated, because you included this MRSA more than once. It would be \href{https://en.wikipedia.org/wiki/Selection_bias}{selection bias}.
|
|
\strong{\code{points_threshold}} \cr
|
|
To compare key antibiotics, the difference between antimicrobial interpretations will be measured. A difference from I to S|R (or vice versa) means 0.5 points. A difference from S to R (or vice versa) means 1 point. When the sum of points exceeds \code{points_threshold}, an isolate will be (re)selected as a first weighted isolate.
|
|
}
|
|
\examples{
|
|
\dontrun{
|
|
|
|
# set key antibiotics to a new variable
|
|
tbl$keyab <- key_antibiotics(tbl)
|
|
|
|
tbl$first_isolate <-
|
|
first_isolate(tbl)
|
|
|
|
tbl$first_isolate_weighed <-
|
|
first_isolate(tbl,
|
|
col_keyantibiotics = 'keyab')
|
|
|
|
tbl$first_blood_isolate <-
|
|
first_isolate(tbl,
|
|
filter_specimen = 'Blood')
|
|
|
|
tbl$first_blood_isolate_weighed <-
|
|
first_isolate(tbl,
|
|
filter_specimen = 'Blood',
|
|
col_keyantibiotics = 'keyab')
|
|
|
|
tbl$first_urine_isolate <-
|
|
first_isolate(tbl,
|
|
filter_specimen = 'Urine')
|
|
|
|
tbl$first_urine_isolate_weighed <-
|
|
first_isolate(tbl,
|
|
filter_specimen = 'Urine',
|
|
col_keyantibiotics = 'keyab')
|
|
|
|
tbl$first_resp_isolate <-
|
|
first_isolate(tbl,
|
|
filter_specimen = 'Respiratory')
|
|
|
|
tbl$first_resp_isolate_weighed <-
|
|
first_isolate(tbl,
|
|
filter_specimen = 'Respiratory',
|
|
col_keyantibiotics = 'keyab')
|
|
}
|
|
}
|
|
\keyword{first}
|
|
\keyword{isolate}
|
|
\keyword{isolates}
|