(v0.8.0.9033) antivirals data set, cleanup

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 0.8.0.9032
-Date: 2019-11-15
+Version: 0.8.0.9033
+Date: 2019-11-18
 Title: Antimicrobial Resistance Analysis
 Authors@R: c(
     person(role = c("aut", "cre"), 

NEWS.md

@@ -1,5 +1,5 @@
-# AMR 0.8.0.9032
-<small>Last updated: 15-Nov-2019</small>
+# AMR 0.8.0.9033
+## <small>Last updated: 18-Nov-2019</small>
 
 ### Breaking
 * Adopted Adeolu *et al.* (2016), [PMID 27620848](https://www.ncbi.nlm.nih.gov/pubmed/27620848) for the `microorganisms` data set, which means that the new order Enterobacterales now consists of a part of the existing family Enterobacteriaceae, but that this family has been split into other families as well (like *Morganellaceae* and *Yersiniaceae*). Although published in 2016, this information is not yet in the Catalogue of Life version of 2019. All MDRO determinations with `mdro()` will now use the Enterobacterales order for all guidelines before 2016 that were dependent on the Enterobacteriaceae family.
@@ -25,6 +25,7 @@
 * Support for a new MDRO guideline: Magiorakos AP, Srinivasan A *et al.* "Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance." Clinical Microbiology and Infection (2012).
   * This is now the new default guideline for the `mdro()` function
   * The new Verbose mode (`mdro(...., verbose = TRUE)`) returns an informative data set where the reason for MDRO determination is given for every isolate, and an list of the resistant antimicrobial agents
+* Data set `antivirals`, containing all entries from the ATC J05 group with their DDDs for oral and parenteral treatment
 
 ### Changes
 * Improvements to algorithm in `as.mo()`:
@@ -48,13 +49,14 @@
 * When running `as.rsi()` over a data set, it will now print the guideline that will be used if it is not specified by the user
 * Improvements for `eucast_rules()`:
   * Fix where *Stenotrophomonas maltophilia* would always become ceftazidime R (following EUCAST v3.1)
-  * Fix where *Leuconostoc* and *Pediococcus* would not always become glyopeptides R
+  * Fix where *Leuconostoc* and *Pediococcus* would not always become glycopeptides R
   * non-EUCAST rules in `eucast_rules()` are now applied first and not as last anymore. This is to improve the dependency on certain antibiotics for the official EUCAST rules. Please see `?eucast_rules`.
 * Fix for interpreting MIC values with `as.rsi()` where the input is `NA`
 * Added "imi" and "imp" as allowed abbreviation for Imipenem (IPM)
 * Fix for automatically determining columns with antibiotic results in `mdro()` and `eucast_rules()`
 * Added ATC codes for ceftaroline, ceftobiprole and faropenem and fixed two typos in the `antibiotics` data set
 * More robust way of determining valid MIC values
+* Small changed to the `example_isolates` data set to better reflect reality
 
 ### Other
 * Change dependency on `clean` to `cleaner`, as this package was renamed accordingly upon CRAN request

R/data.R

@@ -34,7 +34,7 @@
 #'   \item{\code{abbr}}{List of abbreviations as used in many countries, also for antibiotic susceptibility testing (AST)}
 #'   \item{\code{synonyms}}{Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID}
 #'   \item{\code{oral_ddd}}{Defined Daily Dose (DDD), oral treatment}
-#'   \item{\code{oral_units}}{Units of \code{ddd_units}}
+#'   \item{\code{oral_units}}{Units of \code{oral_ddd}}
 #'   \item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
 #'   \item{\code{iv_units}}{Units of \code{iv_ddd}}
 #' }
@@ -48,9 +48,28 @@
 #' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}
 #' @inheritSection WHOCC WHOCC
 #' @inheritSection AMR Read more on our website!
-#' @seealso \code{\link{microorganisms}}
+#' @seealso \code{\link{antivirals}} \code{\link{microorganisms}}
 "antibiotics"
 
+#' Data set with ~100 antivirals
+#'
+#' A data set containing all antivirals, according to the ATC code group 'J05' (Antivirals for systemic use).
+#' @format A \code{\link{data.frame}} with 102 observations and 7 variables:
+#' \describe{
+#'   \item{\code{atc}}{ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC}
+#'   \item{\code{name}}{Official name as used by WHONET/EARS-Net or the WHO}
+#'   \item{\code{atc_group}}{Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC}
+#'   \item{\code{oral_ddd}}{Defined Daily Dose (DDD), oral treatment}
+#'   \item{\code{oral_units}}{Units of \code{oral_ddd}}
+#'   \item{\code{iv_ddd}}{Defined Daily Dose (DDD), parenteral treatment}
+#'   \item{\code{iv_units}}{Units of \code{iv_ddd}}
+#' }
+#' @source World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): \url{https://www.whocc.no/atc_ddd_index/}
+#' @inheritSection WHOCC WHOCC
+#' @inheritSection AMR Read more on our website!
+#' @seealso \code{\link{antibiotics}} \code{\link{microorganisms}}
+"antivirals"
+
 #' Data set with ~70,000 microorganisms
 #'
 #' A data set containing the microbial taxonomy of six kingdoms from the Catalogue of Life. MO codes can be looked up using \code{\link{as.mo}}.
@@ -126,9 +145,9 @@ catalogue_of_life <- list(
 #' @seealso \code{\link{as.mo}} \code{\link{microorganisms}}
 "microorganisms.codes"
 
-#' Data set with 2,000 blood culture isolates
+#' Data set with 2,000 example isolates
 #'
-#' An anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found 4 different hospitals in the Netherlands, between 2001 and 2017. This \code{data.frame} can be used to practice AMR analysis. For examples, please read \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{the tutorial on our website}.
+#' A data set containing 2,000 microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR analysis. For examples, please read \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{the tutorial on our website}.
 #' @format A \code{\link{data.frame}} with 2,000 observations and 49 variables:
 #' \describe{
 #'   \item{\code{date}}{date of receipt at the laboratory}
@@ -138,7 +157,7 @@ catalogue_of_life <- list(
 #'   \item{\code{ward_outpatient}}{logical to determine if ward is an outpatient clinic}
 #'   \item{\code{age}}{age of the patient}
 #'   \item{\code{gender}}{gender of the patient}
-#'   \item{\code{patient_id}}{ID of the patient, first 10 characters of an SHA hash containing irretrievable information}
+#'   \item{\code{patient_id}}{ID of the patient}
 #'   \item{\code{mo}}{ID of microorganism created with \code{\link{as.mo}}, see also \code{\link{microorganisms}}}
 #'   \item{\code{PEN:RIF}}{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{ab_name}}}
 #' }
@@ -183,17 +202,17 @@ catalogue_of_life <- list(
 #' Data set for RSI interpretation
 #'
 #' Data set to interpret MIC and disk diffusion to RSI values. Included guidelines are CLSI (2011-2019) and EUCAST (2011-2019). Use \code{\link{as.rsi}} to transform MICs or disks measurements to RSI values.
-#' @format A \code{\link{data.frame}} with 11,559 observations and 9 variables:
+#' @format A \code{\link{data.frame}} with 13,975 observations and 9 variables:
 #' \describe{
 #'   \item{\code{guideline}}{Name of the guideline}
+#'   \item{\code{method}}{Either "MIC" or "DISK"}
+#'   \item{\code{site}}{Body site, e.g. "Oral" or "Respiratory"}
 #'   \item{\code{mo}}{Microbial ID, see \code{\link{as.mo}}}
 #'   \item{\code{ab}}{Antibiotic ID, see \code{\link{as.ab}}}
 #'   \item{\code{ref_tbl}}{Info about where the guideline rule can be found}
-#'   \item{\code{S_mic}}{Lowest MIC value that leads to "S"}
-#'   \item{\code{R_mic}}{Highest MIC value that leads to "R"}
-#'   \item{\code{dose_disk}}{Dose of the used disk diffusion method}
-#'   \item{\code{S_disk}}{Lowest number of millimeters that leads to "S"}
-#'   \item{\code{R_disk}}{Highest number of millimeters that leads to "R"}
+#'   \item{\code{disk_dose}}{Dose of the used disk diffusion method}
+#'   \item{\code{breakpoint_S}}{Lowest MIC value or highest number of millimeters that leads to "S"}
+#'   \item{\code{breakpoint_R}}{Highest MIC value or lowest number of millimeters that leads to "R"}
 #' }
 #' @inheritSection AMR Read more on our website!
 "rsi_translation"

R/eucast_rules.R

@@ -163,6 +163,7 @@ EUCAST_VERSION_EXPERT_RULES <- "3.1, 2016"
 #'   }
 #' @inheritSection AMR Read more on our website!
 #' @examples
+#' \donttest{
 #' a <- data.frame(mo = c("Staphylococcus aureus",
 #'                        "Enterococcus faecalis",
 #'                        "Escherichia coli",
@@ -198,7 +199,6 @@ EUCAST_VERSION_EXPERT_RULES <- "3.1, 2016"
 #' # 5 Pseudomonas aeruginosa    R    R    -    -    R    R    R
 #'
 #'
-#' \donttest{
 #' # do not apply EUCAST rules, but rather get a data.frame
 #' # with 18 rows, containing all details about the transformations:
 #' c <- eucast_rules(a, verbose = TRUE)

R/mdro.R

@@ -54,29 +54,24 @@
 #' @rdname mdro
 #' @aliases MDR XDR PDR BRMO 3MRGN 4MRGN
 #' @importFrom dplyr %>% filter_at vars all_vars pull mutate_at
-#' @importFrom crayon blue bold italic
+#' @importFrom crayon blue bold italic red
 #' @importFrom cleaner percentage
 #' @export
 #' @inheritSection AMR Read more on our website!
 #' @source
 #' Please see Details for the list of publications used for this function.
 #' @examples
+#' \donttest{
 #' library(dplyr)
 #' 
 #' example_isolates %>%
 #'   mdro() %>%
 #'   freq()
 #'   
-#' \donttest{
 #' example_isolates %>%
 #'   mutate(EUCAST = eucast_exceptional_phenotypes(.),
 #'          BRMO = brmo(.),
 #'          MRGN = mrgn(.))
-#'          
-#' example_isolates %>% 
-#'   rename(PIP = TZP) %>% # no piperacillin, so take piperacillin/tazobactam
-#'   mrgn() %>%            # check German guideline
-#'   freq()                # check frequencies
 #' }
 mdro <- function(x,
                  guideline = NULL,
@@ -155,7 +150,7 @@ mdro <- function(x,
     guideline$name <- "Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance."
     guideline$author <- "Magiorakos AP, Srinivasan A, Carey RB, ..., Vatopoulos A, Weber JT, Monnet DL"
     guideline$version <- "N/A"
-    guideline$source <- "Magiorakos et al. (2012) Clinical Microbiology and Infection 18:3. DOI: 10.1111/j.1469-0691.2011.03570.x"
+    guideline$source <- "Clinical Microbiology and Infection 18:3, 2012. DOI: 10.1111/j.1469-0691.2011.03570.x"
     
   } else if (guideline$code == "eucast") {
     guideline$name <- "EUCAST Expert Rules, \"Intrinsic Resistance and Exceptional Phenotypes Tables\""
@@ -174,7 +169,7 @@ mdro <- function(x,
     guideline$name <- "Cross-border comparison of the Dutch and German guidelines on multidrug-resistant Gram-negative microorganisms"
     guideline$author <- "M\u00fcller J, Voss A, K\u00f6ck R, ..., Kern WV, Wendt C, Friedrich AW"
     guideline$version <- "N/A"
-    guideline$source <- "M\u00fcller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6"
+    guideline$source <- "Antimicrobial Resistance and Infection Control 4:7, 2015. DOI: 10.1186/s13756-015-0047-6"
     
   } else if (guideline$code == "brmo") {
     guideline$name <- "WIP-Richtlijn Bijzonder Resistente Micro-organismen (BRMO)"
@@ -422,9 +417,9 @@ mdro <- function(x,
   
   if (info == TRUE) {
     if (combine_SI == TRUE) {
-      cat("\nOnly results with 'R' are considered as resistance. Use `combine_SI = FALSE` to also consider 'I' as resistance.\n")
+      cat(red("\nOnly results with 'R' are considered as resistance. Use `combine_SI = FALSE` to also consider 'I' as resistance.\n"))
     } else {
-      cat("\nResults with 'R' or 'I' are considered as resistance. Use `combine_SI = TRUE` to only consider 'R' as resistance.\n")
+      cat(red("\nResults with 'R' or 'I' are considered as resistance. Use `combine_SI = TRUE` to only consider 'R' as resistance.\n"))
     }
     cat("\nDetermining multidrug-resistant organisms (MDRO), according to:\n",
         bold("Guideline: "), italic(guideline$name), "\n",

R/mo.R

@@ -572,22 +572,21 @@ exec_as.mo <- function(x,
     # add start en stop regex
     x <- paste0("^", x, "$")
     
-    
     x_withspaces_start_only <- paste0("^", x_withspaces)
     x_withspaces_end_only <- paste0(x_withspaces, "$")
     x_withspaces_start_end <- paste0("^", x_withspaces, "$")
     
     if (isTRUE(debug)) {
-      cat(paste0(blue('x'), '                       "', x, '"\n'))
-      cat(paste0(blue('x_species'), '               "', x_species, '"\n'))
-      cat(paste0(blue('x_withspaces_start_only'), ' "', x_withspaces_start_only, '"\n'))
-      cat(paste0(blue('x_withspaces_end_only'), '   "', x_withspaces_end_only, '"\n'))
-      cat(paste0(blue('x_withspaces_start_end'), '  "', x_withspaces_start_end, '"\n'))
-      cat(paste0(blue('x_backup'), '                "', x_backup, '"\n'))
-      cat(paste0(blue('x_backup_without_spp'), '    "', x_backup_without_spp, '"\n'))
-      cat(paste0(blue('x_trimmed'), '               "', x_trimmed, '"\n'))
-      cat(paste0(blue('x_trimmed_species'), '       "', x_trimmed_species, '"\n'))
-      cat(paste0(blue('x_trimmed_without_group'), ' "', x_trimmed_without_group, '"\n'))
+      cat(paste0(blue("x"), '                       "', x, '"\n'))
+      cat(paste0(blue("x_species"), '               "', x_species, '"\n'))
+      cat(paste0(blue("x_withspaces_start_only"), ' "', x_withspaces_start_only, '"\n'))
+      cat(paste0(blue("x_withspaces_end_only"), '   "', x_withspaces_end_only, '"\n'))
+      cat(paste0(blue("x_withspaces_start_end"), '  "', x_withspaces_start_end, '"\n'))
+      cat(paste0(blue("x_backup"), '                "', x_backup, '"\n'))
+      cat(paste0(blue("x_backup_without_spp"), '    "', x_backup_without_spp, '"\n'))
+      cat(paste0(blue("x_trimmed"), '               "', x_trimmed, '"\n'))
+      cat(paste0(blue("x_trimmed_species"), '       "', x_trimmed_species, '"\n'))
+      cat(paste0(blue("x_trimmed_without_group"), ' "', x_trimmed_without_group, '"\n'))
     }
     
     progress <- progress_estimated(n = length(x), min_time = 3)
@@ -1782,6 +1781,7 @@ pillar_shaft.mo <- function(x, ...) {
   out[is.na(x)] <- pillar::style_na("  NA")
   out[x == "UNKNOWN"] <- pillar::style_na("  UNKNOWN")
   
+  # make it always fit exactly
   pillar::new_pillar_shaft_simple(out, align = "left", width = max(nchar(x)))
 }
 

R/whocc.R

@@ -24,7 +24,7 @@
 #' All antimicrobial drugs and their official names, ATC codes, ATC groups and defined daily dose (DDD) are included in this package, using the WHO Collaborating Centre for Drug Statistics Methodology.
 #' @section WHOCC:
 #' \if{html}{\figure{logo_who.png}{options: height=60px style=margin-bottom:5px} \cr}
-#' This package contains \strong{all ~450 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}). 
+#' This package contains \strong{all ~550 antibiotic, antimycotic and antiviral drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}). 
 #'
 #' These have become the gold standard for international drug utilisation monitoring and research.
 #'

_pkgdown.yml

@@ -83,15 +83,6 @@ navbar:
       href: "LICENSE-text.html"
 
 reference:
-  - title: "Background information"
-    desc: >
-      Some pages about our package and its external sources. Be sure to read our [How To's](./../articles/index.html)
-      for more information about how to work with functions in this package.
-    contents:
-    - "`AMR`"
-    - "`catalogue_of_life`"
-    - "`catalogue_of_life_version`"
-    - "`WHOCC`"
   - title: "Cleaning your data"
     desc: >
       Functions for cleaning and optimising your data, to be able to add
@@ -99,28 +90,28 @@ reference:
       antibiotic interpretations by applying [EUCAST rules](http://www.eucast.org/expert_rules_and_intrinsic_resistance/).
     contents:
     - starts_with("as.")
-    - "`mo_source`"
     - "`eucast_rules`"
-    - "`rsi_translation`"
     - "`guess_ab_col`"
+    - "`mo_source`"
     - "`read.4D`"
-  - title: "Adding variables to your data"
+    - "`rsi_translation`"
+  - title: "Enhancing your data"
     desc: >
-      Functions to add new data to existing data, like the determination
+      Functions to add new data to your existing data, such as the determination
       of first isolates, multi-drug resistant microorganisms (MDRO), getting
       properties of microorganisms or antibiotics and determining the age of
       patients or divide ages into age groups.
     contents:
+    - "`ab_property`"
+    - "`age_groups`"
+    - "`age`"
+    - "`atc_online_property`"
     - "`first_isolate`"
-    - "`mdro`"
+    - "`join`"
     - "`key_antibiotics`"
+    - "`mdro`"
     - "`mo_property`"
-    - "`ab_property`"
-    - "`age`"
-    - "`age_groups`"
     - "`p_symbol`"
-    - "`join`"
-    - "`atc_online_property`"
   - title: "Analysing your data"
     desc: >
       Functions for conducting AMR analysis, like counting isolates, calculating
@@ -129,24 +120,34 @@ reference:
     - "`availability`"
     - "`bug_drug_combinations`"
     - "`count`"
-    - "`portion`"
     - "`filter_ab_class`"
     - "`g.test`"
     - "`ggplot_rsi`"
     - "`kurtosis`"
+    - "`portion`"
     - "`resistance_predict`"
     - "`skewness`"
   - title: "Included data sets"
     desc: >
-      References for microorganisms and antibiotics, and even a
-      genuine data set with isolates from septic patients.
+      Scientifically reliable references for microorganisms and
+      antibiotics, and example data sets to use for practise.
     contents:
     - "`antibiotics`"
-    - "`microorganisms`"
+    - "`antivirals`"
     - "`example_isolates`"
-    - "`WHONET`"
     - "`microorganisms.codes`"
     - "`microorganisms.old`"
+    - "`microorganisms`"
+    - "`WHONET`"
+  - title: "Background information"
+    desc: >
+      Some pages about our package and its external sources. Be sure to read our [How To's](./../articles/index.html)
+      for more information about how to work with functions in this package.
+    contents:
+    - "`AMR`"
+    - "`catalogue_of_life`"
+    - "`catalogue_of_life_version`"
+    - "`WHOCC`"
   - title: Other functions
     desc: >
       These functions are mostly for internal use, but some of
@@ -160,9 +161,10 @@ reference:
       These functions are extensions of functions in other packages.
     contents:
     - "`extended-functions`"
+    - "`reexports`"
   - title:  functions
     desc: >
-      These functions are deprecated, meaning that they still
+      These functions are deprecated, meaning that they will still
       work but show a warning with every use and will be removed
       in a future version.
     contents:

data-raw/reproduction_of_antibiotics.R

@@ -1,3 +1,23 @@
+# ==================================================================== #
+# TITLE                                                                #
+# Antimicrobial Resistance (AMR) Analysis                              #
+#                                                                      #
+# SOURCE                                                               #
+# https://gitlab.com/msberends/AMR                                     #
+#                                                                      #
+# LICENCE                                                              #
+# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)  #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+#                                                                      #
+# This R package was created for academic research and was publicly    #
+# released in the hope that it will be useful, but it comes WITHOUT    #
+# ANY WARRANTY OR LIABILITY.                                           #
+# Visit our website for more info: https://msberends.gitlab.io/AMR.    #
+# ==================================================================== #
 
 library(dplyr)
 

data-raw/reproduction_of_antivirals.R

@@ -0,0 +1,62 @@
+# ==================================================================== #
+# TITLE                                                                #
+# Antimicrobial Resistance (AMR) Analysis                              #
+#                                                                      #
+# SOURCE                                                               #
+# https://gitlab.com/msberends/AMR                                     #
+#                                                                      #
+# LICENCE                                                              #
+# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl)  #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+#                                                                      #
+# This R package was created for academic research and was publicly    #
+# released in the hope that it will be useful, but it comes WITHOUT    #
+# ANY WARRANTY OR LIABILITY.                                           #
+# Visit our website for more info: https://msberends.gitlab.io/AMR.    #
+# ==================================================================== #
+
+# get all data from the WHOCC website
+
+get_atc_table <- function(atc_group) {
+  # give as input J0XXX, like atc_group = "J05AB"
+  downloaded <- read_html(paste0("https://www.whocc.no/atc_ddd_index/?code=", atc_group, "&showdescription=no"))
+  table_title <- downloaded %>% html_nodes(paste0('a[href="./?code=', atc_group, '"]')) %>% html_text()
+  table_content <- downloaded %>% 
+    html_nodes("table") %>%
+    html_table(header = TRUE) %>%
+    # returns list, so make data.frame out of it
+    as.data.frame(stringsAsFactors = FALSE) %>%
+    # select right columns
+    select(atc = ATC.code, name = Name, ddd = DDD, unit = U, ddd_type = Adm.R) %>%
+    # fill empty rows
+    mutate(atc = ifelse(atc == "", lag(atc), atc), name = ifelse(name == "", lag(name), name)) %>% 
+    pivot_wider(names_from = ddd_type, values_from = c(ddd, unit)) %>% 
+    mutate(atc_group = table_title)
+  if (!"ddd_O" %in% colnames(table_content)) {
+    table_content <- table_content %>% mutate(ddd_O = NA_real_, unit_O = NA_character_)
+  }
+  if (!"ddd_P" %in% colnames(table_content)) {
+    table_content <- table_content %>% mutate(ddd_P = NA_real_, unit_P = NA_character_)
+  }
+  table_content %>% select(atc, name, atc_group, 
+                           oral_ddd = ddd_O, oral_units = unit_O,
+                           iv_ddd = ddd_P, iv_units = unit_P)
+}
+
+# these are the relevant groups for input: https://www.whocc.no/atc_ddd_index/?code=J05A (J05 only contains J05A)
+atc_groups <- c("J05AA", "J05AB", "J05AC", "J05AD", "J05AE", "J05AF", "J05AG", "J05AH", "J05AP", "J05AR", "J05AX")
+
+# get the first
+antivirals <- get_atc_table(atc_groups[1])
+# bind all others to it
+for (i in 2:length(atc_groups)) {
+  antivirals <- rbind(antivirals, get_atc_table(atc_groups[i]))
+}
+
+# arrange on name, untibble it and save
+antivirals <- antivirals %>% arrange(name) %>% as.data.frame(stringsAsFactors = FALSE)
+usethis::use_data(antivirals, overwrite = TRUE)

docs/404.html

@@ -84,7 +84,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="https://msberends.gitlab.io/AMR/index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9033</span>
       </span>
     </div>
 

docs/LICENSE-text.html

@@ -84,7 +84,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9033</span>
       </span>
     </div>
 

docs/articles/AMR.html

@@ -41,7 +41,7 @@
       </button>
       <span class="navbar-brand">
         <a class="navbar-link" href="../index.html">AMR (for R)</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9031</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.8.0.9032</span>
       </span>
     </div>
 
@@ -187,7 +187,7 @@
       <h1>How to conduct AMR analysis</h1>
                         <h4 class="author">Matthijs S. Berends</h4>
             
-            <h4 class="date">15 November 2019</h4>
+            <h4 class="date">18 November 2019</h4>
       
       
       <div class="hidden name"><code>AMR.Rmd</code></div>
@@ -196,7 +196,7 @@
 
     
     
-<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 15 November 2019.</p>
+<p><strong>Note:</strong> values on this page will change with every website update since they are based on randomly created values and the page was written in <a href="https://rmarkdown.rstudio.com/">R Markdown</a>. However, the methodology remains unchanged. This page was generated on 18 November 2019.</p>
 <div id="introduction" class="section level1">
 <h1 class="hasAnchor">
 <a href="#introduction" class="anchor"></a>Introduction</h1>
@@ -212,21 +212,21 @@
 </tr></thead>
 <tbody>
 <tr class="odd">
-<td align="center">2019-11-15</td>
+<td align="center">2019-11-18</td>
 <td align="center">abcd</td>
 <td align="center">Escherichia coli</td>
 <td align="center">S</td>
 <td align="center">S</td>
 </tr>
 <tr class="even">
-<td align="center">2019-11-15</td>
+<td align="center">2019-11-18</td>
 <td align="center">abcd</td>
 <td align="center">Escherichia coli</td>
 <td align="center">S</td>
 <td align="center">R</td>
 </tr>
 <tr class="odd">
-<td align="center">2019-11-15</td>
+<td align="center">2019-11-18</td>
 <td align="center">efgh</td>
 <td align="center">Escherichia coli</td>
 <td align="center">R</td>
@@ -321,8 +321,8 @@
 </tr></thead>
 <tbody>
 <tr class="odd">
-<td align="center">2015-09-02</td>
-<td align="center">V3</td>
+<td align="center">2011-03-27</td>
+<td align="center">O9</td>
 <td align="center">Hospital B</td>
 <td align="center">Escherichia coli</td>
 <td align="center">S</td>
@@ -332,59 +332,59 @@
 <td align="center">F</td>
 </tr>
 <tr class="even">
-<td align="center">2017-06-27</td>
-<td align="center">H4</td>
+<td align="center">2015-09-08</td>
+<td align="center">U5</td>
 <td align="center">Hospital C</td>
 <td align="center">Escherichia coli</td>
-<td align="center">R</td>
-<td align="center">R</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">M</td>
+<td align="center">S</td>
+<td align="center">S</td>
+<td align="center">F</td>
 </tr>
 <tr class="odd">
-<td align="center">2012-05-31</td>
-<td align="center">X3</td>
-<td align="center">Hospital B</td>
-<td align="center">Streptococcus pneumoniae</td>
-<td align="center">I</td>
+<td align="center">2014-09-10</td>
+<td align="center">L5</td>
+<td align="center">Hospital C</td>
+<td align="center">Staphylococcus aureus</td>
 <td align="center">S</td>
+<td align="center">R</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">F</td>
+<td align="center">M</td>
 </tr>
 <tr class="even">
-<td align="center">2013-06-08</td>
-<td align="center">K2</td>
-<td align="center">Hospital B</td>
-<td align="center">Staphylococcus aureus</td>
-<td align="center">I</td>
+<td align="center">2011-07-28</td>
+<td align="center">D7</td>
+<td align="center">Hospital A</td>
+<td align="center">Escherichia coli</td>
+<td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">M</td>
 </tr>
 <tr class="odd">
-<td align="center">2012-02-10</td>
-<td align="center">M5</td>
+<td align="center">2013-04-12</td>
+<td align="center">N6</td>
 <td align="center">Hospital A</td>
 <td align="center">Escherichia coli</td>
+<td align="center">I</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">S</td>
-<td align="center">M</td>
+<td align="center">F</td>
 </tr>
 <tr class="even">
-<td align="center">2010-06-25</td>
-<td align="center">N7</td>
-<td align="center">Hospital D</td>
+<td align="center">2017-03-29</td>
+<td align="center">F1</td>
+<td align="center">Hospital A</td>
 <td align="center">Escherichia coli</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">F</td>
+<td align="center">M</td>
 </tr>
 </tbody>
 </table>
@@ -406,8 +406,8 @@
 # 
 #      Item     Count   Percent   Cum. Count   Cum. Percent
 # ---  -----  -------  --------  -----------  -------------
-# 1    M       10,309    51.55%       10,309         51.55%
-# 2    F        9,691    48.46%       20,000        100.00%</code></pre>
+# 1    M       10,413    52.06%       10,413         52.06%
+# 2    F        9,587    47.94%       20,000        100.00%</code></pre>
 <p>So, we can draw at least two conclusions immediately. From a data scientists perspective, the data looks clean: only values <code>M</code> and <code>F</code>. From a researchers perspective: there are slightly more men. Nothing we didn’t already know.</p>
 <p>The data is already quite clean, but we still need to transform some variables. The <code>bacteria</code> column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The <code><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate()</a></code> function of the <code>dplyr</code> package makes this really easy:</p>
 <div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">data &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span></a>
@@ -422,8 +422,8 @@
 <a class="sourceLine" id="cb14-3" data-line-number="3"><span class="co"># Other rules by this AMR package</span></a>
 <a class="sourceLine" id="cb14-4" data-line-number="4"><span class="co"># Non-EUCAST: inherit amoxicillin results for unavailable ampicillin (no changes)</span></a>
 <a class="sourceLine" id="cb14-5" data-line-number="5"><span class="co"># Non-EUCAST: inherit ampicillin results for unavailable amoxicillin (no changes)</span></a>
-<a class="sourceLine" id="cb14-6" data-line-number="6"><span class="co"># Non-EUCAST: set amoxicillin/clav acid = S where ampicillin = S (3,022 values changed)</span></a>
-<a class="sourceLine" id="cb14-7" data-line-number="7"><span class="co"># Non-EUCAST: set ampicillin = R where amoxicillin/clav acid = R (151 values changed)</span></a>
+<a class="sourceLine" id="cb14-6" data-line-number="6"><span class="co"># Non-EUCAST: set amoxicillin/clav acid = S where ampicillin = S (2,986 values changed)</span></a>
+<a class="sourceLine" id="cb14-7" data-line-number="7"><span class="co"># Non-EUCAST: set ampicillin = R where amoxicillin/clav acid = R (176 values changed)</span></a>
 <a class="sourceLine" id="cb14-8" data-line-number="8"><span class="co"># Non-EUCAST: set piperacillin = R where piperacillin/tazobactam = R (no changes)</span></a>
 <a class="sourceLine" id="cb14-9" data-line-number="9"><span class="co"># Non-EUCAST: set piperacillin/tazobactam = S where piperacillin = S (no changes)</span></a>
 <a class="sourceLine" id="cb14-10" data-line-number="10"><span class="co"># Non-EUCAST: set trimethoprim = R where trimethoprim/sulfa = R (no changes)</span></a>
@@ -448,14 +448,14 @@
 <a class="sourceLine" id="cb14-29" data-line-number="29"><span class="co"># Pasteurella multocida (no changes)</span></a>
 <a class="sourceLine" id="cb14-30" data-line-number="30"><span class="co"># Staphylococcus (no changes)</span></a>
 <a class="sourceLine" id="cb14-31" data-line-number="31"><span class="co"># Streptococcus groups A, B, C, G (no changes)</span></a>
-<a class="sourceLine" id="cb14-32" data-line-number="32"><span class="co"># Streptococcus pneumoniae (1,071 values changed)</span></a>
+<a class="sourceLine" id="cb14-32" data-line-number="32"><span class="co"># Streptococcus pneumoniae (1,015 values changed)</span></a>
 <a class="sourceLine" id="cb14-33" data-line-number="33"><span class="co"># Viridans group streptococci (no changes)</span></a>
 <a class="sourceLine" id="cb14-34" data-line-number="34"><span class="co"># </span></a>
 <a class="sourceLine" id="cb14-35" data-line-number="35"><span class="co"># EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)</span></a>
-<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,282 values changed)</span></a>
+<a class="sourceLine" id="cb14-36" data-line-number="36"><span class="co"># Table 01: Intrinsic resistance in Enterobacteriaceae (1,284 values changed)</span></a>
 <a class="sourceLine" id="cb14-37" data-line-number="37"><span class="co"># Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria (no changes)</span></a>
 <a class="sourceLine" id="cb14-38" data-line-number="38"><span class="co"># Table 03: Intrinsic resistance in other Gram-negative bacteria (no changes)</span></a>
-<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,783 values changed)</span></a>
+<a class="sourceLine" id="cb14-39" data-line-number="39"><span class="co"># Table 04: Intrinsic resistance in Gram-positive bacteria (2,796 values changed)</span></a>
 <a class="sourceLine" id="cb14-40" data-line-number="40"><span class="co"># Table 08: Interpretive rules for B-lactam agents and Gram-positive cocci (no changes)</span></a>
 <a class="sourceLine" id="cb14-41" data-line-number="41"><span class="co"># Table 09: Interpretive rules for B-lactam agents and Gram-negative rods (no changes)</span></a>
 <a class="sourceLine" id="cb14-42" data-line-number="42"><span class="co"># Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins (no changes)</span></a>
@@ -463,15 +463,15 @@
 <a class="sourceLine" id="cb14-44" data-line-number="44"><span class="co"># Table 13: Interpretive rules for quinolones (no changes)</span></a>
 <a class="sourceLine" id="cb14-45" data-line-number="45"><span class="co"># </span></a>
 <a class="sourceLine" id="cb14-46" data-line-number="46"><span class="co"># --------------------------------------------------------------------------</span></a>
-<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># EUCAST rules affected 6,586 out of 20,000 rows, making a total of 8,309 edits</span></a>
+<a class="sourceLine" id="cb14-47" data-line-number="47"><span class="co"># EUCAST rules affected 6,569 out of 20,000 rows, making a total of 8,257 edits</span></a>
 <a class="sourceLine" id="cb14-48" data-line-number="48"><span class="co"># =&gt; added 0 test results</span></a>
 <a class="sourceLine" id="cb14-49" data-line-number="49"><span class="co"># </span></a>
-<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># =&gt; changed 8,309 test results</span></a>
-<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co">#    - 129 test results changed from S to I</span></a>
-<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co">#    - 4,834 test results changed from S to R</span></a>
-<a class="sourceLine" id="cb14-53" data-line-number="53"><span class="co">#    - 1,222 test results changed from I to S</span></a>
-<a class="sourceLine" id="cb14-54" data-line-number="54"><span class="co">#    - 324 test results changed from I to R</span></a>
-<a class="sourceLine" id="cb14-55" data-line-number="55"><span class="co">#    - 1,800 test results changed from R to S</span></a>
+<a class="sourceLine" id="cb14-50" data-line-number="50"><span class="co"># =&gt; changed 8,257 test results</span></a>
+<a class="sourceLine" id="cb14-51" data-line-number="51"><span class="co">#    - 123 test results changed from S to I</span></a>
+<a class="sourceLine" id="cb14-52" data-line-number="52"><span class="co">#    - 4,779 test results changed from S to R</span></a>
+<a class="sourceLine" id="cb14-53" data-line-number="53"><span class="co">#    - 1,134 test results changed from I to S</span></a>
+<a class="sourceLine" id="cb14-54" data-line-number="54"><span class="co">#    - 369 test results changed from I to R</span></a>
+<a class="sourceLine" id="cb14-55" data-line-number="55"><span class="co">#    - 1,852 test results changed from R to S</span></a>
 <a class="sourceLine" id="cb14-56" data-line-number="56"><span class="co"># --------------------------------------------------------------------------</span></a>
 <a class="sourceLine" id="cb14-57" data-line-number="57"><span class="co"># </span></a>
 <a class="sourceLine" id="cb14-58" data-line-number="58"><span class="co"># Use eucast_rules(..., verbose = TRUE) (on your original data) to get a data.frame with all specified edits instead.</span></a></code></pre></div>
@@ -499,8 +499,8 @@
 <a class="sourceLine" id="cb16-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `bacteria` as input for `col_mo`.</span></a>
 <a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `date` as input for `col_date`.</span></a>
 <a class="sourceLine" id="cb16-5" data-line-number="5"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
-<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,688 first isolates (28.4% of total)</span></a></code></pre></div>
-<p>So only 28.4% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
+<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="co"># =&gt; Found 5,699 first isolates (28.5% of total)</span></a></code></pre></div>
+<p>So only 28.5% is suitable for resistance analysis! We can now filter on it with the <code><a href="https://dplyr.tidyverse.org/reference/filter.html">filter()</a></code> function, also from the <code>dplyr</code> package:</p>
 <div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
 <a class="sourceLine" id="cb17-2" data-line-number="2"><span class="st">  </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(first <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>)</a></code></pre></div>
 <p>For future use, the above two syntaxes can be shortened with the <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> function:</p>
@@ -510,7 +510,7 @@
 <div id="first-weighted-isolates" class="section level2">
 <h2 class="hasAnchor">
 <a href="#first-weighted-isolates" class="anchor"></a>First <em>weighted</em> isolates</h2>
-<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient I9, sorted on date:</p>
+<p>We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient X7, sorted on date:</p>
 <table class="table">
 <thead><tr class="header">
 <th align="center">isolate</th>
@@ -526,19 +526,19 @@
 <tbody>
 <tr class="odd">
 <td align="center">1</td>
-<td align="center">2010-02-08</td>
-<td align="center">I9</td>
+<td align="center">2010-03-18</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">R</td>
+<td align="center">S</td>
 <td align="center">S</td>
 <td align="center">TRUE</td>
 </tr>
 <tr class="even">
 <td align="center">2</td>
-<td align="center">2010-03-05</td>
-<td align="center">I9</td>
+<td align="center">2010-04-28</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
@@ -548,30 +548,30 @@
 </tr>
 <tr class="odd">
 <td align="center">3</td>
-<td align="center">2010-05-14</td>
-<td align="center">I9</td>
+<td align="center">2010-06-26</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
+<td align="center">R</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">R</td>
 <td align="center">FALSE</td>
 </tr>
 <tr class="even">
 <td align="center">4</td>
-<td align="center">2010-12-10</td>
-<td align="center">I9</td>
+<td align="center">2010-08-06</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
-<td align="center">R</td>
 <td align="center">S</td>
-<td align="center">R</td>
+<td align="center">S</td>
+<td align="center">S</td>
 <td align="center">S</td>
 <td align="center">FALSE</td>
 </tr>
 <tr class="odd">
 <td align="center">5</td>
-<td align="center">2010-12-17</td>
-<td align="center">I9</td>
+<td align="center">2010-08-31</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
@@ -581,19 +581,19 @@
 </tr>
 <tr class="even">
 <td align="center">6</td>
-<td align="center">2011-04-18</td>
-<td align="center">I9</td>
+<td align="center">2010-10-15</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
+<td align="center">R</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">S</td>
-<td align="center">TRUE</td>
+<td align="center">FALSE</td>
 </tr>
 <tr class="odd">
 <td align="center">7</td>
-<td align="center">2011-04-25</td>
-<td align="center">I9</td>
+<td align="center">2010-11-19</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">R</td>
 <td align="center">S</td>
@@ -603,8 +603,8 @@
 </tr>
 <tr class="even">
 <td align="center">8</td>
-<td align="center">2011-06-06</td>
-<td align="center">I9</td>
+<td align="center">2011-01-20</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
@@ -614,23 +614,23 @@
 </tr>
 <tr class="odd">
 <td align="center">9</td>
-<td align="center">2011-07-14</td>
-<td align="center">I9</td>
+<td align="center">2011-04-10</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">FALSE</td>
+<td align="center">TRUE</td>
 </tr>
 <tr class="even">
 <td align="center">10</td>
-<td align="center">2011-07-31</td>
-<td align="center">I9</td>
+<td align="center">2011-04-12</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">R</td>
+<td align="center">S</td>
 <td align="center">S</td>
 <td align="center">FALSE</td>
 </tr>
@@ -647,7 +647,7 @@
 <a class="sourceLine" id="cb19-7" data-line-number="7"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `patient_id` as input for `col_patient_id`.</span></a>
 <a class="sourceLine" id="cb19-8" data-line-number="8"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `keyab` as input for `col_keyantibiotics`. Use col_keyantibiotics = FALSE to prevent this.</span></a>
 <a class="sourceLine" id="cb19-9" data-line-number="9"><span class="co"># [Criterion] Inclusion based on key antibiotics, ignoring I</span></a>
-<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,051 first weighted isolates (75.3% of total)</span></a></code></pre></div>
+<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># =&gt; Found 15,085 first weighted isolates (75.4% of total)</span></a></code></pre></div>
 <table class="table">
 <thead><tr class="header">
 <th align="center">isolate</th>
@@ -664,92 +664,92 @@
 <tbody>
 <tr class="odd">
 <td align="center">1</td>
-<td align="center">2010-02-08</td>
-<td align="center">I9</td>
+<td align="center">2010-03-18</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">R</td>
+<td align="center">S</td>
 <td align="center">S</td>
 <td align="center">TRUE</td>
 <td align="center">TRUE</td>
 </tr>
 <tr class="even">
 <td align="center">2</td>
-<td align="center">2010-03-05</td>
-<td align="center">I9</td>
+<td align="center">2010-04-28</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">FALSE</td>
-<td align="center">TRUE</td>
+<td align="center">FALSE</td>
 </tr>
 <tr class="odd">
 <td align="center">3</td>
-<td align="center">2010-05-14</td>
-<td align="center">I9</td>
+<td align="center">2010-06-26</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
+<td align="center">R</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">R</td>
 <td align="center">FALSE</td>
 <td align="center">TRUE</td>
 </tr>
 <tr class="even">
 <td align="center">4</td>
-<td align="center">2010-12-10</td>
-<td align="center">I9</td>
+<td align="center">2010-08-06</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
-<td align="center">R</td>
 <td align="center">S</td>
-<td align="center">R</td>
+<td align="center">S</td>
+<td align="center">S</td>
 <td align="center">S</td>
 <td align="center">FALSE</td>
 <td align="center">TRUE</td>
 </tr>
 <tr class="odd">
 <td align="center">5</td>
-<td align="center">2010-12-17</td>
-<td align="center">I9</td>
+<td align="center">2010-08-31</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">FALSE</td>
-<td align="center">TRUE</td>
+<td align="center">FALSE</td>
 </tr>
 <tr class="even">
 <td align="center">6</td>
-<td align="center">2011-04-18</td>
-<td align="center">I9</td>
+<td align="center">2010-10-15</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
+<td align="center">R</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">S</td>
-<td align="center">TRUE</td>
+<td align="center">FALSE</td>
 <td align="center">TRUE</td>
 </tr>
 <tr class="odd">
 <td align="center">7</td>
-<td align="center">2011-04-25</td>
-<td align="center">I9</td>
+<td align="center">2010-11-19</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">R</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">FALSE</td>
-<td align="center">TRUE</td>
+<td align="center">FALSE</td>
 </tr>
 <tr class="even">
 <td align="center">8</td>
-<td align="center">2011-06-06</td>
-<td align="center">I9</td>
+<td align="center">2011-01-20</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
@@ -760,35 +760,35 @@
 </tr>
 <tr class="odd">
 <td align="center">9</td>
-<td align="center">2011-07-14</td>
-<td align="center">I9</td>
+<td align="center">2011-04-10</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">FALSE</td>
-<td align="center">FALSE</td>
+<td align="center">TRUE</td>
+<td align="center">TRUE</td>
 </tr>
 <tr class="even">
 <td align="center">10</td>
-<td align="center">2011-07-31</td>
-<td align="center">I9</td>
+<td align="center">2011-04-12</td>
+<td align="center">X7</td>
 <td align="center">B_ESCHR_COLI</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">R</td>
+<td align="center">S</td>
 <td align="center">S</td>
 <td align="center">FALSE</td>
-<td align="center">TRUE</td>
+<td align="center">FALSE</td>
 </tr>
 </tbody>
 </table>
-<p>Instead of 2, now 9 isolates are flagged. In total, 75.3% of all isolates are marked ‘first weighted’ - 46.8% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
+<p>Instead of 2, now 6 isolates are flagged. In total, 75.4% of all isolates are marked ‘first weighted’ - 46.9% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.</p>
 <p>As with <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code>, there’s a shortcut for this new algorithm too:</p>
 <div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data <span class="op">%&gt;%</span><span class="st"> </span></a>
 <a class="sourceLine" id="cb20-2" data-line-number="2"><span class="st">  </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_weighted_isolate</a></span>()</a></code></pre></div>
-<p>So we end up with 15,051 isolates for analysis.</p>
+<p>So we end up with 15,085 isolates for analysis.</p>
 <p>We can remove unneeded columns:</p>
 <div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">data_1st &lt;-<span class="st"> </span>data_1st <span class="op">%&gt;%</span><span class="st"> </span></a>
 <a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st">  </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span><span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(first, keyab))</a></code></pre></div>
@@ -813,57 +813,25 @@
 </tr></thead>
 <tbody>
 <tr class="odd">
-<td>2</td>
-<td align="center">2017-06-27</td>
-<td align="center">H4</td>
-<td align="center">Hospital C</td>
+<td>1</td>
+<td align="center">2011-03-27</td>
+<td align="center">O9</td>
+<td align="center">Hospital B</td>
 <td align="center">B_ESCHR_COLI</td>
-<td align="center">R</td>
-<td align="center">R</td>
 <td align="center">S</td>
 <td align="center">S</td>
-<td align="center">M</td>
+<td align="center">S</td>
+<td align="center">S</td>
+<td align="center">F</td>
 <td align="center">Gram-negative</td>
 <td align="center">Escherichia</td>
 <td align="center">coli</td>
 <td align="center">TRUE</td>
 </tr>
 <tr class="even">
-<td>3</td>
-<td align="center">2012-05-31</td>
-<td align="center">X3</td>
-<td align="center">Hospital B</td>
-<td align="center">B_STRPT_PNMN</td>
-<td align="center">I</td>
-<td align="center">I</td>
-<td align="center">S</td>
-<td align="center">R</td>
-<td align="center">F</td>
-<td align="center">Gram-positive</td>