% 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}