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update to septic_patients, speed improvements

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dr. M.S. (Matthijs) Berends
2018-07-25 14:17:04 +02:00
parent 03a3cb397b
commit d9e204031d
26 changed files with 273 additions and 233 deletions
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R/data.R
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@ -252,7 +252,7 @@
#' \item{\code{type_nl}}{Type of microorganism in Dutch, like \code{"Bacterie"} and \code{"Schimmel/gist"}}
#' \item{\code{gramstain_nl}}{Gram of microorganism in Dutch, like \code{"Negatieve staven"}}
#' }
#' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
# source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
#' @seealso \code{\link{guess_bactid}} \code{\link{antibiotics}} \code{\link{microorganisms.umcg}}
"microorganisms"
@ -264,14 +264,14 @@
#' \item{\code{mocode}}{Code of microorganism according to UMCG MMB}
#' \item{\code{bactid}}{Code of microorganism in \code{\link{microorganisms}}}
#' }
#' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl}
# source MOLIS (LIS of Certe) - \url{https://www.certe.nl} \cr \cr GLIMS (LIS of UMCG) - \url{https://www.umcg.nl}
#' @seealso \code{\link{guess_bactid}} \code{\link{microorganisms}}
"microorganisms.umcg"
#' Dataset with 2000 blood culture isolates of septic patients
#'
#' An anonymised dataset containing 2000 microbial blood culture isolates with their antibiogram of septic patients found in 5 different hospitals in the Netherlands, between 2001 and 2017. This data.frame can be used to practice AMR analysis. For examples, press F1.
#' @format A data.frame with 2000 observations and 47 variables:
#' @format A data.frame with 2000 observations and 49 variables:
#' \describe{
#' \item{\code{date}}{date of receipt at the laboratory}
#' \item{\code{hospital_id}}{ID of the hospital}
@ -282,9 +282,9 @@
#' \item{\code{sex}}{sex of the patient}
#' \item{\code{patient_id}}{ID of the patient, first 10 characters of an SHA hash containing irretrievable information}
#' \item{\code{bactid}}{ID of microorganism, see \code{\link{microorganisms}}}
#' \item{\code{peni:mupi}}{38 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}); these column names occur in \code{\link{antibiotics}} and can be translated with \code{\link{abname}}}
#' \item{\code{peni:rifa}}{40 different antibiotics with class \code{rsi} (see \code{\link{as.rsi}}); these column names occur in \code{\link{antibiotics}} data set and can be translated with \code{\link{abname}}}
#' }
#' @source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
# source MOLIS (LIS of Certe) - \url{https://www.certe.nl}
#' @examples
#' # ----------- #
#' # PREPARATION #
@ -304,15 +304,15 @@
#' # ANALYSIS #
#' # -------- #
#'
#' # 1. Get the amoxicillin resistance percentages
#' # of E. coli, divided by hospital:
#' # 1. Get the amoxicillin resistance percentages (p)
#' # and numbers (n) of E. coli, divided by hospital:
#'
#' my_data %>%
#' filter(bactid == "ESCCOL",
#' filter(bactid == guess_bactid("E. coli"),
#' first_isolates == TRUE) %>%
#' group_by(hospital_id) %>%
#' summarise(n = n(),
#' amoxicillin_resistance = rsi(amox))
#' summarise(n = n_rsi(amox),
#' p = resistance(amox))
#'
#'
#' # 2. Get the amoxicillin/clavulanic acid resistance
@ -322,6 +322,6 @@
#' filter(bactid == guess_bactid("E. coli"),
#' first_isolates == TRUE) %>%
#' group_by(year = format(date, "%Y")) %>%
#' summarise(n = n(),
#' amoxclav_resistance = rsi(amcl, minimum = 20))
#' summarise(n = n_rsi(amcl),
#' p = resistance(amcl, minimum = 20))
"septic_patients"