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2 years ago
# AMR 1.6.0
### New
* 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.
* Added function `eucast_dosage()` to get a `data.frame` with advised dosages of a certain bug-drug combination, which is based on the new `dosage` data set
* Added data set `dosage` to fuel the new `eucast_dosage()` function and to make this data available in a structured way
* Existing data set `example_isolates` now reflects the latest EUCAST rules
* Added 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:
* All antibiotic selector functions (`ab_class()` and its wrappers, such as `aminoglycosides()`, `carbapenems()`, `penicillins()`)
* All antibiotic filter functions (`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
```r
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:
```r
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()) # dplyr
```
The `mo_type()` function has also been updated to reflect this change:
```r
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:
```r
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 8
```
### Changed
* Updated the bacterial taxonomy to 3 March 2021 (using [LSPN](https://lpsn.dsmz.de))
* Added 3,372 new species and 1,523 existing species became synomyms
* The URL of a bacterial species (`mo_url()`) will now lead to https://lpsn.dsmz.de
* Big update for plotting classes `rsi`, `<mic>`, and `<disk>`:
* Plotting of MIC and disk diffusion values now support interpretation colouring if you supply the microorganism and antimicrobial agent
* All colours were updated to colour-blind friendly versions for values R, S and I for all plot methods (also applies to tibble printing)
* Interpretation of MIC and disk diffusion values to R/SI will now be translated if the system language is German, Dutch or Spanish (see `translate`)
* Plotting is now possible with base R using `plot()` and with ggplot2 using `ggplot()` on any vector of MIC and disk diffusion values
* Updated SNOMED codes to US Edition of SNOMED CT from 1 September 2020 and added the source to the help page of the `microorganisms` data set
* `is.rsi()` and `is.rsi.eligible()` now return a vector of `TRUE`/`FALSE` when the input is a data set, by iterating over all columns
* Using functions without setting a data set (e.g., `mo_is_gram_negative()`, `mo_is_gram_positive()`, `mo_is_intrinsic_resistant()`, `first_isolate()`, `mdro()`) now work with `dplyr`s `group_by()` again
* `first_isolate()` can be used with `group_by()` (also when using a dot `.` as input for the data) and now returns the names of the groups
* Updated the data set `microorganisms.codes` (which contains popular LIS and WHONET codes for microorganisms) for some species of *Mycobacterium* that previously incorrectly returned *M. africanum*
* WHONET code `"PNV"` will now correctly be interpreted as `PHN`, the antibiotic code for phenoxymethylpenicillin ('peni V')
* Fix for verbose output of `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.
* Functions `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)
* Argument `ampc_cephalosporin_resistance` in `eucast_rules()` now also applies to value "I" (not only "S")
* Functions `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()`
* Improved speed and reliability of `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.
* Fix for `mo_name()` when used in other languages than English
* The `like()` 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)
* *Staphylococcus cornubiensis* is now correctly categorised as coagulase-positive
* `random_disk()` and `random_mic()` now have an expanded range in their randomisation
* Support for GISA (glycopeptide-intermediate *S. aureus*), so e.g. `mo_genus("GISA")` will return `"Staphylococcus"`
* Added translations of German and Spanish for more than 200 antimicrobial drugs
* Speed improvement for `as.ab()` when the input is an official name or ATC code
* Added argument `include_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 empty
2 years ago
### Other
* Big documentation updates
* Loading the package (i.e., `library(AMR)`) now is ~50 times faster than before, in costs of package size (which increased by ~3 MB)
# AMR 1.5.0
2 years ago
### New
* 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 `dplyr`s grouping (i.e. using `group_by()`):
```r
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](https://www.eucast.org/expert_rules_and_intrinsic_resistance/) 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.
### Changed
* New argument `ampc_cephalosporin_resistance` in `eucast_rules()` to correct for AmpC de-repressed cephalosporin-resistant mutants
* Interpretation of antimicrobial resistance - `as.rsi()`:
* Reference data used for `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`.
* Better determination of disk zones and MIC values when running `as.rsi()` on a data.frame
* Fix for using `as.rsi()` on a data.frame in older R versions
* `as.rsi()` on a data.frame will not print a message anymore if the values are already clean R/SI values
* If using `as.rsi()` on MICs or disk diffusion while there is intrinsic antimicrobial resistance, a warning will be thrown to remind about this
* Fix for using `as.rsi()` on a `data.frame` that only contains one column for antibiotic interpretations
* Some 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()`
```r
# 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()
```
2 years ago
* 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):
```r
# 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`](https://github.com/moodymudskipper/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](https://github.com/msberends/AMR/blob/v1.4.0/R/p_symbol.R) 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 <mo> in tibbles when all values are `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
### Other
* All messages and warnings thrown by this package now break sentences on whole words
* More extensive unit tests
* Internal calls to `options()` were all removed in favour of a new internal environment `pkg_env`
* Improved internal type setting (among other things: replaced all `sapply()` calls with `vapply()`)
* Added CodeFactor as a continuous code review to this package: <https://www.codefactor.io/repository/github/msberends/amr/>
* Added Dr. Rogier Schade as contributor
# AMR 1.4.0
### New
* 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?
```r
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
### Changed
* 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.
```r
# 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:
```r
as.disk(c("disk zone: 23.4 mm", 23.4))
#> Class <disk>
#> [1] 24 24
```
* Improvements for `as.mo()`:
* A completely new matching score for ambiguous user input, using `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.
* Big speed improvement for already valid microorganism ID. This also means an significant speed improvement for using `mo_*` functions like `mo_name()` on microoganism IDs.
* Added argument `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 `tibble`s 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:
* Updated oral and parental DDDs from the WHOCC
* Added abbreviation "piptazo" to 'Piperacillin/tazobactam' (TZP)
* 'Penicillin G' (for intravenous use) is now named 'Benzylpenicillin' (code `PEN`)
* 'Penicillin V' (for oral use, code `PNV`) was removed, since its actual entry 'Phenoxymethylpenicillin' (code `PHN`) already existed
* The group name (`antibiotics$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.
2 years ago
### Other
* Removed functions `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()`
* Removed unnecessary references to the `base` package
* Added packages that could be useful for some functions to the `Suggests` field of the `DESCRIPTION` file
# AMR 1.3.0
### New
* Function `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](https://tidyselect.r-lib.org/reference/language.html) 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()`:
```r
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)`.
### Changed
* 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:
* 95% speed improvement by using other base R functions for calculation
* Using unexisting columns wil now return an error instead of dropping them silently
* Using variables for column names (as well as selectors like `dplyr::all_of()`) now works again
* Improvements for `as.ab()`:
* Dramatic improvement of the algorithm behind `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 more
* Added progress bar
* Fixed a bug where `as.ab()` would return an error on invalid input values
* The `as.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. `tibble`s and `data.table`s)
* For functions `rsi_df()`, `proportion_df()` and `count_df()`:
* Fixed a bug for using grouped versions
* Fixed a bug where not all different antimicrobial results were added as rows
* Fixed a bug when only calculating counts (`count_df()`) when all antibiotics in the data set have only `NA`s
* Improved 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`)
2 years ago
### Other
* Moved primary location of this project from GitLab to [GitHub](https://github.com/msberends/AMR), giving us native support for automated syntax checking without being dependent on external services such as AppVeyor and Travis CI.
# AMR 1.2.0
### Breaking
* 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:
* Function `freq()` that was borrowed from the `cleaner` package was removed. Use `cleaner::freq()`, or run `library("cleaner")` before you use `freq()`.
* ~~Printing values of class `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.~~
* ~~All functions from the `mo_*` family (like `mo_name()` and `mo_gramstain()`) are noticeably slower when running on hundreds of thousands of rows.~~
* For developers: classes `mo` and `ab` now both also inherit class `character`, to support any data transformation. This change invalidates code that checks for class length == 1.
### Changed
* Taxonomy:
* Updated the taxonomy of microorganisms to May 2020, using the Catalogue of Life (CoL), the Global Biodiversity Information Facility (GBIF) and the List of Prokaryotic names with Standing in Nomenclature (LPSN, hosted by DSMZ since February 2020). **Note:** a taxonomic update may always impact determination of first isolates (using `first_isolate()`), since some bacterial names might be renamed to other genera or other (sub)species. This is expected behaviour.
* Removed the Catalogue of Life IDs (like 776351), since they now work with a species ID (hexadecimal string)
* EUCAST rules:
* The `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")`.
* Fixed a bug where checking antimicrobial results in the original data were not regarded as valid R/SI values
* All "other" rules now apply for all drug combinations in the `antibiotics` data set these two rules:
1. A drug **with** enzyme inhibitor will be set to S if the drug **without** enzyme inhibitor is S
2. A drug **without** enzyme inhibitor will be set to R if the drug **with** enzyme inhibitor is R
This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/avibactam, trimethoprim/sulfamethoxazole, etc.
* Added official drug names to verbose output of `eucast_rules()`
* Added function `ab_url()` to return the direct URL of an antimicrobial agent from the official WHO website
* Improvements for algorithm in `as.ab()`, so that e.g. `as.ab("ampi sul")` and `ab_name("ampi sul")` work
* Functions `ab_atc()` and `ab_group()` now return `NA` if no antimicrobial agent could be found
* Small fix for some text input that could not be coerced as valid MIC values
* Fix for interpretation of generic CLSI interpretation rules (thanks to Anthony Underwood)
* Fix for `set_mo_source()` to make sure that column `mo` will always be the second column
* Added abbreviation "cfsc" for Cefoxitin and "cfav" for Ceftazidime/avibactam
### Other
* Removed previously deprecated function `p.symbol()` - it was replaced with `p_symbol()`
* Removed function `read.4d()`, that was only useful for reading data from an old test database.
3 years ago
# AMR 1.1.0
### New
* Support for easy principal component analysis for AMR, using the new `pca()` function
* Plotting biplots for principal component analysis using the new `ggplot_pca()` function
### Changed
* Improvements for the algorithm used by `as.mo()` (and consequently all `mo_*` functions, that use `as.mo()` internally):
* Support for codes ending with `SPE` for species, like `"ESCSPE"` for *Escherichia coli*
* Support for any encoding, which means that any language-specific character with accents can be used for input
* Support for more arbitrary IDs used in laboratory information systems
* Small fix for preventing viruses being treated as bacteria
* Small fix for preventing contamination and lack of growth being treated as valid microorganisms
* Support for all abbreviations of antibiotics and antimycotics used by the Netherlands National Institute for Public Health and the Environment (Rijksinstituut voor Volksgezondheid en Milieu; RIVM)
* Added more abbreviations to the `antibiotics` data set
* Reloaded original EUCAST master tables from 2019 (2020 was already available). This seems more reliable than the data we used from WHONET.
* Added generic CLSI rules for R/SI interpretation using `as.rsi()` for years 2010-2019 (thanks to Anthony Underwood)
### Other
* Support for the upcoming `dplyr` version 1.0.0
* More robust assigning for classes `rsi` and `mic`
3 years ago
# AMR 1.0.1
### Changed
3 years ago
* Fixed 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:
```r
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)
3 years ago
# AMR 1.0.0
This software is now out of beta and considered stable. Nonetheless, this package will be developed continually.
### New
* Support for the newest [EUCAST Clinical Breakpoint Tables v.10.0](https://www.eucast.org/clinical_breakpoints/), valid from 1 January 2020. This affects translation of MIC and disk zones using `as.rsi()` and inferred resistance and susceptibility using `eucast_rules()`.
* The repository of this package now contains a clean version of the EUCAST and CLSI guidelines from 2011-2020 to translate MIC and disk diffusion values to R/SI: <https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt>. This **allows for machine reading these guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. This file used to process the EUCAST Clinical Breakpoints Excel file [can be found here](https://github.com/msberends/AMR/blob/master/data-raw/read_EUCAST.R).
* Support for LOINC and SNOMED codes
* Support for LOINC codes in the `antibiotics` data set. Use `ab_loinc()` to retrieve LOINC codes, or use a LOINC code for input in any `ab_*` function:
```r
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:
```r
mo_snomed("S. aureus")
#> [1] 115329001 3092008 113961008
mo_name(115329001)
#> [1] "Staphylococcus aureus"
mo_gramstain(115329001)
#> [1] "Gram-positive"
```
### Changes
* The `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.
* Bugfix for some WHONET microorganism codes that were not interpreted correctly when using `as.rsi()`
* Improvements for the algorithm used by `as.mo()` (and consequently all `mo_*` functions, that use `as.mo()` internally):
* Support for missing spaces, e.g. in `as.mo("Methicillin-resistant S.aureus")`
* Better support for determination of *Salmonella* biovars
* Speed improvements, especially for the *G. species* format (G for genus), like *E. coli* and *K pneumoniae*
* Support for more common codes used in laboratory information systems
* Input values for `as.disk()` limited to a maximum of 50 millimeters
2 years ago
* Added a lifecycle state to every function, following the lifecycle circle of the `tidyverse`
* For in `as.ab()`: support for drugs starting with "co-" like co-amoxiclav, co-trimoxazole, co-trimazine and co-trimazole (thanks to Peter Dutey)
* Changes to the `antibiotics` data set (thanks to Peter Dutey):
* Added more synonyms to colistin, imipenem and piperacillin/tazobactam
* Moved synonyms Rifinah and Rimactazid from rifampicin (`RIF`) to rifampicin/isoniazid (`RFI`). Please note that [the combination rifampicin/isoniazid has no DDDs defined](https://www.whocc.no/atc_ddd_index/?code=J04AM02&showdescription=no), so e.g. `ab_ddd("Rimactazid")` will now return `NA`.
* Moved synonyms Bactrimel and Cotrimazole from sulfamethoxazole (`SMX`) to trimethoprim/sulfamethoxazole (`SXT`)
### Other
* Add a `CITATION` file
* Full support for the upcoming R 4.0
* Removed unnecessary `AMR::` calls
3 years ago
# AMR 0.9.0
### Breaking
* Adopted Adeolu *et al.* (2016), [PMID 27620848](https:/pubmed.ncbi.nlm.nih.gov/27620848/) for the `microorganisms` data set, which means that the new order Enterobacterales now consists of a part of the existing family Enterobacteriaceae, but that this family has been split into other families as well (like *Morganellaceae* and *Yersiniaceae*). Although published in 2016, this information is not yet in the Catalogue of Life version of 2019. All MDRO determinations with `mdro()` will now use the Enterobacterales order for all guidelines before 2016 that were dependent on the Enterobacteriaceae family.
* If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:
```r
if (mo_family(somebugs) == "Enterobacteriaceae") ...
```
then please adjust this to:
```r
if (mo_order(somebugs) == "Enterobacterales") ...
```
### New
* 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.
```r
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).
* This is now the new default guideline for the `mdro()` function
* The new Verbose mode (`mdro(...., verbose = TRUE)`) returns an informative data set where the reason for MDRO determination is given for every isolate, and an list of the resistant antimicrobial agents
* Data set `antivirals`, containing all entries from the ATC J05 group with their DDDs for oral and parenteral treatment
### Changes
* Improvements to algorithm in `as.mo()`:
* 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](https://en.wikipedia.org/wiki/Levenshtein_distance):
```r
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%)
```
* Removed previously deprecated function `as.atc()` - this function was replaced by `ab_atc()`
* Renamed all `portion_*` functions to `proportion_*`. All `portion_*` functions are still available as deprecated functions, and will return a warning when used.
* When running `as.rsi()` over a data set, it will now print the guideline that will be used if it is not specified by the user
* Improvements for `eucast_rules()`:
* Fix where *Stenotrophomonas maltophilia* would always become ceftazidime R (following EUCAST v3.1)
* Fix where *Leuconostoc* and *Pediococcus* would not always become glycopeptides R
* non-EUCAST rules in `eucast_rules()` are now applied first and not as last anymore. This is to improve the dependency on certain antibiotics for the official EUCAST rules. Please see `?eucast_rules`.
* Fix for interpreting MIC values with `as.rsi()` where the input is `NA`
* Added "imi" and "imp" as allowed abbreviation for Imipenem (IPM)
* Fix for automatically determining columns with antibiotic results in `mdro()` and `eucast_rules()`
* Added ATC codes for ceftaroline, ceftobiprole and faropenem and fixed two typos in the `antibiotics` data set
* More robust way of determining valid MIC values
* Small changed to the `example_isolates` data set to better reflect reality
* Added more microorganisms codes from laboratory systems (esp. species of *Pseudescherichia* and *Rodentibacter*)
* Added Gram-stain to `mo_info()`
### Other
* Rewrote the complete documentation to markdown format, to be able to use the very latest version of the great [Roxygen2](https://roxygen2.r-lib.org/index.html), released in November 2019. This tremously improved the documentation quality, since the rewrite forced us to go over all texts again and make changes where needed.
* Change dependency on `clean` to `cleaner`, as this package was renamed accordingly upon CRAN request
* Added Dr. Sofia Ny as contributor
3 years ago
# AMR 0.8.0
### Breaking
* Determination 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`:
```r
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`:
```r
# 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 generated
```
This 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`](https://github.com/msberends/clean) ([CRAN link](https://cran.r-project.org/package=clean)), 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`
### New
* 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:
```r
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:
```r
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:
```r
# --------------------------------------------------------------------
# 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 `tibble`s 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.
```r
# (run this on your own console, as this page does not support colour printing)
library(dplyr)
example_isolates %>%
select(mo:AMC) %>%
as_tibble()
```
### Changed
* Many algorithm improvements for `as.mo()` (of which some led to additions to the `microorganisms` data set). Many thanks to all contributors that helped improving the algorithms.
* Self-learning algorithm - the function now gains experience from previously determined microorganism IDs and learns from it (yielding 80-95% speed improvement for any guess after the first try)
* Big improvement for misspelled input
* These new trivial names known to the field are now understood: meningococcus, gonococcus, pneumococcus
* Updated to the latest taxonomic data (updated to August 2019, from the International Journal of Systematic and Evolutionary Microbiology
* Added support for Viridans Group Streptococci (VGS) and Milleri Group Streptococci (MGS)
* Added support for *Blastocystis*
* Added support for 5,000 new fungi
* Added support for unknown yeasts and fungi
* Changed most microorganism IDs to improve readability. For example, the old code `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 æ (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.
* More intelligent guessing for `as.ab()`, including bidirectional language support
* Added support for the German national guideline (3MRGN/4MRGN) in the `mdro()` function, to determine multi-drug resistant organisms
* Function `eucast_rules()`:
* Fixed a bug for *Yersinia pseudotuberculosis*
* Added more informative errors and warnings
* Printed info now distinguishes between added and changes values
* Using Verbose mode (i.e. `eucast_rules(..., verbose = TRUE)`) returns more informative and readable output
* Using factors as input now adds missing factors levels when the function changes antibiotic results
* Improved the internal auto-guessing function for determining antimicrobials in your data set (`AMR:::get_column_abx()`)
* Removed class `atc` - using `as.atc()` is now deprecated in favour of `ab_atc()` and this will return a character, not the `atc` class anymore
* Removed deprecated functions `abname()`, `ab_official()`, `atc_name()`, `atc_official()`, `atc_property()`, `atc_tradenames()`, `atc_trivial_nl()`
* Fix and speed improvement for `mo_shortname()`
* Fix for using `mo_*` functions where the coercion uncertainties and failures would not be available through `mo_uncertainties()` and `mo_failures()` anymore
* Deprecated the `country` argument of `mdro()` in favour of the already existing `guideline` argument to support multiple guidelines within one country
* The `name` of `RIF` is now Rifampicin instead of Rifampin
* The `antibiotics` data set is now sorted by name and all cephalosporins now have their generation between brackets
* Speed improvement for `guess_ab_col()` which is now 30 times faster for antibiotic abbreviations
* Improved `filter_ab_class()` to be more reliable and to support 5th generation cephalosporins
* Function `availability()` now uses `portion_R()` instead of `portion_IR()`, to comply with EUCAST insights
* Functions `age()` and `age_groups()` now have a `na.rm` argument to remove empty values
* Renamed function `p.symbol()` to `p_symbol()` (the former is now deprecated and will be removed in a future version)
* Using negative values for `x` in `age_groups()` will now introduce `NA`s and not return an error anymore
* Fix for determining the system's language
* Fix for `key_antibiotics()` on foreign systems
* Added 80 new LIS codes for microorganisms
* Relabeled the factor levels of `mdr_tb()`
* Added more MIC factor levels (`as.mic()`)
#### Other
* Added Prof. Dr. Casper Albers as doctoral advisor and added Dr. Judith Fonville, Eric Hazenberg, Dr. Bart Meijer, Dr. Dennis Souverein and Annick Lenglet as contributors
* Cleaned the coding style of every single syntax line in this package with the help of the `lintr` package
# AMR 0.7.1
#### New
* Function `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:
```r
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 228
```
* Support for all scientifically published pathotypes of *E. coli* to date (that we could find). Supported are:
* AIEC (Adherent-Invasive *E. coli*)
* ATEC (Atypical Entero-pathogenic *E. coli*)
* DAEC (Diffusely Adhering *E. coli*)
* EAEC (Entero-Aggresive *E. coli*)
* EHEC (Entero-Haemorrhagic *E. coli*)
* EIEC (Entero-Invasive *E. coli*)
* EPEC (Entero-Pathogenic *E. coli*)
* ETEC (Entero-Toxigenic *E. coli*)
* NMEC (Neonatal Meningitis‚Äźcausing *E. coli*)
* STEC (Shiga-toxin producing *E. coli*)
* UPEC (Uropathogenic *E. coli*)
All these lead to the microbial ID of *E. coli*:
```r
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
#### Changed
* Column names of output `count_df()` and `portion_df()` are now lowercase
* Fixed bug in translation of microorganism names
* Fixed bug in determining taxonomic kingdoms
* Algorithm improvements for `as.ab()` and `as.mo()` to understand even more severely misspelled input
* Function `as.ab()` now allows spaces for coercing antibiotics names
* Added `ggplot2` methods for automatically determining the scale type of classes `mo` and `ab`
* Added names of object in the header in frequency tables, even when using pipes
* Prevented `"bacteria"` from getting coerced by `as.ab()` because Bacterial is a brand name of trimethoprim (TMP)
* Fixed a bug where setting an antibiotic would not work for `eucast_rules()` and `mdro()`
* Fixed a EUCAST rule for Staphylococci, where amikacin resistance would not be inferred from tobramycin
* Removed `latest_annual_release` from the `catalogue_of_life_version()` function
* Removed antibiotic code `PVM1` from the `antibiotics` data set as this was a duplicate of `PME`
* Fixed bug where not all old taxonomic names would be printed, when using a vector as input for `as.mo()`
* Manually added *Trichomonas vaginalis* from the kingdom of Protozoa, which is missing from the Catalogue of Life
* Small improvements to `plot()` and `barplot()` for MIC and RSI classes
* Allow Catalogue of Life IDs to be coerced by `as.mo()`
#### Other