(v0.9.0.9026) update documentation

v1.8.2
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@ -1,6 +1,6 @@
Package: AMR
Version: 0.9.0.9025
Date: 2020-02-16
Version: 0.9.0.9026
Date: 2020-02-17
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),
@ -28,9 +28,7 @@ Authors@R: c(
person(role = "ctb",
family = "Ny", given = "Sofia", email = "sofia.ny@folkhalsomyndigheten.se"),
person(role = "ctb",
family = "Souverein", given = "Dennis", email = "d.souvereing@streeklabhaarlem.nl"),
person(role = "fnd",
given = "Stichting Certe Medische Diagnostiek en Advies", email = "medischedataanalyse@certe.nl"))
family = "Souverein", given = "Dennis", email = "d.souvereing@streeklabhaarlem.nl"))
Description: Functions to simplify the analysis and prediction of Antimicrobial
Resistance (AMR) and to work with microbial and antimicrobial properties by
using evidence-based methods, like those defined by Leclercq et al. (2013)

@ -1,9 +1,9 @@
# AMR 0.9.0.9025
## <small>Last updated: 16-Feb-2020</small>
# AMR 0.9.0.9026
## <small>Last updated: 17-Feb-2020</small>
### New
* Support for the newest [EUCAST Clinical Breakpoint Tables v.10.0](http://www.eucast.org/clinical_breakpoints/), valid from 2020-01-01 (use `as.rsi()` to transform MICs and disk zones)
* The repository of this package now contains a clean version of the EUCAST and CLSI guidelines from 2011-2020 to translate MIC and disk diffusion values to R/SI: https://gitlab.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt. This **allows for machine reading these guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. This file is updated automatically.
* Support for the newest [EUCAST Clinical Breakpoint Tables v.10.0](http://www.eucast.org/clinical_breakpoints/), valid from 1 January 2020. This affects translation of MIC and disk zones using `as.rsi()` and inferred resistance and susceptibility using `eucast_rules()`.
* The repository of this package now contains a clean version of the EUCAST and CLSI guidelines from 2011-2020 to translate MIC and disk diffusion values to R/SI: <https://gitlab.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt>. This **allows for machine reading these guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. This file used to process the EUCAST Clinical Breakpoints Excel file [can be found here](https://gitlab.com/msberends/AMR/blob/master/data-raw/read_EUCAST.R).
* Support for LOINC and SNOMED codes
* Support for LOINC codes in the `antibiotics` data set. Use `ab_loinc()` to retrieve LOINC codes, or use a LOINC code for input in any `ab_*` function:
```r

@ -38,15 +38,17 @@
#' - Getting properties for any microorganism (like Gram stain, species, genus or family)
#' - Getting properties for any antibiotic (like name, EARS-Net code, ATC code, PubChem code, defined daily dose or trade name)
#' - Plotting antimicrobial resistance
#' - Applying EUCAST expert rules
#' - Getting SNOMED codes of a microorganism, or get its name associated with a SNOMED code
#' - Getting LOINC codes of an antibiotic, or get its name associated with a LOINC code
#' - Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI
#' @section Read more on our website!:
#' On our website <https://msberends.gitlab.io/AMR> you can find [a tutorial](https://msberends.gitlab.io/AMR/articles/AMR.html) about how to conduct AMR analysis, the [complete documentation of all functions](https://msberends.gitlab.io/AMR/reference) (which reads a lot easier than here in R) and [an example analysis using WHONET data](https://msberends.gitlab.io/AMR/articles/WHONET.html).
#' On our website <https://msberends.gitlab.io/AMR> you can find [a comprehensive tutorial](https://msberends.gitlab.io/AMR/articles/AMR.html) about how to conduct AMR analysis, the [complete documentation of all functions](https://msberends.gitlab.io/AMR/reference) (which reads a lot easier than here in R) and [an example analysis using WHONET data](https://msberends.gitlab.io/AMR/articles/WHONET.html).
#' @section Contact us:
#' For suggestions, comments or questions, please contact us at:
#'
#' Matthijs S. Berends \cr
#' m.s.berends at umcg dot nl \cr
#' m.s.berends \[at\] umcg \[dot\] nl \cr
#' Department of Medical Microbiology, University of Groningen \cr
#' University Medical Center Groningen \cr
#' Post Office Box 30001 \cr

@ -205,8 +205,8 @@ catalogue_of_life <- list(
#' - `ab`\cr Antibiotic ID, see [as.ab()]
#' - `ref_tbl`\cr Info about where the guideline rule can be found
#' - `disk_dose`\cr Dose of the used disk diffusion method
#' - `breakpoint_S`\cr Lowest MIC value or highest number of millimeters that leads to "S"
#' - `breakpoint_R`\cr Highest MIC value or lowest number of millimeters that leads to "R"
#' - `breakpoint_S`\cr Lowest MIC value or highest number of millimetres that leads to "S"
#' - `breakpoint_R`\cr Highest MIC value or lowest number of millimetres that leads to "R"
#' @details The repository of this `AMR` package contains a file comprising this exact data set: <https://gitlab.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt>. This file **allows for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. This file is updated automatically.
#' @inheritSection AMR Read more on our website!
"rsi_translation"

@ -21,7 +21,7 @@
#' Class 'disk'
#'
#' This transforms a vector to a new class [`disk`], which is a growth zone size (around an antibiotic disk) in millimeters between 6 and 50.
#' This transforms a vector to a new class [`disk`], which is a growth zone size (around an antibiotic disk) in millimetres between 6 and 50.
#' @inheritSection lifecycle Stable lifecycle
#' @rdname as.disk
#' @param x vector
@ -33,15 +33,22 @@
#' @seealso [as.rsi()]
#' @inheritSection AMR Read more on our website!
#' @examples
#' # interpret disk values
#' as.rsi(x = 12,
#' mo = as.mo("S. pneumoniae"),
#' ab = "AMX",
#' # transform existing disk zones to the `disk` class
#' df <- data.frame(microorganism = "E. coli",
#' AMP = 20,
#' CIP = 14,
#' GEN = 18,
#' TOB = 16)
#' df <- df %>% mutate_at(vars(AMP:TOB, as.disk))
#' df
#'
#' # interpret disk values, see ?as.rsi
#' as.rsi(x = as.disk(18),
#' mo = "Strep pneu", # `mo` will be coerced with as.mo()
#' ab = "ampicillin", # and `ab` with as.ab()
#' guideline = "EUCAST")
#' as.rsi(x = 12,
#' mo = as.mo("S. pneumoniae"),
#' ab = "AMX",
#' guideline = "CLSI")
#'
#' as.rsi(df)
as.disk <- function(x, na.rm = FALSE) {
if (is.disk(x)) {
x

@ -20,7 +20,7 @@
# ==================================================================== #
# global variables
EUCAST_VERSION_BREAKPOINTS <- "9.0, 2019"
EUCAST_VERSION_BREAKPOINTS <- "10.0, 2020"
EUCAST_VERSION_EXPERT_RULES <- "3.1, 2016"
#' Apply EUCAST rules
@ -655,9 +655,11 @@ eucast_rules <- function(x,
cat(bold(
case_when(
rule_group_current %like% "breakpoint" ~
paste0("\nEUCAST Clinical Breakpoints (v", EUCAST_VERSION_BREAKPOINTS, ")\n"),
paste0("\nEUCAST Clinical Breakpoints (",
red(paste0("v", EUCAST_VERSION_BREAKPOINTS)), ")\n"),
rule_group_current %like% "expert" ~
paste0("\nEUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v", EUCAST_VERSION_EXPERT_RULES, ")\n"),
paste0("\nEUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (",
red(paste0("v", EUCAST_VERSION_EXPERT_RULES)), ")\n"),
TRUE ~
"\nOther rules by this AMR package\n"
)

@ -21,7 +21,7 @@
#' Calculate microbial resistance
#'
#' @description These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in [dplyr::summarise()] and support grouped variables, please see *Examples*.
#' @description These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in `summarise()`][dplyr::summarise()] and also support grouped variables, please see *Examples*.
#'
#' [resistance()] should be used to calculate resistance, [susceptibility()] should be used to calculate susceptibility.\cr
#' @inheritSection lifecycle Stable lifecycle
@ -40,11 +40,11 @@
#'
#' **Remember that you should filter your table to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set.
#'
#' These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the [AMR::count()] functions to count isolates. The function [susceptibility()] is essentially equal to `count_susceptible() / count_all()`. *Low counts can infuence the outcome - the `proportion` functions may camouflage this, since they only return the proportion (albeit being dependent on the `minimum` parameter).*
#' These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the `count()`][AMR::count()] functions to count isolates. The function [susceptibility()] is essentially equal to `count_susceptible() / count_all()`. *Low counts can influence the outcome - the `proportion` functions may camouflage this, since they only return the proportion (albeit being dependent on the `minimum` parameter).*
#'
#' The function [proportion_df()] takes any variable from `data` that has an [`rsi`] class (created with [as.rsi()]) and calculates the proportions R, I and S. The function [rsi_df()] works exactly like [proportion_df()], but adds the number of isolates.
#' @section Combination therapy:
#' When using more than one variable for `...` (= combination therapy)), use `only_all_tested` to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Antibiotic A and Antibiotic B, about how [susceptibility()] works to calculate the %SI:
#' When using more than one variable for `...` (= combination therapy)), use `only_all_tested` to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Drug A and Drug B, about how [susceptibility()] works to calculate the %SI:
#'
#' ```
#' --------------------------------------------------------------------

@ -24,9 +24,9 @@
#' Interpret MIC values and disk diffusion diameters according to EUCAST or CLSI, or clean up existing R/SI values. This transforms the input to a new class [`rsi`], which is an ordered factor with levels `S < I < R`. Invalid antimicrobial interpretations will be translated as `NA` with a warning.
#' @inheritSection lifecycle Stable lifecycle
#' @rdname as.rsi
#' @param x vector of values (for class [`mic`]: an MIC value in mg/L, for class [`disk`]: a disk diffusion radius in millimeters)
#' @param mo a microorganism code, generated with [as.mo()]
#' @param ab an antimicrobial code, generated with [as.ab()]
#' @param x vector of values (for class [`mic`]: an MIC value in mg/L, for class [`disk`]: a disk diffusion radius in millimetres)
#' @param mo any (vector of) text that can be coerced to a valid microorganism code with [as.mo()]
#' @param ab any (vector of) text that can be coerced to a valid antimicrobial code with [as.ab()]
#' @inheritParams first_isolate
#' @param guideline defaults to the latest included EUCAST guideline, run `unique(rsi_translation$guideline)` for all options
#' @param threshold maximum fraction of invalid antimicrobial interpretations of `x`, please see *Examples*
@ -71,8 +71,10 @@
#'
#' # a whole data set, even with combined MIC values and disk zones
#' df <- data.frame(microorganism = "E. coli",
#' AMP = as.mic(12),
#' GEN = as.disk(18))
#' AMP = as.mic(8),
#' CIP = as.mic(0.256),
#' GEN = as.disk(18),
#' TOB = as.disk(16))
#' as.rsi(df)
#'
#'
@ -239,12 +241,12 @@ exec_as.rsi <- function(method, x, mo, ab, guideline) {
if (guideline_coerced != guideline) {
message(blue(paste0("Note: Using guideline ", bold(guideline_coerced), " as input for `guideline`.")))
}
new_rsi <- rep(NA_character_, length(x))
trans <- rsi_translation %>%
filter(guideline == guideline_coerced & method == method_param) %>%
mutate(lookup = paste(mo, ab))
lookup_mo <- paste(mo, ab)
lookup_genus <- paste(mo_genus, ab)
lookup_family <- paste(mo_family, ab)

Binary file not shown.

@ -186,7 +186,3 @@ template:
params:
noindex: false
bootswatch: "flatly"
docsearch:
# using algolia.com
api_key: "f737050abfd4d726c63938e18f8c496e"
index_name: "amr"

@ -5,7 +5,7 @@
# and all separate EARS-Net letter codes like 'AMC'. They can be separated by comma: 'AMC, fluoroquinolones'.
# The 'if_mo_property' column can be any column name from the AMR::microorganisms data set, or "genus_species" or "gramstain".
# The like.is.one_of column must be 'like' or 'is' or 'one_of' ('like' will read the 'this_value' column as regular expression)
# The EUCAST guideline contains references to the 'Burkholderia cepacia complex'. All species in this group can be found in: LiPuma J (2005, PMID 16217180).
# The EUCAST guideline contains references to the 'Burkholderia cepacia complex'. All species in this group are noted on the 'B.cepacia' sheet of the EUCAST Clinical Breakpoint v.10.0 Excel file of 2020 (v_10.0_Breakpoint_Tables.xlsx).
# >>>>> IF YOU WANT TO IMPORT THIS FILE INTO YOUR OWN SOFTWARE, HAVE THE FIRST 10 LINES SKIPPED <<<<<
# -------------------------------------------------------------------------------------------------------------------------------
if_mo_property like.is.one_of this_value and_these_antibiotics have_these_values then_change_these_antibiotics to_value reference.rule reference.rule_group
@ -37,7 +37,6 @@ genus is Staphylococcus ERY S AZM, CLR, RXT S Staphylococcus Breakpoints
genus is Staphylococcus ERY I AZM, CLR, RXT I Staphylococcus Breakpoints
genus is Staphylococcus ERY R AZM, CLR, RXT R Staphylococcus Breakpoints
genus is Staphylococcus TCY S DOX, MNO S Staphylococcus Breakpoints
genus_species is Enterococcus faecium AMP R all_betalactams R Enterococcus Breakpoints
genus is Enterococcus AMP S AMX, AMC, PIP, TZP S Enterococcus Breakpoints
genus is Enterococcus AMP I AMX, AMC, PIP, TZP I Enterococcus Breakpoints
genus is Enterococcus AMP R AMX, AMC, PIP, TZP R Enterococcus Breakpoints
@ -47,7 +46,8 @@ genus is Enterococcus NOR R CIP, LVX R Enterococcus Breakpoints
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ PEN S aminopenicillins, ureidopenicillins, cephalosporins_except_CAZ, carbapenems, FLC, AMC S Streptococcus groups A, B, C, G Breakpoints
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ PEN I aminopenicillins, ureidopenicillins, cephalosporins_except_CAZ, carbapenems, FLC, AMC I Streptococcus groups A, B, C, G Breakpoints
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ PEN R aminopenicillins, ureidopenicillins, cephalosporins_except_CAZ, carbapenems, FLC, AMC R Streptococcus groups A, B, C, G Breakpoints
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ NOR S LVX, MFX S Streptococcus groups A, B, C, G Breakpoints
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ NOR S MFX S Streptococcus groups A, B, C, G Breakpoints
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ NOR S LVX I Streptococcus groups A, B, C, G Breakpoints
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ ERY S AZM, CLR, RXT S Streptococcus groups A, B, C, G Breakpoints
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ ERY I AZM, CLR, RXT I Streptococcus groups A, B, C, G Breakpoints
genus_species like ^Streptococcus (pyogenes|agalactiae|dysgalactiae|group A|group B|group C|group G)$ ERY R AZM, CLR, RXT R Streptococcus groups A, B, C, G Breakpoints
@ -56,7 +56,8 @@ genus_species is Streptococcus pneumoniae PEN S AMP, AMX, AMC, PIP, TZP S Strept
genus_species is Streptococcus pneumoniae AMP S AMX, AMC, PIP, TZP S Streptococcus pneumoniae Breakpoints
genus_species is Streptococcus pneumoniae AMP I AMX, AMC, PIP, TZP I Streptococcus pneumoniae Breakpoints
genus_species is Streptococcus pneumoniae AMP R AMX, AMC, PIP, TZP R Streptococcus pneumoniae Breakpoints
genus_species is Streptococcus pneumoniae NOR S LVX, MFX S Streptococcus pneumoniae Breakpoints
genus_species is Streptococcus pneumoniae NOR S MFX S Streptococcus pneumoniae Breakpoints
genus_species is Streptococcus pneumoniae NOR S LVX I Streptococcus pneumoniae Breakpoints
genus_species is Streptococcus pneumoniae ERY S AZM, CLR, RXT S Streptococcus pneumoniae Breakpoints
genus_species is Streptococcus pneumoniae ERY I AZM, CLR, RXT I Streptococcus pneumoniae Breakpoints
genus_species is Streptococcus pneumoniae ERY R AZM, CLR, RXT R Streptococcus pneumoniae Breakpoints
@ -122,6 +123,11 @@ genus_species is Kingella kingae ERY S AZM, CLR S Kingella kingae Breakpoints
genus_species is Kingella kingae ERY I AZM, CLR I Kingella kingae Breakpoints
genus_species is Kingella kingae ERY R AZM, CLR R Kingella kingae Breakpoints
genus_species is Kingella kingae TCY S DOX S Kingella kingae Breakpoints
genus_species is Kingella kingae TCY I DOX I Kingella kingae Breakpoints
genus_species is Kingella kingae TCY R DOX R Kingella kingae Breakpoints
genus_species is Burkholderia pseudomallei TCY S DOX S Burkholderia pseudomallei Breakpoints
genus_species is Burkholderia pseudomallei TCY I DOX I Burkholderia pseudomallei Breakpoints
genus_species is Burkholderia pseudomallei TCY R DOX R Burkholderia pseudomallei Breakpoints
order is Enterobacterales PEN, glycopeptides, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
fullname like ^Citrobacter (koseri|amalonaticus|sedlakii|farmeri|rodentium) aminopenicillins, TIC R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
fullname like ^Citrobacter (freundii|braakii|murliniae|werkmanii|youngae) aminopenicillins, AMC, CZO, FOX R Table 01: Intrinsic resistance in Enterobacteriaceae Expert Rules
@ -146,7 +152,7 @@ genus_species is Acinetobacter pittii aminopenicillins, AMC, CZO, CTX, CRO, AT
genus_species is Acinetobacter nosocomialis aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
genus_species is Acinetobacter calcoaceticus aminopenicillins, AMC, CZO, CTX, CRO, ATM, ETP, TMP, FOS, DOX, TCY R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
genus_species is Achromobacter xylosoxidans aminopenicillins, CZO, CTX, CRO, ETP R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
fullname like ^Burkholderia (cepacia|multivorans|cenocepacia|stabilis|vietnamiensis|dolosa|ambifaria|anthina|pyrrocinia|ubonensis) aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, ATM, ETP, CIP, CHL, aminoglycosides, TMP, FOS, polymyxins R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
fullname like ^Burkholderia (ambifaria|anthina|arboris|cepacia|cenocepacia|contaminans|diffusa|dolosa|lata|latens|metallica|multivorans|paludis|pseudomultivorans|pyrrocinia|pseudomultivorans|seminalis|stabilis|stagnalis|territorii|ubonensis|vietnamiensis) aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, ATM, ETP, CIP, CHL, aminoglycosides, TMP, FOS, polymyxins R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
genus_species is Elizabethkingia meningoseptica aminopenicillins, AMC, TIC, CZO, CTX, CRO, CAZ, FEP, ATM, ETP, IPM, MEM, polymyxins R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
genus_species is Ochrobactrum anthropi aminopenicillins, AMC, TIC, PIP, TZP, CZO, CTX, CRO, CAZ, FEP, ATM, ETP R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules
genus_species is Pseudomonas aeruginosa aminopenicillins, AMC, CZO, CTX, CRO, ETP, CHL, KAN, NEO, TMP, SXT, tetracyclines, TGC R Table 02: Intrinsic resistance in non-fermentative Gram-negative bacteria Expert Rules

Can't render this file because it contains an unexpected character in line 6 and column 96.

@ -31,7 +31,7 @@ eucast_rules_file <- utils::read.delim(file = "data-raw/eucast_rules.tsv",
header = TRUE,
strip.white = TRUE,
na = c(NA, "", NULL))
# take the order of the reference.rule_group column in the orginal data file
# take the order of the reference.rule_group column in the original data file
eucast_rules_file$reference.rule_group <- factor(eucast_rules_file$reference.rule_group,
levels = unique(eucast_rules_file$reference.rule_group),
ordered = TRUE)

@ -24,6 +24,8 @@ library(dplyr)
library(cleaner)
library(AMR)
# USE THIS FUNCTION TO READ THE EUCAST EXCEL FILE THAT CONTAINS THE BREAKPOINT TABLES
read_EUCAST <- function(sheet, file = "data-raw/v_10.0_Breakpoint_Tables.xlsx") {
message("Getting sheet ", sheet)

@ -40,12 +40,6 @@
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@ -210,12 +204,6 @@
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@ -16,9 +16,7 @@
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@ -187,7 +179,7 @@
<h1>How to apply EUCAST rules</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">26 January 2020</h4>
<h4 class="date">17 February 2020</h4>
<div class="hidden name"><code>EUCAST.Rmd</code></div>
@ -203,25 +195,169 @@
<blockquote>
<p><em>EUCAST expert rules are a tabulated collection of expert knowledge on intrinsic resistances, exceptional resistance phenotypes and interpretive rules that may be applied to antimicrobial susceptibility testing in order to reduce errors and make appropriate recommendations for reporting particular resistances.</em></p>
</blockquote>
<p>In Europe, a lot of medical microbiological laboratories already apply these rules (<a href="https://www.eurosurveillance.org/content/10.2807/1560-7917.ES2015.20.2.21008">Brown <em>et al.</em>, 2015</a>). Our package features their latest insights on intrinsic resistance and exceptional phenotypes (version 9.0, 2019). Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function we use for this purpose can also apply additional rules, like forcing <help title="ATC: J01CA01">ampicillin</help> = R in isolates when <help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p>
<p>In Europe, a lot of medical microbiological laboratories already apply these rules (<a href="https://www.eurosurveillance.org/content/10.2807/1560-7917.ES2015.20.2.21008">Brown <em>et al.</em>, 2015</a>). Our package features their latest insights on intrinsic resistance and exceptional phenotypes (version 10.0, 2020). Moreover, the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function we use for this purpose can also apply additional rules, like forcing <help title="ATC: J01CA01">ampicillin</help> = R in isolates when <help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.</p>
</div>
<div id="examples" class="section level2">
<h2 class="hasAnchor">
<a href="#examples" class="anchor"></a>Examples</h2>
<p>These rules can be used to discard impossible bug-drug combinations in your data. For example, <em>Klebsiella</em> produces beta-lactamase that prevents ampicillin (or amoxicillin) from working against it. In other words, every strain of <em>Klebsiella</em> is resistant to ampicillin.</p>
<p>Sometimes, laboratory data can still contain such strains with ampicillin being susceptible to ampicillin. This could be because an antibiogram is available before an identification is available, and the antibiogram is then not re-interpreted based on the identification (namely, <em>Klebsiella</em>). EUCAST expert rules solves this:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1">oops &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="dt">mo =</span> <span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Klebsiella"</span>, </a>
<a class="sourceLine" id="cb1-2" data-line-number="2"> <span class="st">"Escherichia"</span>),</a>
<a class="sourceLine" id="cb1-3" data-line-number="3"> <span class="dt">ampicillin =</span> <span class="st">"S"</span>)</a>
<a class="sourceLine" id="cb1-4" data-line-number="4">oops</a>
<a class="sourceLine" id="cb1-5" data-line-number="5"><span class="co"># mo ampicillin</span></a>
<a class="sourceLine" id="cb1-6" data-line-number="6"><span class="co"># 1 Klebsiella S</span></a>
<a class="sourceLine" id="cb1-7" data-line-number="7"><span class="co"># 2 Escherichia S</span></a>
<a class="sourceLine" id="cb1-8" data-line-number="8"></a>
<a class="sourceLine" id="cb1-9" data-line-number="9"><span class="kw"><a href="../reference/eucast_rules.html">eucast_rules</a></span>(oops, <span class="dt">info =</span> <span class="ot">FALSE</span>)</a>
<a class="sourceLine" id="cb1-10" data-line-number="10"><span class="co"># mo ampicillin</span></a>
<a class="sourceLine" id="cb1-11" data-line-number="11"><span class="co"># 1 Klebsiella R</span></a>
<a class="sourceLine" id="cb1-12" data-line-number="12"><span class="co"># 2 Escherichia S</span></a></code></pre></div>
<p>These rules can be used to discard impossible bug-drug combinations in your data. For example, <em>Klebsiella</em> produces beta-lactamase that prevents ampicillin (or amoxicillin) from working against it. In other words, practically every strain of <em>Klebsiella</em> is resistant to ampicillin.</p>
<p>Sometimes, laboratory data can still contain such strains with ampicillin being susceptible to ampicillin. This could be because an antibiogram is available before an identification is available, and the antibiogram is then not re-interpreted based on the identification (namely, <em>Klebsiella</em>). EUCAST expert rules solve this, that can be used with <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1"></a>oops &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="dt">mo =</span> <span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Klebsiella"</span>, </span>
<span id="cb1-2"><a href="#cb1-2"></a> <span class="st">"Escherichia"</span>),</span>
<span id="cb1-3"><a href="#cb1-3"></a> <span class="dt">ampicillin =</span> <span class="st">"S"</span>)</span>
<span id="cb1-4"><a href="#cb1-4"></a>oops</span>
<span id="cb1-5"><a href="#cb1-5"></a><span class="co"># mo ampicillin</span></span>
<span id="cb1-6"><a href="#cb1-6"></a><span class="co"># 1 Klebsiella S</span></span>
<span id="cb1-7"><a href="#cb1-7"></a><span class="co"># 2 Escherichia S</span></span>
<span id="cb1-8"><a href="#cb1-8"></a></span>
<span id="cb1-9"><a href="#cb1-9"></a><span class="kw"><a href="../reference/eucast_rules.html">eucast_rules</a></span>(oops, <span class="dt">info =</span> <span class="ot">FALSE</span>)</span>
<span id="cb1-10"><a href="#cb1-10"></a><span class="co"># mo ampicillin</span></span>
<span id="cb1-11"><a href="#cb1-11"></a><span class="co"># 1 Klebsiella R</span></span>
<span id="cb1-12"><a href="#cb1-12"></a><span class="co"># 2 Escherichia S</span></span></code></pre></div>
<p>EUCAST rules can not only be used for correction, they can also be used for filling in known resistance and susceptibility based on results of other antimicrobials drugs. This process is called <em>interpretive reading</em> and is part of the <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> function as well:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1"></a>data &lt;-<span class="st"> </span><span class="kw"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span>(<span class="dt">mo =</span> <span class="kw"><a href="https://rdrr.io/r/base/c.html">c</a></span>(<span class="st">"Staphylococcus aureus"</span>,</span>
<span id="cb2-2"><a href="#cb2-2"></a> <span class="st">"Enterococcus faecalis"</span>,</span>
<span id="cb2-3"><a href="#cb2-3"></a> <span class="st">"Escherichia coli"</span>,</span>
<span id="cb2-4"><a href="#cb2-4"></a> <span class="st">"Klebsiella pneumoniae"</span>,</span>
<span id="cb2-5"><a href="#cb2-5"></a> <span class="st">"Pseudomonas aeruginosa"</span>),</span>
<span id="cb2-6"><a href="#cb2-6"></a> <span class="dt">VAN =</span> <span class="st">"-"</span>, <span class="co"># Vancomycin</span></span>
<span id="cb2-7"><a href="#cb2-7"></a> <span class="dt">AMX =</span> <span class="st">"-"</span>, <span class="co"># Amoxicillin</span></span>
<span id="cb2-8"><a href="#cb2-8"></a> <span class="dt">COL =</span> <span class="st">"-"</span>, <span class="co"># Colistin</span></span>
<span id="cb2-9"><a href="#cb2-9"></a> <span class="dt">CAZ =</span> <span class="st">"-"</span>, <span class="co"># Ceftazidime</span></span>
<span id="cb2-10"><a href="#cb2-10"></a> <span class="dt">CXM =</span> <span class="st">"-"</span>, <span class="co"># Cefuroxime</span></span>
<span id="cb2-11"><a href="#cb2-11"></a> <span class="dt">PEN =</span> <span class="st">"S"</span>, <span class="co"># Penicillin G</span></span>
<span id="cb2-12"><a href="#cb2-12"></a> <span class="dt">FOX =</span> <span class="st">"S"</span>, <span class="co"># Cefoxitin</span></span>
<span id="cb2-13"><a href="#cb2-13"></a> <span class="dt">stringsAsFactors =</span> <span class="ot">FALSE</span>)</span></code></pre></div>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1"></a>data</span></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="left">mo</th>
<th align="center">VAN</th>
<th align="center">AMX</th>
<th align="center">COL</th>
<th align="center">CAZ</th>
<th align="center">CXM</th>
<th align="center">PEN</th>
<th align="center">FOX</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">Staphylococcus aureus</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="left">Enterococcus faecalis</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="odd">
<td align="left">Escherichia coli</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="left">Klebsiella pneumoniae</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="odd">
<td align="left">Pseudomonas aeruginosa</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
</tbody>
</table>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1"></a><span class="kw"><a href="../reference/eucast_rules.html">eucast_rules</a></span>(data, <span class="dt">info =</span> <span class="ot">FALSE</span>)</span></code></pre></div>
<table class="table">
<thead><tr class="header">
<th align="left">mo</th>
<th align="center">VAN</th>
<th align="center">AMX</th>
<th align="center">COL</th>
<th align="center">CAZ</th>
<th align="center">CXM</th>
<th align="center">PEN</th>
<th align="center">FOX</th>
</tr></thead>
<tbody>
<tr class="odd">
<td align="left">Staphylococcus aureus</td>
<td align="center">-</td>
<td align="center">S</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="left">Enterococcus faecalis</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="left">Escherichia coli</td>
<td align="center">R</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">R</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="left">Klebsiella pneumoniae</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">R</td>
<td align="center">S</td>
</tr>
<tr class="odd">
<td align="left">Pseudomonas aeruginosa</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">R</td>
<td align="center">R</td>
<td align="center">R</td>
</tr>
</tbody>
</table>
</div>
</div>
@ -253,20 +389,7 @@
</div>
<script src="https://cdnjs.cloudflare.com/ajax/libs/docsearch.js/2.6.1/docsearch.min.js" integrity="sha256-GKvGqXDznoRYHCwKXGnuchvKSwmx9SRMrZOTh2g4Sb0=" crossorigin="anonymous"></script><script>
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@ -40,12 +40,6 @@
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.9.0.9025</span>
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@ -210,12 +204,6 @@
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@ -250,7 +238,7 @@
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alexander W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.9.0.9026</span>
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@ -210,12 +204,6 @@
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@ -302,10 +290,6 @@
<p><strong>Dennis Souverein</strong>. Contributor.
</p>
</li>
<li>
<p><strong>Stichting Certe Medische Diagnostiek en Advies</strong>. Funder.
</p>
</li>
</ul>
</div>
@ -316,7 +300,7 @@
<footer>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alexander W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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@ -327,23 +311,6 @@
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@ -191,6 +191,9 @@ thead ~ tbody {
/* only when it has a header */
border-bottom: 2px solid black;
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th {
text-align: inherit;
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table a:not(.btn), .table a:not(.btn) {
text-decoration: inherit;
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@ -66,10 +66,8 @@ $( document ).ready(function() {
// edit footer
$('footer').html(
'<div>' +
'<p>' + $('footer .copyright p').html().replace(
"Developed by",
'<code>AMR</code> (for R). Developed at the <a href="https://www.rug.nl">University of Groningen</a>.<br>Authors:') + '</p>' +
'<a href="https://www.rug.nl"><img src="https://gitlab.com/msberends/AMR/raw/master/docs/logo_rug.png" class="footer_logo"></a>' +
'<p><code>AMR</code> (for R). Developed at the <a href="https://www.rug.nl">University of Groningen</a> in collaboration with non-profit organisations <a href="https://www.certe.nl">Certe Medical Diagnostics and Advice</a> and <a href="https://www.umcg.nl">University Medical Center Groningen</a>.</p>' +
'<a href="https://www.rug.nl"><img src="https://gitlab.com/msberends/AMR/raw/master/docs/logo_rug.png" class="footer_logo"></a>' +
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@ -16,9 +16,7 @@
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@ -170,13 +168,7 @@
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@ -423,7 +415,6 @@ A methods paper about this package has been preprinted at bioRxiv (DOI: 10.1101/
<a href="https://www.rug.nl/staff/c.j.albers/">Casper J. Albers</a> <br><small class="roles"> Author, thesis advisor </small> <a href="https://orcid.org/0000-0002-9213-6743" target="orcid.widget"><img src="https://members.orcid.org/sites/default/files/vector_iD_icon.svg" class="orcid" alt="ORCID"></a> </li>
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<a href="https://www.rug.nl/staff/c.glasner/">Corinna Glasner</a> <br><small class="roles"> Author, thesis advisor </small> <a href="https://orcid.org/0000-0003-1241-1328" target="orcid.widget"><img src="https://members.orcid.org/sites/default/files/vector_iD_icon.svg" class="orcid" alt="ORCID"></a> </li>
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<li><a href="authors.html">All authors...</a></li>
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@ -433,7 +424,7 @@ A methods paper about this package has been preprinted at bioRxiv (DOI: 10.1101/
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@ -444,20 +435,7 @@ A methods paper about this package has been preprinted at bioRxiv (DOI: 10.1101/
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<div id="amr-0909026" class="section level1">
<h1 class="page-header">
<a href="#amr-0909025" class="anchor"></a>AMR 0.9.0.9025<small> Unreleased </small>
<a href="#amr-0909026" class="anchor"></a>AMR 0.9.0.9026<small> Unreleased </small>
</h1>
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<h2 class="hasAnchor">
<a href="#last-updated-16-feb-2020" class="anchor"></a><small>Last updated: 16-Feb-2020