- Removed all functions and references that used the deprecated
rsi
class, which were all replaced with theirsir
equivalents a year ago
- Function group
scale_*_mic()
, namely:scale_x_mic()
,scale_y_mic()
,scale_colour_mic()
andscale_fill_mic()
. They are advanced ggplot2 extensions to allow plotting of MIC values. They allow for manual range definition and plotting missing intermediate log2 levels. - Function
rescale_mic()
, which allows to rescale MIC values to a manually set range. This is the powerhouse behind thescale_*_mic()
functions, but it can be used by users directly to e.g. compare equality in MIC distributions by rescaling them to the same range first.
- For MICs:
- Added 4096 and 5 powers of 192 as valid levels (192, 384, 576, 768, 960)
- Added new argument
keep_operators
toas.mic()
. This can be"all"
(default),"none"
, or"edges"
.
- Fix for selecting first isolates using the phenotype-based method
- This included too many isolates when patients had altering antibiograms within the same bacterial species
- See for more info our issue #122
- Added 1,366 LOINC codes to the
antibiotics
data set and updated to the latest version (LOINC v2.76) - MICs can now be used in complex number calculations and allow scientific number format as input (e.g.,
as.mic("1.28e-2")
) - Fix rounding MICs on latest R beta ('R-devel')
- Removed unneeded note about the used language when option
AMR_locale
is set - Fixed non-ASCII characters in documentation, according to CRAN maintainers
- Regarding clinical breakpoints:
- Clinical breakpoints and intrinsic resistance of EUCAST 2023 and CLSI 2023 have been added to the
clinical_breakpoints
data set for usage inas.sir()
. EUCAST 2023 (v13.0) is now the new default guideline for all MIC and disks diffusion interpretations - The EUCAST dosage guideline of v13.0 has been added to the
dosage
data set - The
clinical_breakpoints
data set now also contains epidemiological cut-off (ECOFF) values and CLSI animal breakpoints. These two new breakpoint types can be used for MIC/disk interpretation usingas.sir(..., breakpoint_type = "ECOFF")
oras.sir(..., breakpoint_type = "animal")
, which is an important new addition for veterinary microbiology.
- Clinical breakpoints and intrinsic resistance of EUCAST 2023 and CLSI 2023 have been added to the
- Added support for 30 species groups / complexes. They are gathered in a new data set
microorganisms.groups
and are used in clinical breakpoint interpretation. For example, CLSI 2023 contains breakpoints for the RGM group (Rapidly Growing Mycobacterium, containing over 80 species) which is now supported by our package. - Added oxygen tolerance from BacDive to over 25,000 bacteria in the
microorganisms
data set- Added
mo_oxygen_tolerance()
to retrieve the values - Added
mo_is_anaerobic()
to determine which genera/species are obligate anaerobic bacteria
- Added
- Added LPSN and GBIF identifiers, and oxygen tolerance to
mo_info()
- Added SAS Transport files (file extension
.xpt
) to our download page to use in SAS software - Added microbial codes for Gram-negative/positive anaerobic bacteria
- Updated algorithm of
as.mo()
by giving more weight to fungi - Fixed clinical breakpoints errors introduced by the source we import the rules from
mo_rank()
now returnsNA
for 'unknown' microorganisms (B_ANAER
,B_ANAER-NEG
,B_ANAER-POS
,B_GRAMN
,B_GRAMP
,F_FUNGUS
,F_YEAST
, andUNKNOWN
)- When printing microorganism or antibiotic codes in a tibble, a mouse-hover now shows the full name of the code
- Plots for MIC and disk diffusion values:
- Now have settable arguments for breakpoint type and PK/PD, like
as.sir()
- Will now contain the name of the guideline table in the subtitle of the plot
- Now have settable arguments for breakpoint type and PK/PD, like
- Fixed formatting for
sir_interpretation_history()
- Fixed some WHONET codes for microorganisms and consequently a couple of entries in
clinical_breakpoints
- Fixed a bug for
as.mo()
that led to coercion ofNA
values when using custom microorganism codes - Fixed usage of
icu_exclude
infirst_isolates()
- Improved
as.mo()
algorithm:- Now allows searching on only species names
- Fix for using the
keep_synonyms
argument when using MO codes as input - Fix for using the
minimum_matching_score
argument
- Updated the code table in
microorganisms.codes
- Fixed an endless loop if using
reference_df
inas.mo()
- Fixed bug for indicating UTIs in
as.sir()
- Greatly improved speed of
as.sir()
This is a new major release of the AMR package, with great new additions but also some breaking changes for current users. These are all listed below.
- All functions and arguments with 'rsi' were replaced with 'sir', such as the interpretation of MIC values (now
as.sir()
instead ofas.rsi()
) - all old functions still work for now - Many new interesting functions, such as
antibiogram()
(for generating traditional/combined/syndromic/WISCA antibiograms),sir_confidence_interval()
andmean_amr_distance()
, andadd_custom_microorganisms()
to add custom microorganisms to this package - Clinical breakpoints added for EUCAST 2022 and CLSI 2022
- Microbiological taxonomy (
microorganisms
data set) updated to 2022 and now based on LPSN and GBIF - Much increased algorithms to translate user input to valid taxonomy, e.g. by using recent scientific work about per-species human pathogenicity
- 20 new antibiotics added and updated all DDDs and ATC codes
- Extended support for antiviral agents (
antivirals
data set), with many new functions - Now available in 20 languages
- Many small bug fixes
For this milestone version, we replaced all mentions of RSI with SIR, to comply with what is actually being commonly used in the field of clinical microbiology when it comes to this tri-form regarding AMR.
While existing functions such as as.rsi()
, rsi_df()
and ggplot_rsi()
still work, their replacements as.sir()
, sir_df()
, ggplot_sir()
are now the current functions for AMR data analysis. A warning will be thrown once a session to remind users about this. The data set rsi_translation
is now called clinical_breakpoints
to better reflect its content.
The 'RSI functions' will be removed in a future version, but not before late 2023 / early 2024.
With the new antibiogram()
function, users can now generate traditional, combined, syndromic, and even weighted-incidence syndromic combination antibiograms (WISCA). With this, we follow the logic in the previously described work of Klinker et al. (2021, DOI 10.1177/20499361211011373) and Barbieri et al. (2021, DOI 10.1186/s13756-021-00939-2).
The help page for antibiogram()
extensively elaborates on use cases, and antibiogram()
also supports printing in R Markdown and Quarto, with support for 20 languages.
Furthermore, different plotting methods were implemented to allow for graphical visualisations as well.
The clinical breakpoints and intrinsic resistance of EUCAST 2022 and CLSI 2022 have been added for as.sir()
. EUCAST 2022 (v12.0) is now the new default guideline for all MIC and disks diffusion interpretations, and for eucast_rules()
to apply EUCAST Expert Rules. The default guideline (EUCAST) can now be changed with the new AMR_guideline
option, such as: options(AMR_guideline = "CLSI 2020")
.
With the new arguments include_PKPD
(default: TRUE
) and include_screening
(default: FALSE
), users can now specify whether breakpoints for screening and from the PK/PD table should be included when interpreting MICs and disks diffusion values. These options can be set globally, which can be read in our new manual.
Interpretation guidelines older than 10 years were removed, the oldest now included guidelines of EUCAST and CLSI are from 2013.
We added support for the following ten languages: Chinese (simplified), Czech, Finnish, Greek, Japanese, Norwegian (bokmål), Polish, Romanian, Turkish and Ukrainian. All antibiotic names are now available in these languages, and the AMR package will automatically determine a supported language based on the user's system language.
We are very grateful for the valuable input by our colleagues from other countries. The AMR
package is now available in 20 languages in total, and according to download stats used in almost all countries in the world!
For analysis in outbreak management, we updated the get_episode()
and is_new_episode()
functions: they now contain an argument case_free_days
. This argument can be used to quantify the duration of case-free days (the inter-epidemic interval), after which a new episode will start.
This is common requirement in outbreak management, e.g. when determining the number of norovirus outbreaks in a hospital. The case-free period could then be 14 or 28 days, so that new norovirus cases after that time will be considered a different (or new) episode.
The microorganisms
data set no longer relies on the Catalogue of Life, but on the List of Prokaryotic names with Standing in Nomenclature (LPSN) and is supplemented with the 'backbone taxonomy' from the Global Biodiversity Information Facility (GBIF). The structure of this data set has changed to include separate LPSN and GBIF identifiers. Almost all previous MO codes were retained. It contains over 1,400 taxonomic names from 2022.
We previously relied on our own experience to categorise species into pathogenic groups, but we were very happy to encounter the very recent work of Bartlett et al. (2022, DOI 10.1099/mic.0.001269) who extensively studied medical-scientific literature to categorise all bacterial species into groups. See mo_matching_score()
on how their work was incorporated into the prevalence
column of the microorganisms
data set. Using their results, the as.mo()
and all mo_*()
functions are now much better capable of converting user input to valid taxonomic records.
The new function add_custom_microorganisms()
allows users to add custom microorganisms to the AMR
package.
We also made the following changes regarding the included taxonomy or microorganisms functions:
- Updated full microbiological taxonomy according to the latest daily LPSN data set (December 2022) and latest yearly GBIF taxonomy backbone (November 2022)
- Added function
mo_current()
to get the currently valid taxonomic name of a microorganism - Support for all 1,516 city-like serovars of Salmonella, such as Salmonella Goldcoast. Formally, these are serovars belonging to the S. enterica species, but they are reported with only the name of the genus and the city. For this reason, the serovars are in the
subspecies
column of themicroorganisms
data set and "enterica" is in thespecies
column, but the full name does not contain the species name (enterica). - All new algorithm for
as.mo()
(and thus allmo_*()
functions) while still following our original set-up as described in our recently published JSS paper (DOI 10.18637/jss.v104.i03).- A new argument
keep_synonyms
allows to not correct for updated taxonomy, in favour of the now deleted argumentallow_uncertain
- It has increased tremendously in speed and returns generally more consequent results
- Sequential coercion is now extremely fast as results are stored to the package environment, although coercion of unknown values must be run once per session. Previous results can be reset/removed with the new
mo_reset_session()
function. - Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net)
- The MO matching score algorithm (
mo_matching_score()
) now counts deletions and substitutions as 2 instead of 1, which impacts the outcome ofas.mo()
and anymo_*()
function
- A new argument
- Removed all species of the taxonomic kingdom Chromista from the package. This was done for multiple reasons:
- CRAN allows packages to be around 5 MB maximum, some packages are exempted but this package is not one of them
- Chromista are not relevant when it comes to antimicrobial resistance, thus lacking the primary scope of this package
- Chromista are almost never clinically relevant, thus lacking the secondary scope of this package
- The
microorganisms.old
data set was removed, and all previously accepted names are now included in themicroorganisms
data set. A new columnstatus
contains"accepted"
for currently accepted names and"synonym"
for taxonomic synonyms; currently invalid names. All previously accepted names now have a microorganisms ID and - if available - an LPSN, GBIF and SNOMED CT identifier.
The new function add_custom_antimicrobials()
allows users to add custom antimicrobial codes and names to the AMR
package.
The antibiotics
data set was greatly updated:
- The following 20 antibiotics have been added (also includes the new J01RA ATC group): azithromycin/fluconazole/secnidazole (AFC), cefepime/amikacin (CFA), cefixime/ornidazole (CEO), ceftriaxone/beta-lactamase inhibitor (CEB), ciprofloxacin/metronidazole (CIM), ciprofloxacin/ornidazole (CIO), ciprofloxacin/tinidazole (CIT), furazidin (FUR), isoniazid/sulfamethoxazole/trimethoprim/pyridoxine (IST), lascufloxacin (LSC), levofloxacin/ornidazole (LEO), nemonoxacin (NEM), norfloxacin/metronidazole (NME), norfloxacin/tinidazole (NTI), ofloxacin/ornidazole (OOR), oteseconazole (OTE), rifampicin/ethambutol/isoniazid (REI), sarecycline (SRC), tetracycline/oleandomycin (TOL), and thioacetazone (TAT)
- Added some missing ATC codes
- Updated DDDs and PubChem Compound IDs
- Updated some antibiotic name spelling, now used by WHOCC (such as cephalexin -> cefalexin, and phenethicillin -> pheneticillin)
- Antibiotic code "CEI" for ceftolozane/tazobactam has been replaced with "CZT" to comply with EARS-Net and WHONET 2022. The old code will still work in all cases when using
as.ab()
or any of theab_*()
functions. - Support for antimicrobial interpretation of anaerobic bacteria, by adding a 'placeholder' code
B_ANAER
to themicroorganisms
data set and adding the breakpoints of anaerobics to theclinical_breakpoints
data set, which is used byas.sir()
for interpretion of MIC and disk diffusion values
Also, we added support for using antibiotic selectors in scoped dplyr
verbs (with or without using vars()
), such as in: ... %>% summarise_at(aminoglycosides(), resistance)
, please see resistance()
for examples.
We now added extensive support for antiviral agents! For the first time, the AMR
package has extensive support for antiviral drugs and to work with their names, codes and other data in any way.
- The
antivirals
data set has been extended with 18 new drugs (also from the new J05AJ ATC group) and now also contains antiviral identifiers and LOINC codes - A new data type
av
(antivirals) has been added, which is functionally similar toab
for antibiotics - Functions
as.av()
,av_name()
,av_atc()
,av_synonyms()
,av_from_text()
have all been added as siblings to theirab_*()
equivalents
- Function
sir_confidence_interval()
to add confidence intervals in AMR calculation. This is now also included insir_df()
andproportion_df()
. - Function
mean_amr_distance()
to calculate the mean AMR distance. The mean AMR distance is a normalised numeric value to compare AMR test results and can help to identify similar isolates, without comparing antibiograms by hand. - Function
sir_interpretation_history()
to view the history of previous runs ofas.sir()
(previouslyas.rsi()
). This returns a 'logbook' with the selected guideline, reference table and specific interpretation of each row in a data set on whichas.sir()
was run.
get_episode()
(and its wrapperis_new_episode()
):- Fix for working with
NA
values - Fix for unsorted dates of length 2
- Now returns class
integer
instead ofnumeric
since they are always whole numbers
- Fix for working with
- Argument
combine_IR
has been removed from this package (affecting functionscount_df()
,proportion_df()
, andsir_df()
and some plotting functions), since it was replaced withcombine_SI
three years ago - Using
units
inab_ddd(..., units = "...")
had been deprecated for some time and is now not supported anymore. Useab_ddd_units()
instead. - Support for
data.frame
-enhancing R packages, more specifically:data.table::data.table
,janitor::tabyl
,tibble::tibble
, andtsibble::tsibble
. AMR package functions that have a data set as output (such assir_df()
andbug_drug_combinations()
), will now return the same data type as the input. - All data sets in this package are now a
tibble
, instead of base Rdata.frame
s. Older R versions are still supported, even if they do not supporttibble
s. - Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info in this article on our website.
- For
as.sir()
:- Fixed certain EUCAST breakpoints for MIC values
- Allow
NA
values (e.g.as.sir(as.disk(NA), ...)
) - Fix for bug-drug combinations with multiple breakpoints for different body sites
- Interpretation from MIC and disk zones is now more informative about availability of breakpoints and more robust
- Removed the
as.integer()
method for MIC values, since MIC are not integer values and runningtable()
on MIC values consequently failed for not being able to retrieve the level position (as that's how normallyas.integer()
onfactor
s work) - Fixed determination of Gram stains (
mo_gramstain()
), since the taxonomic phyla Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes have been renamed to respectively Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota in 2021 droplevels()
on MIC will now return a commonfactor
at default and will lose themic
class. Usedroplevels(..., as.mic = TRUE)
to keep themic
class.- Small fix for using
ab_from_text()
- Fixes for reading in text files using
set_mo_source()
, which now also allows the source file to contain valid taxonomic names instead of only valid microorganism ID of this package - Fixed a bug for
mdro()
when using similar column names with the Magiorakos guideline - Using any
random_*()
function (such asrandom_mic()
) is now possible by directly calling the package without loading it first:AMR::random_mic(10)
- Extended support for the
vctrs
package, used internally by the tidyverse. This allows to change values of classmic
,disk
,sir
,mo
andab
in tibbles, and to use antibiotic selectors for selecting/filtering, e.g.df[carbapenems() == "R", ]
- Fix for using
info = FALSE
inmdro()
- For all interpretation guidelines using
as.sir()
on amoxicillin, the rules for ampicillin will be used if amoxicillin rules are not available - Fix for using
ab_atc()
on non-existing ATC codes - Black and white message texts are now reversed in colour if using an RStudio dark theme
mo_snomed()
now returns classcharacter
, notnumeric
anymore (to make long SNOMED codes readable)- Fix for using
as.ab()
onNA
values - Updated support for all WHONET 2022 microorganism codes
- Antimicrobial interpretation 'SDD' (susceptible dose-dependent, coined by CLSI) will be interpreted as 'I' to comply with EUCAST's 'I' in
as.sir()
- Fix for
mo_shortname()
in case of higher taxonomic ranks (order, class, phylum) - Cleaning columns with
as.sir()
,as.mic()
, oras.disk()
will now show the column name in the warning for invalid results - Fix for using
g.test()
with zeroes in a 2x2 table mo_synonyns()
now contains the scientific reference as names
- Added Peter Dutey-Magni, Dmytro Mykhailenko, Anton Mymrikov, Andrew Norgan, Jonas Salm, and Anita Williams as contributors, to thank them for their valuable input
- New website to make use of the new Bootstrap 5 and pkgdown 2.0. The website now contains results for all examples and will be automatically regenerated with every change to our repository, using GitHub Actions
- All R and Rmd files in this project are now styled using the
styler
package - Set scalar conditional expressions (
&&
and||
) where possible to comply with the upcoming R 4.3 - An enormous lot of code cleaning, fixing some small bugs along the way
This changelog only contains changes from AMR v2.0 (January 2023) and later. For prior versions, please see our archive.