P281424/AMR
1
0
Fork 0
mirror of https://github.com/msberends/AMR.git synced 2025-07-09 00:02:38 +02:00
Code Releases Activity

use guess_bactid for GLIMS codes

Browse Source
This commit is contained in:
dr. M.S. (Matthijs) Berends
2018-03-19 21:23:21 +01:00
parent c765f424ab
commit fe803f7279
5 changed files with 19 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
man/bactlist.umcg.Rd
View File

@ -16,9 +16,9 @@ MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) -
bactlist.umcg
}
\description{
A dataset containing all bacteria codes of UMCG MMB. These codes can be joined to data with an ID from \code{\link{bactlist}$bactid}, using \code{\link{left_join_bactlist}}.
A dataset containing all bacteria codes of UMCG MMB. These codes can be joined to data with an ID from \code{\link{bactlist}$bactid} (using \code{\link{left_join_bactlist}}). GLIMS codes can also be translated to valid \code{bactid}'s with \code{\link{guess_bactid}}.
}
\seealso{
\code{\link{bactlist}}
\code{\link{guess_bactid}} \code{\link{bactlist}}
}
\keyword{datasets}

8
man/first_isolate.Rd
View File

@ -59,10 +59,10 @@ Determine first (weighted) isolates of all microorganisms of every patient per e
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{DETERMINING WEIGHTED ISOLATES} \cr
\strong{1. Using \code{type = "keyantibiotics"} and parameter \code{ignore_I}} \cr
To determine weighted isolates, the difference between key antibiotics will be checked. Any difference from S to R (or vice versa) will (re)select an isolate as a first weighted isolate. With \code{ignore_I == FALSE}, also differences from I to S|R (or vice versa) will lead to this. This is a reliable and fast method. \cr
\strong{2. Using \code{type = "points"} and parameter \code{points_threshold}} \cr
To determine weighted isolates, difference between antimicrobial interpretations will be measured with points. 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. This method is being used by the Infection Prevention department (Dr M. Lokate) of the University Medical Center Groningen (UMCG).
\strong{1. Using} \code{type = "keyantibiotics"} \strong{and parameter} \code{ignore_I} \cr
To determine weighted isolates, the difference between key antibiotics will be checked. Any difference from S to R (or vice versa) will (re)select an isolate as a first weighted isolate. With \code{ignore_I = FALSE}, also differences from I to S|R (or vice versa) will lead to this. This is a reliable method and 30-35 times faster than method 2. \cr
\strong{2. Using} \code{type = "points"} \strong{and parameter} \code{points_threshold} \cr
To determine weighted isolates, difference between antimicrobial interpretations will be measured with points. 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. This method is being used by the Infection Prevention department (Dr M. Lokate) of the University Medical Center Groningen (UMCG).
}
\examples{
# septic_patients is a dataset available in the AMR package