AMR 1.8.2This is a small intermediate update to include the reference to our publication in the Journal of Statistical Software, DOI 10.18637/jss.v104.i03.
A major update will be released by the end of 2022 or early 2023 to include the most recent EUCAST and CLSI guidelines, updated microbial taxonomy, and support for 16 languages.
AMR 1.8.1All functions in this package are considered to be stable. Updates to the AMR interpretation rules (such as by EUCAST and CLSI), the microbial taxonomy, and the antibiotic dosages will all be updated every 6 to 12 months.
Fix for using as.rsi() on values containing capped
values (such as >=), sometimes leading to
NA
Support for antibiotic interpretations of the MIPS laboratory
system: "U" for S (‘susceptible urine’), "D"
for I (‘susceptible dose-dependent’)
Improved algorithm of as.mo(), especially for
ignoring non-taxonomic text, such as:
mo_name("methicillin-resistant S. aureus (MRSA)")
#> [1] "Staphylococcus aureus"More informative warning messages
Added 192 as valid MIC
Updated MIC printing in tibbles
Increased speed for loading the package
AMR 1.8.0p_symbol() and all filter_*()
functions (except for filter_first_isolate()), which were
all deprecated in a previous package versionkey_antibiotics() and
key_antibiotics_equal() functions, which were deprecated
and superseded by key_antimicrobials() and
antimicrobials_equal()ggplot2::ggplot()
generics for classes <mic>,
<disk>, <rsi> and
<resistance_predict> as they did not follow the
ggplot2 logic. They were replaced with
ggplot2::autoplot() generics.get_locale() to
get_AMR_locale() to prevent conflicts with other
packagesSupport for the CLSI 2021 guideline for interpreting MIC/disk
diffusion values, which are incorporated in the
rsi_translation data set. This data set now more strictly
follows the WHONET software as well.
Support for EUCAST Intrinsic Resistance and Unusual Phenotypes
v3.3 (October 2021). This is now the default EUCAST guideline in the
package (all older guidelines are still available) for
eucast_rules(), mo_is_intrinsic_resistant()
and mdro(). The intrinsic_resistant data set
was also updated accordingly.
Support for all antimicrobial drug (group) names and colloquial microorganism names in Danish, Dutch, English, French, German, Italian, Portuguese, Russian, Spanish and Swedish
Function set_ab_names() to rename data set columns
that resemble antimicrobial drugs. This allows for quickly renaming
columns to official names, ATC codes, etc. Its second argument can be a
tidyverse way of selecting:
example_isolates %>% set_ab_names(where(is.rsi))
example_isolates %>% set_ab_names(AMC:GEN, property = "atc")Function mo_lpsn() to retrieve the LPSN record ID
Function ab_ddd_units() to get units of DDDs (daily
defined doses), deprecating the use of
ab_ddd(..., units = TRUE) to be more consistent in data
types of function output
antibiotics data set now contains all ATC
codes that are available through the WHOCC website, regardless of drugs being
present in more than one ATC group. This means that:
antibiotics$atc is now a list containing
character vectors, and this atc column was
moved to the 5th position of the antibiotics data setab_atc() does not always return a character vector of
length 1, and returns a list if the input is larger than
length 1ab_info() has a slightly different outputThey now also work in R-3.0 and R-3.1, supporting every version of R since 2013 like the rest of the package
Added more selectors for antibiotic classes:
aminopenicillins(), antifungals(),
antimycobacterials(), lincosamides(),
lipoglycopeptides(), polymyxins(),
quinolones(), streptogramins(),
trimethoprims() and
ureidopenicillins()
Added specific selectors for certain types for treatment:
administrable_per_os() and administrable_iv(),
which are based on available Defined Daily Doses (DDDs), as defined by
the WHOCC. These are ideal for e.g. analysing pathogens in primary care
where IV treatment is not an option. They can be combined with other AB
selectors, e.g. to select penicillins that are only administrable per os
(i.e., orally):
example_isolates[, penicillins() & administrable_per_os()] # base R
example_isolates %>% select(penicillins() & administrable_per_os()) # dplyrAdded the selector ab_selector(), which accepts a
filter to be used internally on the antibiotics data set,
yielding great flexibility on drug properties, such as selecting
antibiotic columns with an oral DDD of at least 1 gram:
example_isolates[, ab_selector(oral_ddd > 1 & oral_units == "g")] # base R
example_isolates %>% select(ab_selector(oral_ddd > 1 & oral_units == "g")) # dplyrAdded the selector not_intrinsic_resistant(), which
only keeps antibiotic columns that are not intrinsic resistant for all
microorganisms in a data set, based on the latest EUCAST guideline on
intrinsic resistance. For example, if a data set contains only
microorganism codes or names of E. coli and K.
pneumoniae and contains a column “vancomycin”, this column will be
removed (or rather, unselected) using this function.
Added argument only_treatable, which defaults to
TRUE and will exclude drugs that are only for laboratory
tests and not for treating patients (such as imipenem/EDTA and
gentamicin-high)
Fix for using selectors multiple times in one call (e.g., using
them in dplyr::filter() and immediately after in
dplyr::select())
Fix for using having multiple columns that are coerced to the same antibiotic agent
Fixed for using all() or any() on
antibiotic selectors in an R Markdown file
mo_gramstain()) determination of
the taxonomic class Negativicutes within the phylum of Firmicutes - they
were considered Gram-positives because of their phylum but are actually
Gram-negative. This impacts 137 taxonomic species, genera and families,
such as Negativicoccus and Veillonella.first_isolate()NAs for old MO codes when
running as.mo() on themproportion_*() and count_*() functions
failas.mo()col_* arguments
are left blank, e.g. in first_isolate()random_mic(),
random_disk() and random_rsi() are now
enforcedas.rsi() has an improved algorithm and can now also
correct for textual input (such as “Susceptible”, “Resistant”) in all
supported languagesas.mic() has an improved algorithmcount_*(), proportion_*() function (or
resistant() or susceptible()), the
dplyr group will be shown, if availablescale_rsi_colours() when
using ggplot2 v3.3.4 or higher (this is ggplot2 bug 4511,
soon to be fixed)as.mo()random_mic()as.ab() and all ab_*()
functionsfortify() extensions for plotting methodsNA values of the classes <mic>,
<disk> and <rsi> are now exported
objects of this package, e.g. NA_mic_ is an NA
of class mic (just like the base R
NA_character_ is an NA of class
character)proportion_df(), count_df() and
rsi_df() functions now return with the additional S3 class
‘rsi_df’ so they can be extended by other packagesmdro() function now returns NA for all
rows that have no test resultsspecies_id column in the
microorganisms data set now only contains LPSN record
numbers. For this reason, this column is now numeric instead of a
character, and mo_url() has been updated to reflect this
change.get_episode() and
is_new_episode()get_episode() and is_new_episode() can now
cope with NAsAll antibiotic class selectors (such as
carbapenems(), aminoglycosides()) can now be
used for filtering as well, making all their accompanying
filter_*() functions redundant (such as
filter_carbapenems(),
filter_aminoglycosides()). These functions are now
deprecated and will be removed in a next release. Examples of how the
selectors can be used for filtering:
# select columns with results for carbapenems
example_isolates[, carbapenems()] # base R
example_isolates %>% select(carbapenems()) # dplyr
# filter rows for resistance in any carbapenem
example_isolates[any(carbapenems() == "R"), ] # base R
example_isolates %>% filter(any(carbapenems() == "R")) # dplyr
example_isolates %>% filter(if_any(carbapenems(), ~.x == "R")) # dplyr (formal)
# filter rows for resistance in all carbapenems
example_isolates[all(carbapenems() == "R"), ] # base R
example_isolates[carbapenems() == "R", ]
example_isolates %>% filter(all(carbapenems() == "R")) # dplyr
example_isolates %>% filter(carbapenems() == "R")as.rsi())custom_eucast_rules() that brings support for
custom AMR rules in eucast_rules()italicise_taxonomy() to make taxonomic names
within a string italic, with support for markdown and ANSIfirst_isolate() function gained the argument
method that has to be “phenotype-based”, “episode-based”,
“patient-based”, or “isolate-based”. The old behaviour is equal to
“episode-based”. The new default is “phenotype-based” if antimicrobial
test results are available, and “episode-based” otherwise. This new
default will yield slightly more isolates for selection (which is a good
thing).key_antibiotics() and key_antibiotics_equal()
are now deprecated in favour of the key_antimicrobials()
and antimicrobials_equal() functions. Also, the new
all_antimicrobials() function works like the old
key_antibiotics() function, but includes any column with
antimicrobial test results. Using key_antimicrobials()
still only selects six preferred antibiotics for Gram-negatives, six for
Gram-positives, and six universal antibiotics. It has a new
antifungal argument to set antifungal agents
(antimycotics).type == "points" in the
first_isolate() function for phenotype-based selection will
now consider all antimicrobial drugs in the data set, using the new
all_antimicrobials()first_isolate() function can now take a vector of
values for col_keyantibiotics and can have an episode
length of Inffilter_first_isolate() renders the
filter_first_weighted_isolate() function redundant. For
this reason, filter_first_weighted_isolate() is now
deprecated.first_isolate() and
key_antimicrobials() functions has been completely
rewritten.betalactams() as additional antbiotic column
selector and function filter_betalactams() as additional
antbiotic column filter. The group of betalactams consists of all
carbapenems, cephalosporins and penicillins.ggplot() method for
resistance_predict()bug_drug_combinations() now supports grouping using the
dplyr packagemdro(),
custom_mdro_guideline()):
c()age_groups() for persons aged zeroexample_isolates data set now contains some
(fictitious) zero-year old patientsdata.frame or
tibble now gives a warning if the data contains old
microbial codes (from a previous AMR package version)like() functions:
Now checks if pattern is a valid regular
expression
Added %unlike% and %unlike_case% (as
negations of the existing %like% and
%like_case%). This greatly improves readability:
if (!grepl("EUCAST", guideline)) ...
# same:
if (guideline %unlike% "EUCAST") ...Altered the RStudio addin, so it now iterates over
%like% -> %unlike% ->
%like_case% -> %unlike_case% if you keep
pressing your keyboard shortcut
info argument to as.mo() to turn
on/off the progress barcol_mo in some functions
(esp. eucast_rules() and mdro()) could not be
a column name of the microorganisms data set as it would
throw an erroras.rsi())
when the vctrs package is loaded (i.e., when using
tidyverse)barplot() on an RSI classmicroorganisms.codes data setantibiotics data setskimr::skim() on classes mo,
mic and disk when using the just released
dplyr v1.0.6skimr::skim() usage for MIC values to also
include 25th and 75th percentilesdplyr join
functions if the dplyr package is installed - now also
preserving grouped variablescephalosporins())
now maintain the column order from the original datafluoroquinolones()age() now vectorises over both x and
referencetinytest
package, instead of the testthat package. The
testthat package unfortunately requires tons of
dependencies that are also heavy and only usable for recent R versions,
disallowing developers to test a package under any R 3.* version. On the
contrary, the tinytest package is very lightweight and
dependency-free.Support for EUCAST Clinical Breakpoints v11.0 (2021), effective
in the eucast_rules() function and in as.rsi()
to interpret MIC and disk diffusion values. This is now the default
guideline in this package.
eucast_dosage() to get a
data.frame with advised dosages of a certain bug-drug
combination, which is based on the new dosage data setdosage to fuel the new
eucast_dosage() function and to make this data available in
a structured wayexample_isolates now reflects the
latest EUCAST rulesAdded argument only_rsi_columns for some functions,
which defaults to FALSE, to indicate if the functions must
only be applied to columns that are of class <rsi>
(i.e., transformed with as.rsi()). This increases speed
since automatic determination of antibiotic columns is not needed
anymore. Affected functions are:
ab_class() and its
wrappers, such as aminoglycosides(),
carbapenems(), penicillins())filter_ab_class() and
its wrappers, such as filter_aminoglycosides(),
filter_carbapenems(),
filter_penicillins())eucast_rules()mdro() (including wrappers such as brmo(),
mrgn() and
eucast_exceptional_phenotypes())guess_ab_col()Functions oxazolidinones() (an antibiotic selector
function) and filter_oxazolidinones() (an antibiotic filter
function) to select/filter on e.g. linezolid and tedizolid
library(dplyr)
x <- example_isolates %>% select(date, hospital_id, oxazolidinones())
#> Selecting oxazolidinones: column 'LNZ' (linezolid)
x <- example_isolates %>% filter_oxazolidinones()
#> Filtering on oxazolidinones: value in column `LNZ` (linezolid) is either "R", "S" or "I"Support for custom MDRO guidelines, using the new
custom_mdro_guideline() function, please see
mdro() for additional info
ggplot() generics for classes
<mic> and <disk>
Function mo_is_yeast(), which determines whether a
microorganism is a member of the taxonomic class Saccharomycetes or the
taxonomic order Saccharomycetales:
mo_kingdom(c("Aspergillus", "Candida"))
#> [1] "Fungi" "Fungi"
mo_is_yeast(c("Aspergillus", "Candida"))
#> [1] FALSE TRUE
# usage for filtering data:
example_isolates[which(mo_is_yeast()), ] # base R
example_isolates %>% filter(mo_is_yeast()) # dplyrThe mo_type() function has also been updated to reflect
this change:
mo_type(c("Aspergillus", "Candida"))
# [1] "Fungi" "Yeasts"
mo_type(c("Aspergillus", "Candida"), language = "es") # also supported: de, nl, fr, it, pt
#> [1] "Hongos" "Levaduras"Added Pretomanid (PMD, J04AK08) to the antibiotics
data set
MIC values (see as.mic()) can now be used in any
mathematical processing, such as usage inside functions
min(), max(), range(), and with
binary operators (+, -, etc.). This allows for
easy distribution analysis and fast filtering on MIC values:
x <- random_mic(10)
x
#> Class <mic>
#> [1] 128 0.5 2 0.125 64 0.25 >=256 8 16 4
x[x > 4]
#> Class <mic>
#> [1] 128 64 >=256 8 16
range(x)
#> [1] 0.125 256.000
range(log2(x))
#> [1] -3 8mo_url()) will now lead
to https://lpsn.dsmz.dersi,
<mic>, and <disk>:
translate)plot() and
with ggplot2 using ggplot() on any vector of MIC and disk
diffusion valuesmicroorganisms data setis.rsi() and is.rsi.eligible() now return
a vector of TRUE/FALSE when the input is a
data set, by iterating over all columnsmo_is_gram_negative(), mo_is_gram_positive(),
mo_is_intrinsic_resistant(), first_isolate(),
mdro()) now work with dplyrs
group_by() againfirst_isolate() can be used with
group_by() (also when using a dot . as input
for the data) and now returns the names of the groupsmicroorganisms.codes (which
contains popular LIS and WHONET codes for microorganisms) for some
species of Mycobacterium that previously incorrectly returned
M. africanum"PNV" will now correctly be interpreted as
PHN, the antibiotic code for phenoxymethylpenicillin (‘peni
V’)mdro(..., verbose = TRUE) for
German guideline (3MGRN and 4MGRN) and Dutch guideline (BRMO, only
P. aeruginosa)is.rsi.eligible() now detects if the column name
resembles an antibiotic name or code and now returns TRUE
immediately if the input contains any of the values “R”, “S” or “I”.
This drastically improves speed, also for a lot of other functions that
rely on automatic determination of antibiotic columns.get_episode() and
is_new_episode() now support less than a day as value for
argument episode_days (e.g., to include one patient/test
per hour)ampc_cephalosporin_resistance in
eucast_rules() now also applies to value “I” (not only
“S”)print() and summary() on a
Principal Components Analysis object (pca()) now print
additional group info if the original data was grouped using
dplyr::group_by()guess_ab_col(). As
this also internally improves the reliability of
first_isolate() and mdro(), this might have a
slight impact on the results of those functions.mo_name() when used in other languages than
Englishlike() function (and its fast alias
%like%) now always use Perl compatibility, improving speed
for many functions in this package (e.g., as.mo() is now up
to 4 times faster)random_disk() and random_mic() now have an
expanded range in their randomisationmo_genus("GISA") will return
"Staphylococcus"as.ab() when the input is an
official name or ATC codeinclude_untested_rsi to the
first_isolate() functions (defaults to TRUE to
keep existing behaviour), to be able to exclude rows where all R/SI
values (class <rsi>, see as.rsi()) are
emptylibrary(AMR)) now is ~50
times faster than before, in costs of package size (which increased by
~3 MB)Functions get_episode() and
is_new_episode() to determine (patient) episodes which are
not necessarily based on microorganisms. The get_episode()
function returns the index number of the episode per group, while the
is_new_episode() function returns values
TRUE/FALSE to indicate whether an item in a
vector is the start of a new episode. They also support
dplyrs grouping (i.e. using group_by()):
library(dplyr)
example_isolates %>%
group_by(patient_id, hospital_id) %>%
filter(is_new_episode(date, episode_days = 60))Functions mo_is_gram_negative() and
mo_is_gram_positive() as wrappers around
mo_gramstain(). They always return TRUE or
FALSE (except when the input is NA or the MO
code is UNKNOWN), thus always return FALSE for
species outside the taxonomic kingdom of Bacteria.
Function mo_is_intrinsic_resistant() to test for
intrinsic resistance, based on EUCAST Intrinsic Resistance and Unusual
Phenotypes v3.2 from 2020.
Functions random_mic(), random_disk()
and random_rsi() for random value generation. The functions
random_mic() and random_disk() take
microorganism names and antibiotic names as input to make generation
more realistic.
New argument ampc_cephalosporin_resistance in
eucast_rules() to correct for AmpC de-repressed
cephalosporin-resistant mutants
Interpretation of antimicrobial resistance -
as.rsi():
as.rsi() can now be set by the
user, using the reference_data argument. This allows for
using own interpretation guidelines. The user-set data must have the
same structure as rsi_translation.as.rsi() on a data.frameas.rsi() on a data.frame in older R
versionsas.rsi() on a data.frame will not print a message
anymore if the values are already clean R/SI valuesas.rsi() on MICs or disk diffusion while there
is intrinsic antimicrobial resistance, a warning will be thrown to
remind about thisas.rsi() on a data.frame
that only contains one column for antibiotic interpretationsSome functions are now context-aware when used inside
dplyr verbs, such as filter(),
mutate() and summarise(). This means that then
the data argument does not need to be set anymore. This is the case for
the new functions:
mo_is_gram_negative()mo_is_gram_positive()mo_is_intrinsic_resistant()… and for the existing functions:
first_isolate(),key_antibiotics(),mdro(),brmo(),mrgn(),mdr_tb(),mdr_cmi2012(),eucast_exceptional_phenotypes()# to select first isolates that are Gram-negative
# and view results of cephalosporins and aminoglycosides:
library(dplyr)
example_isolates %>%
filter(first_isolate(), mo_is_gram_negative()) %>%
select(mo, cephalosporins(), aminoglycosides()) %>%
as_tibble()For antibiotic selection functions (such as
cephalosporins(), aminoglycosides()) to select
columns based on a certain antibiotic group, the dependency on the
tidyselect package was removed, meaning that they can now
also be used without the need to have this package installed and now
also work in base R function calls (they rely on R 3.2 or later):
# above example in base R:
example_isolates[which(first_isolate() & mo_is_gram_negative()),
c("mo", cephalosporins(), aminoglycosides())]For all function arguments in the code, it is now defined what
the exact type of user input should be (inspired by the typed
package). If the user input for a certain function does not meet the
requirements for a specific argument (such as the class or length), an
informative error will be thrown. This makes the package more robust and
the use of it more reproducible and reliable. In total, more than 420
arguments were defined.
Fix for set_mo_source(), that previously would not
remember the file location of the original file
Deprecated function p_symbol() that not really fits
the scope of this package. It will be removed in a future version. See
here
for the source code to preserve it.
Updated coagulase-negative staphylococci determination with Becker et al. 2020 (PMID 32056452), meaning that the species S. argensis, S. caeli, S. debuckii, S. edaphicus and S. pseudoxylosus are now all considered CoNS
Fix for using argument reference_df in
as.mo() and mo_*() functions that contain old
microbial codes (from previous package versions)
Fixed a bug where mo_uncertainties() would not
return the results based on the MO matching score
Fixed a bug where as.mo() would not return results
for known laboratory codes for microorganisms
Fixed a bug where as.ab() would sometimes
fail
Better tibble printing for MIC values
Fix for plotting MIC values with plot()
Added plot() generic to class
<disk>
LA-MRSA and CA-MRSA are now recognised as an abbreviation for
Staphylococcus aureus, meaning that
e.g. mo_genus("LA-MRSA") will return
"Staphylococcus" and
mo_is_gram_positive("LA-MRSA") will return
TRUE.
Fix for printing class NA
Fix for mo_shortname() when the input contains
NA
If as.mo() takes more than 30 seconds, some
suggestions will be done to improve speed
options() were all removed in favour
of a new internal environment pkg_envsapply() calls with vapply())Support for ‘EUCAST Expert Rules’ / ‘EUCAST Intrinsic Resistance
and Unusual Phenotypes’ version 3.2 of May 2020. With this addition to
the previously implemented version 3.1 of 2016, the
eucast_rules() function can now correct for more than 180
different antibiotics and the mdro() function can determine
multidrug resistance based on more than 150 different antibiotics. All
previously implemented versions of the EUCAST rules are now maintained
and kept available in this package. The eucast_rules()
function consequently gained the arguments
version_breakpoints (at the moment defaults to v10.0, 2020)
and version_expertrules (at the moment defaults to v3.2,
2020). The example_isolates data set now also reflects the
change from v3.1 to v3.2. The mdro() function now accepts
guideline == "EUCAST3.1" and
guideline == "EUCAST3.2".
A new vignette and website page with info about all our public and freely available data sets, that can be downloaded as flat files or in formats for use in R, SPSS, SAS, Stata and Excel: https://msberends.github.io/AMR/articles/datasets.html
Data set intrinsic_resistant. This data set contains
all bug-drug combinations where the ‘bug’ is intrinsic resistant to the
‘drug’ according to the latest EUCAST insights. It contains just two
columns: microorganism and antibiotic.
Curious about which enterococci are actually intrinsic resistant to vancomycin?
library(AMR)
library(dplyr)
intrinsic_resistant %>%
filter(antibiotic == "Vancomycin", microorganism %like% "Enterococcus") %>%
pull(microorganism)
#> [1] "Enterococcus casseliflavus" "Enterococcus gallinarum" Support for veterinary ATC codes
Support for skimming classes <rsi>,
<mic>, <disk> and
<mo> with the skimr package
Although advertised that this package should work under R 3.0.0, we still had a dependency on R 3.6.0. This is fixed, meaning that our package should now work under R 3.0.0.
Improvements for as.rsi():
Support for using dplyr’s across() to
interpret MIC values or disk zone diameters, which also automatically
determines the column with microorganism names or codes.
# until dplyr 1.0.0
your_data %>% mutate_if(is.mic, as.rsi)
your_data %>% mutate_if(is.disk, as.rsi)
# since dplyr 1.0.0
your_data %>% mutate(across(where(is.mic), as.rsi))
your_data %>% mutate(across(where(is.disk), as.rsi))Cleaning columns in a data.frame now allows you to specify those
columns with tidy selection,
e.g. as.rsi(df, col1:col9)
Big speed improvement for interpreting MIC values and disk zone diameters. When interpreting 5,000 MIC values of two antibiotics (10,000 values in total), our benchmarks showed a total run time going from 80.7-85.1 seconds to 1.8-2.0 seconds.
Added argument ‘add_intrinsic_resistance’ (defaults to
FALSE), that considers intrinsic resistance according to
EUCAST
Fixed a bug where in EUCAST rules the breakpoint for R would be interpreted as “>=” while this should have been “<”
Added intelligent data cleaning to as.disk(), so
numbers can also be extracted from text and decimal numbers will always
be rounded up:
as.disk(c("disk zone: 23.4 mm", 23.4))
#> Class <disk>
#> [1] 24 24Improvements for as.mo():
mo_matching_score(). Any user input value that could mean
more than one taxonomic entry is now considered ‘uncertain’. Instead of
a warning, a message will be thrown and the accompanying
mo_uncertainties() has been changed completely; it now
prints all possible candidates with their matching score.mo_*
functions like mo_name() on microoganism IDs.ignore_pattern to as.mo()
which can also be given to mo_* functions like
mo_name(), to exclude known non-relevant input from
analysing. This can also be set with the option
AMR_ignore_pattern.get_locale() now uses at default
Sys.getenv("LANG") or, if LANG is not set,
Sys.getlocale(). This can be overwritten by setting the
option AMR_locale.
Big speed improvement for eucast_rules()
Overall speed improvement by tweaking joining functions
Function mo_shortname() now returns the genus for
input where the species is unknown
BORSA is now recognised as an abbreviation for Staphylococcus
aureus, meaning that e.g. mo_genus("BORSA") will
return “Staphylococcus”
Added a feature from AMR 1.1.0 and earlier again, but now without
other package dependencies: tibble printing support for
classes <rsi>, <mic>,
<disk>, <ab> and
<mo>. When using tibbles containing
antimicrobial columns (class <rsi>), “S” will print
in green, “I” will print in yellow and “R” will print in red. Microbial
IDs (class <mo>) will emphasise on the genus and
species, not on the kingdom.
Names of antiviral agents in data set antivirals now
have a starting capital letter, like it is the case in the
antibiotics data set
Updated the documentation of the WHONET data set to
clarify that all patient names are fictitious
Small as.ab() algorithm improvements
Fix for combining MIC values with raw numbers,
i.e. c(as.mic(2), 2) previously failed but now returns a
valid MIC class
ggplot_rsi() and geom_rsi() gained
arguments minimum and language, to influence
the internal use of rsi_df()
Changes in the antibiotics data set:
PEN)PNV) was removed,
since its actual entry ‘Phenoxymethylpenicillin’ (code PHN)
already existedantibiotics$group) of ‘Linezolid’
(LNZ), ‘Cycloserine’ (CYC), ‘Tedizolid’
(TZD) and ‘Thiacetazone’ (THA) is now
“Oxazolidinones” instead of “Other antibacterials”Added support for using unique() on classes
<rsi>, <mic>,
<disk>, <ab> and
<mo>
Added argument excess to the kurtosis()
function (defaults to FALSE), to return the excess
kurtosis, defined as the kurtosis minus three.
portion_R(), portion_S()
and portion_I() that were deprecated since version 0.9.0
(November 2019) and were replaced with proportion_R(),
proportion_S() and proportion_I()base packageSuggests field of the DESCRIPTION fileFunction ab_from_text() to retrieve antimicrobial
drug names, doses and forms of administration from clinical texts in
e.g. health care records, which also corrects for misspelling since it
uses as.ab() internally
Tidyverse
selection helpers for antibiotic classes, that help to select the
columns of antibiotics that are of a specific antibiotic class, without
the need to define the columns or antibiotic abbreviations. They can be
used in any function that allows selection helpers, like
dplyr::select() and tidyr::pivot_longer():
library(dplyr)
# Columns 'IPM' and 'MEM' are in the example_isolates data set
example_isolates %>%
select(carbapenems())
#> Selecting carbapenems: `IPM` (imipenem), `MEM` (meropenem)Added mo_domain() as an alias to
mo_kingdom()
Added function filter_penicillins() to filter
isolates on a specific result in any column with a name in the
antimicrobial ‘penicillins’ class (more specific: ATC subgroup
Beta-lactam antibacterials, penicillins)
Added official antimicrobial names to all
filter_ab_class() functions, such as
filter_aminoglycosides()
Added antibiotics code “FOX1” for cefoxitin screening
(abbreviation “cfsc”) to the antibiotics data set
Added Monuril as trade name for fosfomycin
Added argument conserve_capped_values to
as.rsi() for interpreting MIC values - it makes sure that
values starting with “<” (but not “<=”) will always return “S” and
values starting with “>” (but not “>=”) will always return “R”.
The default behaviour of as.rsi() has not changed, so you
need to specifically do
as.rsi(..., conserve_capped_values = TRUE).
Big speed improvement for using any function on microorganism
codes from earlier package versions (prior to AMR v1.2.0),
such as as.mo(), mo_name(),
first_isolate(), eucast_rules(),
mdro(), etc.
As a consequence, very old microbial codes (from AMR
v0.5.0 and lower) are not supported anymore. Use
as.mo() on your microorganism names or codes to transform
them to current abbreviations used in this package.
Improvements for susceptibility() and
resistance() and all count_*(),
proportion_*() functions:
dplyr::all_of()) now works againImprovements for as.ab():
as.ab(),
making many more input errors translatable, such as digitalised health
care records, using too few or too many vowels or consonants and many
moreas.ab() would return an error on
invalid input valuesas.ab() function will now throw a note if more than
1 antimicrobial drug could be retrieved from a single input value.Fixed a bug where eucast_rules() would not work on a
tibble when the tibble or dplyr package was
loaded
Fixed a bug for CLSI 2019 guidelines (using
as.rsi()), that also included results for animals. It now
only contains interpretation guidelines for humans.
All *_join_microorganisms() functions and
bug_drug_combinations() now return the original data class
(e.g. tibbles and data.tables)
For functions rsi_df(), proportion_df()
and count_df():
count_df())
when all antibiotics in the data set have only NAsImproved auto-determination for columns of types
<mo> and <Date>
Fixed a bug in bug_drug_combinations() for when only
one antibiotic was in the input data
Changed the summary for class <rsi>, to
highlight the %SI vs. %R
Improved error handling, giving more useful info when functions return an error
Any progress bar will now only show in interactive mode (i.e. not in R Markdown)
Speed improvement for mdro() and
filter_ab_class()
New option arrows_textangled for
ggplot_pca() to indicate whether the text at the end of the
arrows should be angled (defaults to TRUE, as it was in
previous versions)
Added parenteral DDD to benzylpenicillin
Fixed a bug where as.mic() could not handle dots
without a leading zero (like "<=.25)
Removed code dependency on all other R packages, making this package fully independent of the development process of others. This is a major code change, but will probably not be noticeable by most users.
Making this package independent of especially the tidyverse
(e.g. packages dplyr and tidyr) tremendously
increases sustainability on the long term, since tidyverse functions
change quite often. Good for users, but hard for package maintainers.
Most of our functions are replaced with versions that only rely on base
R, which keeps this package fully functional for many years to come,
without requiring a lot of maintenance to keep up with other packages
anymore. Another upside it that this package can now be used with all
versions of R since R-3.0.0 (April 2013). Our package is being used in
settings where the resources are very limited. Fewer dependencies on
newer software is helpful for such settings.
Negative effects of this change are:
freq() that was borrowed from the
cleaner package was removed. Use
cleaner::freq(), or run library("cleaner")
before you use freq().mo or rsi in
a tibble will no longer be in colour and printing rsi in a
tibble will show the class <ord>, not
<rsi> anymore. This is purely a visual
effect.mo_* family (like
mo_name() and mo_gramstain()) are noticeably
slower when running on hundreds of thousands of rows.mo and ab now both
also inherit class character, to support any data
transformation. This change invalidates code that checks for class
length == 1.first_isolate()), since some bacterial names might
be renamed to other genera or other (sub)species. This is expected
behaviour.eucast_rules() function no longer applies “other”
rules at default that are made available by this package (like setting
ampicillin = R when ampicillin + enzyme inhibitor = R). The default
input value for rules is now
c("breakpoints", "expert") instead of "all",
but this can be changed by the user. To return to the old behaviour, set
options(AMR.eucast_rules = "all").antibiotics data set these two rules:
eucast_rules()ab_url() to return the direct URL of an
antimicrobial agent from the official WHO websiteas.ab(), so that
e.g. as.ab("ampi sul") and ab_name("ampi sul")
workab_atc() and ab_group() now
return NA if no antimicrobial agent could be foundset_mo_source() to make sure that column
mo will always be the second columnp.symbol() - it
was replaced with p_symbol()read.4d(), that was only useful for
reading data from an old test database.pca() functionggplot_pca() functionas.mo() (and
consequently all mo_* functions, that use
as.mo() internally):
SPE for species, like
"ESCSPE" for Escherichia coliantibiotics data
setas.rsi() for years 2010-2019 (thanks to Anthony
Underwood)dplyr version 1.0.0rsi and
micFixed important floating point error for some MIC comparisons in EUCAST 2020 guideline
Interpretation from MIC values (and disk zones) to R/SI can now
be used with mutate_at() of the dplyr
package:
yourdata %>%
mutate_at(vars(antibiotic1:antibiotic25), as.rsi, mo = "E. coli")
yourdata %>%
mutate_at(vars(antibiotic1:antibiotic25), as.rsi, mo = .$mybacteria)Added antibiotic abbreviations for a laboratory manufacturer (GLIMS) for cefuroxime, cefotaxime, ceftazidime, cefepime, cefoxitin and trimethoprim/sulfamethoxazole
Added uti (as abbreviation of urinary tract
infections) as argument to as.rsi(), so interpretation of
MIC values and disk zones can be made dependent on isolates specifically
from UTIs
Info printing in functions eucast_rules(),
first_isolate(), mdro() and
resistance_predict() will now at default only print when R
is in an interactive mode (i.e. not in RMarkdown)
This software is now out of beta and considered stable. Nonetheless, this package will be developed continually.
as.rsi() and
inferred resistance and susceptibility using
eucast_rules().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:
ab_loinc("ampicillin")
#> [1] "21066-6" "3355-5" "33562-0" "33919-2" "43883-8" "43884-6" "87604-5"
ab_name("21066-6")
#> [1] "Ampicillin"
ab_atc("21066-6")
#> [1] "J01CA01"Support for SNOMED CT codes in the microorganisms
data set. Use mo_snomed() to retrieve SNOMED codes, or use
a SNOMED code for input in any mo_* function:
mo_snomed("S. aureus")
#> [1] 115329001 3092008 113961008
mo_name(115329001)
#> [1] "Staphylococcus aureus"
mo_gramstain(115329001)
#> [1] "Gram-positive"as.mo() function previously wrote to the package
folder to improve calculation speed for previously calculated results.
This is no longer the case, to comply with CRAN policies. Consequently,
the function clear_mo_history() was removed.as.rsi()as.mo() (and
consequently all mo_* functions, that use
as.mo() internally):
as.mo("Methicillin-resistant S.aureus")as.disk() limited to a maximum of 50
millimeterstidyverseas.ab(): support for drugs starting with “co-”
like co-amoxiclav, co-trimoxazole, co-trimazine and co-trimazole (thanks
to Peter Dutey)antibiotics data set (thanks to Peter
Dutey):
RIF) to rifampicin/isoniazid (RFI). Please
note that the
combination rifampicin/isoniazid has no DDDs defined, so
e.g. ab_ddd("Rimactazid") will now return
NA.SMX) to trimethoprim/sulfamethoxazole
(SXT)CITATION fileAMR:: callsmicroorganisms 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.
If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:
if (mo_family(somebugs) == "Enterobacteriaceae") ...then please adjust this to:
if (mo_order(somebugs) == "Enterobacterales") ...Functions susceptibility() and
resistance() as aliases of proportion_SI() and
proportion_R(), respectively. These functions were added to
make it more clear that “I” should be considered susceptible and not
resistant.
library(dplyr)
example_isolates %>%
group_by(bug = mo_name(mo)) %>%
summarise(amoxicillin = resistance(AMX),
amox_clav = resistance(AMC)) %>%
filter(!is.na(amoxicillin) | !is.na(amox_clav))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).
mdro()
functionmdro(...., 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
agentsData set antivirals, containing all entries from the
ATC J05 group with their DDDs for oral and parenteral treatment
as.mo():
Now allows “ou” where “au” should have been used and vice versa
More intelligent way of coping with some consonants like “l” and “r”
Added a score (a certainty percentage) to
mo_uncertainties(), that is calculated using the Levenshtein
distance:
as.mo(c("Stafylococcus aureus",
"staphylokok aureuz"))
#> Warning:
#> Results of two values were guessed with uncertainty. Use mo_uncertainties() to review them.
#> Class 'mo'
#> [1] B_STPHY_AURS B_STPHY_AURS
mo_uncertainties()
#> "Stafylococcus aureus" -> Staphylococcus aureus (B_STPHY_AURS, score: 95.2%)
#> "staphylokok aureuz" -> Staphylococcus aureus (B_STPHY_AURS, score: 85.7%)as.atc() - this
function was replaced by ab_atc()portion_* functions to
proportion_*. All portion_* functions are
still available as deprecated functions, and will return a warning when
used.as.rsi() over a data set, it will now
print the guideline that will be used if it is not specified by the
usereucast_rules():
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.as.rsi() where the
input is NAmdro() and eucast_rules()antibiotics data setexample_isolates data set to
better reflect realitymo_info()clean to cleaner, as
this package was renamed accordingly upon CRAN requestDetermination of first isolates now excludes all
‘unknown’ microorganisms at default, i.e. microbial code
"UNKNOWN". They can be included with the new argument
include_unknown:
first_isolate(..., include_unknown = TRUE)For WHONET users, this means that all records/isolates with organism
code "con" (contamination) will be excluded at
default, since as.mo("con") = "UNKNOWN". The function
always shows a note with the number of ‘unknown’ microorganisms that
were included or excluded.
For code consistency, classes ab and mo
will now be preserved in any subsetting or assignment. For the sake of
data integrity, this means that invalid assignments will now result in
NA:
# how it works in base R:
x <- factor("A")
x[1] <- "B"
#> Warning message:
#> invalid factor level, NA generated
# how it now works similarly for classes 'mo' and 'ab':
x <- as.mo("E. coli")
x[1] <- "testvalue"
#> Warning message:
#> invalid microorganism code, NA generatedThis is important, because a value like "testvalue"
could never be understood by e.g. mo_name(), although the
class would suggest a valid microbial code.
Function freq() has moved to a new package, clean (CRAN link), since
creating frequency tables actually does not fit the scope of this
package. The freq() function still works, since it is
re-exported from the clean package (which will be installed
automatically upon updating this AMR package).
Renamed data set septic_patients to
example_isolates
Function bug_drug_combinations() to quickly get a
data.frame with the results of all bug-drug combinations in
a data set. The column containing microorganism codes is guessed
automatically and its input is transformed with
mo_shortname() at default:
x <- bug_drug_combinations(example_isolates)
#> NOTE: Using column `mo` as input for `col_mo`.
x[1:4, ]
#> mo ab S I R total
#> 1 A. baumannii AMC 0 0 3 3
#> 2 A. baumannii AMK 0 0 0 0
#> 3 A. baumannii AMP 0 0 3 3
#> 4 A. baumannii AMX 0 0 3 3
#> NOTE: Use 'format()' on this result to get a publicable/printable format.
# change the transformation with the FUN argument to anything you like:
x <- bug_drug_combinations(example_isolates, FUN = mo_gramstain)
#> NOTE: Using column `mo` as input for `col_mo`.
x[1:4, ]
#> mo ab S I R total
#> 1 Gram-negative AMC 469 89 174 732
#> 2 Gram-negative AMK 251 0 2 253
#> 3 Gram-negative AMP 227 0 405 632
#> 4 Gram-negative AMX 227 0 405 632
#> NOTE: Use 'format()' on this result to get a publicable/printable format.You can format this to a printable format, ready for reporting or
exporting to e.g. Excel with the base R format()
function:
format(x, combine_IR = FALSE)Additional way to calculate co-resistance, i.e. when using
multiple antimicrobials as input for portion_* functions or
count_* functions. This can be used to determine the
empiric susceptibility of a combination therapy. A new argument
only_all_tested (which defaults to
FALSE) replaces the old
also_single_tested and can be used to select one of the two
methods to count isolates and calculate portions. The difference can be
seen in this example table (which is also on the portion
and count help pages), where the %SI is being
determined:
# --------------------------------------------------------------------
# only_all_tested = FALSE only_all_tested = TRUE
# ----------------------- -----------------------
# Drug A Drug B include as include as include as include as
# numerator denominator numerator denominator
# -------- -------- ---------- ----------- ---------- -----------
# S or I S or I X X X X
# R S or I X X X X
# <NA> S or I X X - -
# S or I R X X X X
# R R - X - X
# <NA> R - - - -
# S or I <NA> X X - -
# R <NA> - - - -
# <NA> <NA> - - - -
# --------------------------------------------------------------------Since this is a major change, usage of the old
also_single_tested will throw an informative error that it
has been replaced by only_all_tested.
tibble printing support for classes
rsi, mic, disk, ab
mo. When using tibbles containing
antimicrobial columns, values S will print in green, values
I will print in yellow and values R will print
in red. Microbial IDs (class mo) will emphasise on the
genus and species, not on the kingdom.
# (run this on your own console, as this page does not support colour printing)
library(dplyr)
example_isolates %>%
select(mo:AMC) %>%
as_tibble()as.mo() (of which some
led to additions to the microorganisms data set). Many
thanks to all contributors that helped improving the algorithms.
B_ENTRC_FAE could have been both E.
faecalis and E. faecium. Its new code is
B_ENTRC_FCLS and E. faecium has become
B_ENTRC_FACM. Also, the Latin character ae is now preserved
at the start of each genus and species abbreviation. For example, the
old code for Aerococcus urinae was B_ARCCC_NAE.
This is now B_AERCC_URIN. IMPORTANT: Old
microorganism IDs are still supported, but support will be dropped in a
future version. Use as.mo() on your old codes to transform
them to the new format. Using functions from the mo_*
family (like mo_name() and mo_gramstain()) on
old codes, will throw a warning.as.ab(), including
bidirectional language supportmdro() function, to determine multi-drug resistant
organismseucast_rules():
eucast_rules(..., verbose = TRUE)) returns more
informative and readable outputAMR:::get_column_abx())atc - using as.atc() is now
deprecated in favour of ab_atc() and this will return a
character, not the atc class anymoreabname(),
ab_official(), atc_name(),
atc_official(), atc_property(),
atc_tradenames(), atc_trivial_nl()mo_shortname()mo_* functions where the coercion
uncertainties and failures would not be available through
mo_uncertainties() and mo_failures()
anymorecountry argument of mdro()
in favour of the already existing guideline argument to
support multiple guidelines within one countryname of RIF is now Rifampicin instead
of Rifampinantibiotics data set is now sorted by name and all
cephalosporins now have their generation between bracketsguess_ab_col() which is now 30
times faster for antibiotic abbreviationsfilter_ab_class() to be more reliable and to
support 5th generation cephalosporinsavailability() now uses
portion_R() instead of portion_IR(), to comply
with EUCAST insightsage() and age_groups() now have
a na.rm argument to remove empty valuesp.symbol() to p_symbol()
(the former is now deprecated and will be removed in a future
version)x in
age_groups() will now introduce NAs and not
return an error anymorekey_antibiotics() on foreign systemsmdr_tb()as.mic())lintr packageFunction rsi_df() to transform a
data.frame to a data set containing only the microbial
interpretation (S, I, R), the antibiotic, the percentage of S/I/R and
the number of available isolates. This is a convenient combination of
the existing functions count_df() and
portion_df() to immediately show resistance percentages and
number of available isolates:
septic_patients %>%
select(AMX, CIP) %>%
rsi_df()
# antibiotic interpretation value isolates
# 1 Amoxicillin SI 0.4442636 546
# 2 Amoxicillin R 0.5557364 683
# 3 Ciprofloxacin SI 0.8381831 1181
# 4 Ciprofloxacin R 0.1618169 228Support for all scientifically published pathotypes of E. coli to date (that we could find). Supported are:
All these lead to the microbial ID of E. coli:
as.mo("UPEC")
# B_ESCHR_COL
mo_name("UPEC")
# "Escherichia coli"
mo_gramstain("EHEC")
# "Gram-negative"Function mo_info() as an analogy to
ab_info(). The mo_info() prints a list with
the full taxonomy, authors, and the URL to the online database of a
microorganism
Function mo_synonyms() to get all previously
accepted taxonomic names of a microorganism
count_df() and
portion_df() are now lowercaseas.ab() and
as.mo() to understand even more severely misspelled
inputas.ab() now allows spaces for coercing
antibiotics namesggplot2 methods for automatically determining the
scale type of classes mo and ab"bacteria" from getting coerced by
as.ab() because Bacterial is a brand name of trimethoprim
(TMP)eucast_rules() and mdro()latest_annual_release from the
catalogue_of_life_version() functionPVM1 from the
antibiotics data set as this was a duplicate of
PMEas.mo()plot() and barplot()
for MIC and RSI classesas.mo()as.rsi()
on an MIC value (created with as.mic()), a disk diffusion
value (created with the new as.disk()) or on a complete
date set containing columns with MIC or disk diffusion values.mo_name() as alias of
mo_fullname()mdr_tb()) and added a new vignette about MDR. Read
this tutorial here on our
website.first_isolate() where missing
species would lead to incorrect FALSEs. This bug was not present in AMR
v0.5.0, but was in v0.6.0 and v0.6.1.eucast_rules() where antibiotics from
WHONET software would not be recognisedantibiotics data set:
ab contains a human readable EARS-Net code, used
by ECDC and WHO/WHONET - this is the primary identifier used in this
packageatc contains the ATC code, used by
WHO/WHOCCcid contains the CID code (Compound ID), used by
PubChemAMX for amoxicillinatc_certe, ab_umcg and
atc_trivial_nl have been removedatc_* functions are superseded by ab_*
functionsggplot_rsi():
colours to set the bar colourstitle, subtitle,
caption, x.title and y.title to
set titles and axis descriptionsguess_ab_col()microorganisms.old data set, which leads to better results
finding when using the as.mo() functionportion_df() and count_df() this means that
their new argument combine_SI is TRUE at default. Our
plotting function ggplot_rsi() also reflects this change
since it uses count_df() internally.age() function gained a new argument
exact to determine ages with decimalsguess_mo(),
guess_atc(), EUCAST_rules(),
interpretive_reading(), rsi()freq()):
speed improvement for microbial IDs
fixed factor level names for R Markdown
when all values are unique it now shows a message instead of a warning
support for boxplots:
septic_patients %>%
freq(age) %>%
boxplot()
# grouped boxplots:
septic_patients %>%
group_by(hospital_id) %>%
freq(age) %>%
boxplot()age_groups(), to let
groups of fives and tens end with 100+ instead of 120+freq() for when all values are
NAfirst_isolate() for when dates are missingguess_ab_col()as.mo() now gently interprets any number of
whitespace characters (like tabs) as one spaceas.mo() now returns UNKNOWN for
"con" (WHONET ID of ‘contamination’) and returns
NA for "xxx"(WHONET ID of ‘no growth’)as.mo()microorganisms.codes and
cleaned it upmo_shortname() where species would not be
determined correctlyeucast_rules() with
verbose = TRUENew website!
We’ve got a new website: https://msberends.gitlab.io/AMR
(built with the great pkgdown)
BREAKING: removed deprecated functions,
arguments and references to ‘bactid’. Use as.mo() to
identify an MO code.
Catalogue of Life as a new taxonomic source for data about
microorganisms, which also contains all ITIS data we used previously.
The microorganisms data set now contains:
All ~55,000 (sub)species from the kingdoms of Archaea, Bacteria and Protozoa
All ~3,000 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Onygenales, Pneumocystales, Saccharomycetales and Schizosaccharomycetales (covering at least like all species of Aspergillus, Candida, Pneumocystis, Saccharomyces and Trichophyton)
All ~2,000 (sub)species from ~100 other relevant genera, from the kingdoms of Animalia and Plantae (like Strongyloides and Taenia)
All ~15,000 previously accepted names of included (sub)species that have been taxonomically renamed
The responsible author(s) and year of scientific publication
This data is updated annually - check the included version with the
new function catalogue_of_life_version().
Due to this change, some mo codes changed
(e.g. Streptococcus changed from B_STRPTC to
B_STRPT). A translation table is used internally to support
older microorganism IDs, so users will not notice this
difference.
New function mo_rank() for the taxonomic rank
(genus, species, infraspecies, etc.)
New function mo_url() to get the direct URL of a
species from the Catalogue of Life
Support for data from WHONET and EARS-Net (European Antimicrobial Resistance Surveillance Network):
first_isolate() and
eucast_rules(), all arguments will be filled in
automatically.antibiotics
data set now contains a column ears_net.as.mo() now knows all WHONET species
abbreviations too, because almost 2,000 microbial abbreviations were
added to the microorganisms.codes data set.New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:
filter_aminoglycosides()
filter_carbapenems()
filter_cephalosporins()
filter_1st_cephalosporins()
filter_2nd_cephalosporins()
filter_3rd_cephalosporins()
filter_4th_cephalosporins()
filter_fluoroquinolones()
filter_glycopeptides()
filter_macrolides()
filter_tetracyclines()The antibiotics data set will be searched, after which
the input data will be checked for column names with a value in any
abbreviations, codes or official names found in the
antibiotics data set. For example:
septic_patients %>% filter_glycopeptides(result = "R")
# Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R
septic_patients %>% filter_glycopeptides(result = "R", scope = "all")
# Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is RAll ab_* functions are deprecated and replaced by
atc_* functions:
ab_property -> atc_property()
ab_name -> atc_name()
ab_official -> atc_official()
ab_trivial_nl -> atc_trivial_nl()
ab_certe -> atc_certe()
ab_umcg -> atc_umcg()
ab_tradenames -> atc_tradenames()These functions use as.atc() internally. The old
atc_property has been renamed
atc_online_property(). This is done for two reasons:
firstly, not all ATC codes are of antibiotics (ab) but can also be of
antivirals or antifungals. Secondly, the input must have class
atc or must be coerable to this class. Properties of these
classes should start with the same class name, analogous to
as.mo() and e.g. mo_genus.
New functions set_mo_source() and
get_mo_source() to use your own predefined MO codes as
input for as.mo() and consequently all mo_*
functions
Support for the upcoming dplyr version
0.8.0
New function guess_ab_col() to find an antibiotic
column in a table
New function mo_failures() to review values that
could not be coerced to a valid MO code, using as.mo().
This latter function will now only show a maximum of 10 uncoerced values
and will refer to mo_failures().
New function mo_uncertainties() to review values
that could be coerced to a valid MO code using as.mo(), but
with uncertainty.
New function mo_renamed() to get a list of all
returned values from as.mo() that have had taxonomic
renaming
New function age() to calculate the (patients) age
in years
New function age_groups() to split ages into custom
or predefined groups (like children or elderly). This allows for easier
demographic AMR data analysis per age group.
New function ggplot_rsi_predict() as well as the
base R plot() function can now be used for resistance
prediction calculated with resistance_predict():
x <- resistance_predict(septic_patients, col_ab = "amox")
plot(x)
ggplot_rsi_predict(x)Functions filter_first_isolate() and
filter_first_weighted_isolate() to shorten and fasten
filtering on data sets with antimicrobial results, e.g.:
septic_patients %>% filter_first_isolate(...)
# or
filter_first_isolate(septic_patients, ...)is equal to:
septic_patients %>%
mutate(only_firsts = first_isolate(septic_patients, ...)) %>%
filter(only_firsts == TRUE) %>%
select(-only_firsts)New function availability() to check the number of
available (non-empty) results in a data.frame
New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the G-test and more. These are also available (and even easier readable) on our website: https://msberends.gitlab.io/AMR.
eucast_rules():
septic_patients now reflects
these changeseucast_rules(..., verbose = TRUE) to get a data set with
all changed per bug and drug combination.microorganisms.oldDT,
microorganisms.prevDT, microorganisms.unprevDT
and microorganismsDT since they were no longer needed and
only contained info already available in the microorganisms
data setantibiotics data set, from
the Pharmaceuticals
Community Register of the European Commissionatc_group1_nl and
atc_group2_nl from the antibiotics data
setatc_ddd() and atc_groups() have
been renamed atc_online_ddd() and
atc_online_groups(). The old functions are deprecated and
will be removed in a future version.guess_mo() is now deprecated in favour of
as.mo() and will be removed in future versionsguess_atc() is now deprecated in favour of
as.atc() and will be removed in future versionsas.mo():
Now handles incorrect spelling, like i instead of
y and f instead of ph:
# mo_fullname() uses as.mo() internally
mo_fullname("Sthafilokockus aaureuz")
#> [1] "Staphylococcus aureus"
mo_fullname("S. klossi")
#> [1] "Staphylococcus kloosii"Uncertainty of the algorithm is now divided into four levels, 0
to 3, where the default allow_uncertain = TRUE is equal to
uncertainty level 2. Run ?as.mo for more info about these
levels.
# equal:
as.mo(..., allow_uncertain = TRUE)
as.mo(..., allow_uncertain = 2)
# also equal:
as.mo(..., allow_uncertain = FALSE)
as.mo(..., allow_uncertain = 0)Using as.mo(..., allow_uncertain = 3) could lead to very
unreliable results.
Implemented the latest publication of Becker et al. (2019), for categorising coagulase-negative Staphylococci
All microbial IDs that found are now saved to a local file
~/.Rhistory_mo. Use the new function
clean_mo_history() to delete this file, which resets the
algorithms.
Incoercible results will now be considered ‘unknown’, MO code
UNKNOWN. On foreign systems, properties of these will be
translated to all languages already previously supported: German, Dutch,
French, Italian, Spanish and Portuguese.
Fix for vector containing only empty values
Finds better results when input is in other languages
Better handling for subspecies
Better handling for Salmonellae, especially the ‘city like’ serovars like Salmonella London
Understanding of highly virulent E. coli strains like EIEC, EPEC and STEC
There will be looked for uncertain results at default - these results will be returned with an informative warning
Manual (help page) now contains more info about the algorithms
Progress bar will be shown when it takes more than 3 seconds to get results
Support for formatted console text
Console will return the percentage of uncoercable input
first_isolate():
septic_patients data set this yielded a
difference of 0.15% more isolatescol_patientid), when this argument was left
blankcol_keyantibiotics()),
when this argument was left blankoutput_logical, the function will now
always return a logical valuefilter_specimen to
specimen_group, although using filter_specimen
will still workportion functions,
that low counts can influence the outcome and that the
portion functions may camouflage this, since they only
return the portion (albeit being dependent on the minimum
argument)microorganisms.certe and
microorganisms.umcg into
microorganisms.codesmo_taxonomy() now contains the kingdom
toois.rsi.eligible() using the
new threshold argumentscale_rsi_colours()mo will now return the top 3 and the
unique count, e.g. using summary(mo)rsi and
micas.rsi():
"HIGH S" will
return Sfreq() function):
Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:
# Determine genus of microorganisms (mo) in `septic_patients` data set:
# OLD WAY
septic_patients %>%
mutate(genus = mo_genus(mo)) %>%
freq(genus)
# NEW WAY
septic_patients %>%
freq(mo_genus(mo))
# Even supports grouping variables:
septic_patients %>%
group_by(gender) %>%
freq(mo_genus(mo))Header info is now available as a list, with the
header function
The argument header is now set to TRUE
at default, even for markdown
Added header info for class mo to show unique count
of families, genera and species
Now honours the decimal.mark setting, which just
like format defaults to
getOption("OutDec")
The new big.mark argument will at default be
"," when decimal.mark = "." and
"." otherwise
Fix for header text where all observations are
NA
New argument droplevels to exclude empty factor
levels when input is a factor
Factor levels will be in header when present in input data (maximum of 5)
Fix for using select() on frequency tables
scale_y_percent() now contains the
limits argumentmdro(),
key_antibiotics() and eucast_rules()resistance_predict() function)as.mic() to support more values ending in
(several) zeroes%like%,
it will now return the callcount_all to get all available isolates (that
like all portion_* and count_* functions also
supports summarise and group_by), the old
n_rsi is now an alias of count_allget_locale to determine language for
language-dependent output for some mo_* functions. This is
now the default value for their language argument, by which
the system language will be used at default.microorganismsDT,
microorganisms.prevDT, microorganisms.unprevDT
and microorganisms.oldDT to improve the speed of
as.mo. They are for reference only, since they are
primarily for internal use of as.mo.read.4D to read from the 4D database of the
MMB department of the UMCGmo_authors and mo_year to get
specific values about the scientific reference of a taxonomic entryFunctions MDRO, BRMO, MRGN
and EUCAST_exceptional_phenotypes were renamed to
mdro, brmo, mrgn and
eucast_exceptional_phenotypes
EUCAST_rules was renamed to
eucast_rules, the old function still exists as a deprecated
function
Big changes to the eucast_rules function:
rules to specify which rules should be
applied (expert rules, breakpoints, others or all)verbose which can be set to
TRUE to get very specific messages about which columns and
rows were affectedseptic_patients now reflects these
changespipe for piperacillin (J01CA12), also to
the mdro functionAdded column kingdom to the microorganisms data set,
and function mo_kingdom to look up values
Tremendous speed improvement for as.mo (and
subsequently all mo_* functions), as empty values wil be
ignored a priori
Fewer than 3 characters as input for as.mo will
return NA
Function as.mo (and all mo_* wrappers)
now supports genus abbreviations with “species” attached
as.mo("E. species") # B_ESCHR
mo_fullname("E. spp.") # "Escherichia species"
as.mo("S. spp") # B_STPHY
mo_fullname("S. species") # "Staphylococcus species"Added argument combine_IR (TRUE/FALSE) to functions
portion_df and count_df, to indicate that all
values of I and R must be merged into one, so the output only consists
of S vs. IR (susceptible vs. non-susceptible)
Fix for portion_*(..., as_percent = TRUE) when
minimal number of isolates would not be met
Added argument also_single_tested for
portion_* and count_* functions to also
include cases where not all antibiotics were tested but at least one of
the tested antibiotics includes the target antimicribial interpretation,
see ?portion
Using portion_* functions now throws a warning when
total available isolate is below argument minimum
Functions as.mo, as.rsi,
as.mic, as.atc and freq will not
set package name as attribute anymore
Frequency tables - freq():
Support for grouping variables, test with:
septic_patients %>%
group_by(hospital_id) %>%
freq(gender)Support for (un)selecting columns:
septic_patients %>%
freq(hospital_id) %>%
select(-count, -cum_count) # only get item, percent, cum_percentCheck for hms::is.hms
Now prints in markdown at default in non-interactive sessions
No longer adds the factor level column and sorts factors on count again
Support for class difftime
New argument na, to choose which character to print
for empty values
New argument header to turn the header info off
(default when markdown = TRUE)
New argument title to manually setbthe title of the
frequency table
first_isolate now tries to find columns to use as
input when arguments are left blank
Improvements for MDRO algorithm (function
mdro)
Data set septic_patients is now a
data.frame, not a tibble anymore
Removed diacritics from all authors (columns
microorganisms$ref and microorganisms.old$ref)
to comply with CRAN policy to only allow ASCII characters
Fix for mo_property not working properly
Fix for eucast_rules where some Streptococci would
become ceftazidime R in EUCAST rule 4.5
Support for named vectors of class mo, useful for
top_freq()
ggplot_rsi and scale_y_percent have
breaks argument
AI improvements for as.mo:
"CRS" -> Stenotrophomonas maltophilia"CRSM" -> Stenotrophomonas maltophilia"MSSA" -> Staphylococcus aureus"MSSE" -> Staphylococcus epidermidisFix for join functions
Speed improvement for is.rsi.eligible, now 15-20
times faster
In g.test, when sum(x) is below 1000 or
any of the expected values is below 5, Fisher’s Exact Test will be
suggested
ab_name will try to fall back on as.atc
when no results are found
Removed the addin to view data sets
Percentages will now will rounded more logically (e.g. in
freq function)
crayon, to support formatted
text in the consoletidyr is now mandatory (went to
Import field) since portion_df and
count_df rely on itThe data set microorganisms now contains all
microbial taxonomic data from ITIS (kingdoms Bacteria, Fungi
and Protozoa), the Integrated Taxonomy Information System, available via
https://itis.gov. The data set now contains more than 18,000
microorganisms with all known bacteria, fungi and protozoa according
ITIS with genus, species, subspecies, family, order, class, phylum and
subkingdom. The new data set microorganisms.old contains
all previously known taxonomic names from those kingdoms.
New functions based on the existing function
mo_property:
mo_phylum, mo_class,
mo_order, mo_family, mo_genus,
mo_species, mo_subspeciesmo_fullname,
mo_shortnamemo_type,
mo_gramstainmo_refThey also come with support for German, Dutch, French, Italian, Spanish and Portuguese:
mo_gramstain("E. coli")
# [1] "Gram negative"
mo_gramstain("E. coli", language = "de") # German
# [1] "Gramnegativ"
mo_gramstain("E. coli", language = "es") # Spanish
# [1] "Gram negativo"
mo_fullname("S. group A", language = "pt") # Portuguese
# [1] "Streptococcus grupo A"Furthermore, former taxonomic names will give a note about the current taxonomic name:
mo_gramstain("Esc blattae")
# Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)
# [1] "Gram negative"Functions count_R, count_IR,
count_I, count_SI and count_S to
selectively count resistant or susceptible isolates
count_df (which works like
portion_df) to get all counts of S, I and R of a data set
with antibiotic columns, with support for grouped variablesFunction is.rsi.eligible to check for columns that
have valid antimicrobial results, but do not have the rsi
class yet. Transform the columns of your raw data with:
data %>% mutate_if(is.rsi.eligible, as.rsi)
Functions as.mo and is.mo as
replacements for as.bactid and is.bactid
(since the microoganisms data set not only contains
bacteria). These last two functions are deprecated and will be removed
in a future release. The as.mo function determines
microbial IDs using intelligent rules:
as.mo("E. coli")
# [1] B_ESCHR_COL
as.mo("MRSA")
# [1] B_STPHY_AUR
as.mo("S group A")
# [1] B_STRPTC_GRAAnd with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:
thousands_of_E_colis <- rep("E. coli", 25000)
microbenchmark::microbenchmark(as.mo(thousands_of_E_colis), unit = "s")
# Unit: seconds
# min median max neval
# 0.01817717 0.01843957 0.03878077 100Added argument reference_df for as.mo,
so users can supply their own microbial IDs, name or codes as a
reference table
Renamed all previous references to bactid to
mo, like:
EUCAST_rules,
first_isolate and key_antibioticsmicroorganisms and
septic_patientsFunction labels_rsi_count to print datalabels on a
RSI ggplot2 model
Functions as.atc and is.atc to
transform/look up antibiotic ATC codes as defined by the WHO. The
existing function guess_atc is now an alias of
as.atc.
Function ab_property and its aliases:
ab_name, ab_tradenames, ab_certe,
ab_umcg and ab_trivial_nl
Introduction to AMR as a vignette
Removed clipboard functions as it violated the CRAN policy
Renamed septic_patients$sex to
septic_patients$gender
Added three antimicrobial agents to the antibiotics
data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole
(D01AC05)
Added 163 trade names to the antibiotics data set,
it now contains 298 different trade names in total, e.g.:
ab_official("Bactroban")
# [1] "Mupirocin"
ab_name(c("Bactroban", "Amoxil", "Zithromax", "Floxapen"))
# [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin"
ab_atc(c("Bactroban", "Amoxil", "Zithromax", "Floxapen"))
# [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"For first_isolate, rows will be ignored when there’s
no species available
Function ratio is now deprecated and will be removed
in a future release, as it is not really the scope of this
package
Fix for as.mic for values ending in zeroes after a
real number
Small fix where B. fragilis would not be found in the
microorganisms.umcg data set
Added prevalence column to the
microorganisms data set
Added arguments minimum and as_percent
to portion_df
Support for quasiquotation in the functions series
count_* and portions_*, and
n_rsi. This allows to check for more than 2 vectors or
columns.
septic_patients %>% select(amox, cipr) %>% count_IR()
# which is the same as:
septic_patients %>% count_IR(amox, cipr)
septic_patients %>% portion_S(amcl)
septic_patients %>% portion_S(amcl, gent)
septic_patients %>% portion_S(amcl, gent, pita)Edited ggplot_rsi and geom_rsi so they
can cope with count_df. The new fun argument
has value portion_df at default, but can be set to
count_df.
Fix for ggplot_rsi when the ggplot2
package was not loaded
Added datalabels function labels_rsi_count to
ggplot_rsi
Added possibility to set any argument to geom_rsi
(and ggplot_rsi) so you can set your own
preferences
Fix for joins, where predefined suffices would not be honoured
Added argument quote to the freq
function
Added generic function diff for frequency
tables
Added longest en shortest character length in the frequency table
(freq) header of class character
Support for types (classes) list and matrix for
freq
my_matrix = with(septic_patients, matrix(c(age, gender), ncol = 2))
freq(my_matrix)For lists, subsetting is possible:
my_list = list(age = septic_patients$age, gender = septic_patients$gender)
my_list %>% freq(age)
my_list %>% freq(gender)rsi_df was removed in favour
of new functions portion_R, portion_IR,
portion_I, portion_SI and
portion_S to selectively calculate resistance or
susceptibility. These functions are 20 to 30 times faster than the old
rsi function. The old function still works, but is
deprecated.
portion_df to get all portions of S, I and
R of a data set with antibiotic columns, with support for grouped
variablesggplot2
geom_rsi, facet_rsi,
scale_y_percent, scale_rsi_colours and
theme_rsiggplot_rsi to apply all above
functions on a data set:
septic_patients %>% select(tobr, gent) %>% ggplot_rsi
will show portions of S, I and R immediately in a pretty plot?ggplot_rsias.bactid and is.bactid to
transform/ look up microbial ID’s.guess_bactid is now an alias of
as.bactidkurtosis and skewness that are lacking in base
R - they are generic functions and have support for vectors, data.frames
and matricesg.test to perform the X2
distributed G-test, which
use is the same as chisq.testratio to transform a vector of values to
a preset ratioratio(c(10, 500, 10), ratio = "1:2:1") would return
130, 260, 130%in% or %like% (and give them keyboard
shortcuts), or to view the datasets that come with this packagep.symbol to transform p values to their
related symbols:
0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1clipboard_import and
clipboard_export as helper functions to quickly copy and
paste from/to software like Excel and SPSS. These functions use the
clipr package, but are a little altered to also support
headless Linux servers (so you can use it in RStudio Server)freq):
rsi (antimicrobial resistance) to use as
inputtable to use as input:
freq(table(x, y))hist and
plot to use a frequency table as input:
hist(freq(df$age))as.vector, as.data.frame,
as_tibble and formatfreq(mydata, mycolumn) is
the same as mydata %>% freq(mycolumn)top_freq function to return the top/below
n items as vectoroptions(max.print.freq = n) where n is
your preset valueresistance_predict
and added more examplesseptic_patients data set to
better reflect the realitymic and rsi classes now
returns all values - use freq to check distributionskey_antibiotics function are now
generic: 6 for broadspectrum ABs, 6 for Gram-positive specific and 6 for
Gram-negative specific ABsabname function%like% now supports multiple patternsdata.frames with
altered console printing to make it look like a frequency table. Because
of this, the argument toConsole is not longer needed.freq where the class of an item would be
lostseptic_patients
dataset and the column bactid now has the new class
"bactid"microorganisms dataset
(especially for Salmonella) and the column bactid
now has the new class "bactid"rsi
and mic functions:
as.rsi("<=0.002; S") will return Sas.mic("<=0.002; S") will return
<=0.002as.mic("<= 0.002") now worksrsi and mic do not add the
attribute package.version anymore"groups" option for
atc_property(..., property). It will return a vector of the
ATC hierarchy as defined by the WHO. The
new function atc_groups is a convenient wrapper around
this.atc_property as it requires the
host set by url to be responsivefirst_isolate algorithm to exclude isolates
where bacteria ID or genus is unavailable924b62)
from the dplyr package v0.7.5 and aboveguess_bactid (now called as.bactid)
yourdata %>% select(genus, species) %>% as.bactid()
now also worksn_rsi to count cases where antibiotic test
results were available, to be used in conjunction with
dplyr::summarise, see ?rsiguess_bactid to determine the
ID of a microorganism based on genus/species or known
abbreviations like MRSAguess_atc to determine the
ATC of an antibiotic based on name, trade name, or known
abbreviationsfreq to create frequency
tables, with additional info in a headerMDRO to determine Multi Drug Resistant
Organisms (MDRO) with support for country-specific guidelines.
BRMO and MRGN are wrappers for
Dutch and German guidelines, respectively"points" or "keyantibiotics", see
?first_isolatetibbles and
data.tablesrsi class for vectors that contain only invalid
antimicrobial interpretationsablist to antibioticsbactlist to
microorganismsantibiotics datasetmicroorganisms
datasetseptic_patientsjoin
functions%like% to make it case insensitivefirst_isolate and
EUCAST_rules column names are now case-insensitiveas.rsi and as.mic now add the
package name and version as attributesREADME.md with more examplestestthat packageEUCAST_rules applies for amoxicillin even if ampicillin
is missingrsi and mic
classes