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added septic_patients

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dr. M.S. (Matthijs) Berends
2018-02-27 20:01:02 +01:00
parent 98b2b99913
commit 34e70a65ed
10 changed files with 202 additions and 94 deletions
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13
man/first_isolate.Rd
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@ -7,7 +7,7 @@
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, ignore_I = TRUE,
filter_specimen = NA, output_logical = TRUE, points_threshold = 2,
info = TRUE)
}
\arguments{
@ -21,7 +21,7 @@ first_isolate(tbl, col_date, col_patient_id, col_genus, col_species,
\item{col_species}{column name of the species of the microorganisms}
\item{col_testcode}{column name of the test codes, see Details}
\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}
@ -39,7 +39,7 @@ first_isolate(tbl, col_date, col_patient_id, col_genus, col_species,
\item{output_logical}{return output as \code{logical} (will else the values \code{0} or \code{1})}
\item{ignore_I}{ignore \code{"I"} as antimicrobial interpretation of key antibiotics (with \code{FALSE}, changes in antibiograms from S to I and I to R will be interpreted as difference)}
\item{points_threshold}{points until the comparison of key antibiotics will lead to inclusion of an isolate, see Details}
\item{info}{print progress}
}
@ -50,9 +50,10 @@ A vector to add to table, see Examples.
Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type.
}
\details{
To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode. 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 is 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 selection bias.
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.
\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{