diff --git a/DESCRIPTION b/DESCRIPTION index ce77b10c..fe6ffe88 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: AMR -Version: 1.8.2.9047 -Date: 2022-11-12 +Version: 1.8.2.9049 +Date: 2022-11-13 Title: Antimicrobial Resistance Data Analysis Description: Functions to simplify and standardise antimicrobial resistance (AMR) data analysis and to work with microbial and antimicrobial properties by diff --git a/NAMESPACE b/NAMESPACE index 6c1cffbb..439e2885 100755 --- a/NAMESPACE +++ b/NAMESPACE @@ -18,19 +18,23 @@ S3method("==",mic) S3method(">",mic) S3method(">=",mic) S3method("[",ab) +S3method("[",av) S3method("[",disk) S3method("[",mic) S3method("[",mo) S3method("[<-",ab) +S3method("[<-",av) S3method("[<-",disk) S3method("[<-",mic) S3method("[<-",mo) S3method("[<-",rsi) S3method("[[",ab) +S3method("[[",av) S3method("[[",disk) S3method("[[",mic) S3method("[[",mo) S3method("[[<-",ab) +S3method("[[<-",av) S3method("[[<-",disk) S3method("[[<-",mic) S3method("[[<-",mo) @@ -48,6 +52,7 @@ S3method(any,ab_selector) S3method(any,ab_selector_any_all) S3method(any,mic) S3method(as.data.frame,ab) +S3method(as.data.frame,av) S3method(as.data.frame,mo) S3method(as.double,mic) S3method(as.list,custom_eucast_rules) @@ -67,6 +72,7 @@ S3method(barplot,mic) S3method(barplot,rsi) S3method(c,ab) S3method(c,ab_selector) +S3method(c,av) S3method(c,custom_eucast_rules) S3method(c,custom_mdro_guideline) S3method(c,disk) @@ -113,6 +119,7 @@ S3method(plot,mic) S3method(plot,resistance_predict) S3method(plot,rsi) S3method(print,ab) +S3method(print,av) S3method(print,bug_drug_combinations) S3method(print,custom_eucast_rules) S3method(print,custom_mdro_guideline) @@ -127,6 +134,7 @@ S3method(prod,mic) S3method(quantile,mic) S3method(range,mic) S3method(rep,ab) +S3method(rep,av) S3method(rep,disk) S3method(rep,mic) S3method(rep,mo) @@ -153,6 +161,7 @@ S3method(tanpi,mic) S3method(trigamma,mic) S3method(trunc,mic) S3method(unique,ab) +S3method(unique,av) S3method(unique,disk) S3method(unique,mic) S3method(unique,mo) @@ -195,6 +204,7 @@ export(antifungals) export(antimicrobials_equal) export(antimycobacterials) export(as.ab) +export(as.av) export(as.disk) export(as.mic) export(as.mo) @@ -203,6 +213,19 @@ export(atc_online_ddd) export(atc_online_ddd_units) export(atc_online_groups) export(atc_online_property) +export(av_atc) +export(av_cid) +export(av_ddd) +export(av_ddd_units) +export(av_from_text) +export(av_group) +export(av_info) +export(av_loinc) +export(av_name) +export(av_property) +export(av_synonyms) +export(av_tradenames) +export(av_url) export(availability) export(betalactams) export(brmo) @@ -246,6 +269,7 @@ export(glycopeptides) export(guess_ab_col) export(inner_join_microorganisms) export(is.ab) +export(is.av) export(is.disk) export(is.mic) export(is.mo) diff --git a/NEWS.md b/NEWS.md index b1b47eb0..703e8581 100755 --- a/NEWS.md +++ b/NEWS.md @@ -1,4 +1,4 @@ -# AMR 1.8.2.9047 +# AMR 1.8.2.9049 This version will eventually become v2.0! We're happy to reach a new major milestone soon! @@ -8,36 +8,40 @@ This version will eventually become v2.0! We're happy to reach a new major miles * 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` no longer relies on the Catalogue of Life, but now primarily on the List of Prokaryotic names with Standing in Nomenclature (LPSN) and is supplemented with 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 1,000 taxonomic names from 2022 already. -* The `microorganisms.old` data set was removed, and all previously accepted names are now included in the `microorganisms` data set. A new column `status` 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 `microorganisms.old` data set was removed**, and all previously accepted names are now included in the `microorganisms` data set. A new column `status` 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 MO matching score algorithm (`mo_matching_score()`) now counts deletions and substitutions as 2 instead of 1, which impacts the outcome of `as.mo()` and any `mo_*()` function -* Argument `combine_IR` has been removed from this package (affecting functions `count_df()`, `proportion_df()`, and `rsi_df()` and some plotting functions), since it was replaced with `combine_SI` three years ago -* Removal of interpretation guidelines older than 10 years, the oldest now included guidelines of EUCAST and CLSI are from 2013 +* **Argument `combine_IR` has been removed** from this package (affecting functions `count_df()`, `proportion_df()`, and `rsi_df()` and some plotting functions), since it was replaced with `combine_SI` three years ago +* Interpretation **guidelines older than 10 years were removed**, the oldest now included guidelines of EUCAST and CLSI are from 2013 +* Using `units` in `ab_ddd(..., units = "...")` had been deprecated and is now not supported anymore. Use `ab_ddd_units()` instead. ### New -* EUCAST 2022 and CLSI 2022 guidelines have been added for `as.rsi()`. EUCAST 2022 is now the new default guideline for all MIC and disks diffusion interpretations. +* **EUCAST 2022 and CLSI 2022 guidelines** have been added for `as.rsi()`. EUCAST 2022 is now the new default guideline for all MIC and disks diffusion interpretations. * Support for the following languages: Chinese, Greek, Japanese, Polish, Turkish and Ukrainian. We are very grateful for the valuable input by our colleagues from other countries. The `AMR` package is now available in 16 languages. The automatic language determination will give a note at start-up on systems in supported languages. -* All new algorithm for `as.mo()` (and thus all `mo_*()` functions) while still following our original set-up as described in our paper (DOI 10.18637/jss.v104.i03). +* **All new algorithm for `as.mo()`** (and thus all `mo_*()` functions) while still following our original set-up as described in our recently submitted JSS paper (DOI [10.18637/jss.v104.i03](https://doi.org/10.18637/jss.v104.i03)). * A new argument `keep_synonyms` allows to *not* correct for updated taxonomy, in favour of the now deleted argument `allow_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) - -* New functions! +* **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](https://www.whocc.no/atc_ddd_index/?code=J05AJ&showdescription=no)) and now also contains antiviral identifiers and LOINC codes + * A new data type `av` (*antivirals*) has been added, which is functionally similar to `ab` for antibiotics + * Functions `as.av()`, `av_name()`, `av_atc()`, `av_synonyms()`, `av_from_text()` have all been added as siblings to their `ab_*()` equivalents +* **Other new functions!** * Function `rsi_confidence_interval()` to add confidence intervals in AMR calculation. This is also included in `rsi_df()` and `proportion_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 `rsi_interpretation_history()` to view the history of previous runs of `as.rsi()`. This returns a 'logbook' with the selected guideline, reference table and specific interpretation of each row in a data set on which `as.rsi()` was run. * Function `mo_current()` to get the currently valid taxonomic name of a microorganism * Function `add_custom_antimicrobials()` to add custom antimicrobial codes and names to the `AMR` package * New and updated entries for the `antibiotics` data set - * The following 20 antibiotics have been added (also includes the [new J01RA ATC group](https://www.whocc.no/atc_ddd_index/?code=J01RA&showdescription=no)): 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) + * The following **20 antibiotics have been added** (also includes the [new J01RA ATC group](https://www.whocc.no/atc_ddd_index/?code=J01RA&showdescription=no)): 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 the `ab_*()` functions. * Support for antimicrobial interpretation of anaerobic bacteria, by adding a 'placeholder' code `B_ANAER` to the `microorganisms` data set and add the breakpoints of anaerobics to the `rsi_interpretation` data set, which is used by `as.rsi()` when interpreting MIC and disk diffusion values * Support for `data.frame`-enhancing R packages, more specifically: `data.table::data.table`, `janitor::tabyl`, `tibble::tibble`, and `tsibble::tsibble`. AMR package functions that have a data set as output (such as `rsi_df()` and `bug_drug_combinations()`), will now return the same data type as the input. -* All data sets in this package are now exported as `tibble`, instead of base R `data.frame`s. Older R versions are still supported. -* 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](https://msberends.github.io/AMR/articles/datasets.html). +* All data sets in this package are **now exported as `tibble`**, instead of base R `data.frame`s. Older R versions are still supported. +* 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](https://msberends.github.io/AMR/articles/datasets.html). * Support for using antibiotic selectors in scoped `dplyr` verbs (with or without `vars()`), such as in: `... %>% summarise_at(aminoglycosides(), resistance)`, see `resistance()` ### Changed @@ -173,1314 +177,6 @@ A major update will be released by the end of 2022 or early 2023 to include the * This package is now being maintained by two epidemiologists and a data scientist from two different non-profit healthcare organisations. -# AMR 1.7.1 +# AMR older versions -### Breaking change -* All 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: - ```r - # 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") - ``` - -### New -* Support for CLSI 2020 guideline for interpreting MICs and disk diffusion values (using `as.rsi()`) -* Function `custom_eucast_rules()` that brings support for custom AMR rules in `eucast_rules()` -* Function `italicise_taxonomy()` to make taxonomic names within a string italic, with support for markdown and ANSI -* Support for all four methods to determine first isolates as summarised by Hindler *et al.* (doi: [10.1086/511864](https://doi.org/10.1086/511864)): isolate-based, patient-based, episode-based and phenotype-based. The last method is now the default. - * The `first_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). - * Since fungal isolates can also be selected, the functions `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). - * Using `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()` - * The `first_isolate()` function can now take a vector of values for `col_keyantibiotics` and can have an episode length of `Inf` - * Since the phenotype-based method is the new default, `filter_first_isolate()` renders the `filter_first_weighted_isolate()` function redundant. For this reason, `filter_first_weighted_isolate()` is now deprecated. - * The documentation of the `first_isolate()` and `key_antimicrobials()` functions has been completely rewritten. -* Function `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. -* A `ggplot()` method for `resistance_predict()` - - -### Changed -* `bug_drug_combinations()` now supports grouping using the `dplyr` package -* Custom MDRO guidelines (`mdro()`, `custom_mdro_guideline()`): - * Custom MDRO guidelines can now be combined with other custom MDRO guidelines using `c()` - * Fix for applying the rules; in previous versions, rows were interpreted according to the last matched rule. Now, rows are interpreted according to the first matched rule -* Fix for `age_groups()` for persons aged zero -* The `example_isolates` data set now contains some (fictitious) zero-year old patients -* Fix for minor translation errors -* Printing of microbial codes in a `data.frame` or `tibble` now gives a warning if the data contains old microbial codes (from a previous AMR package version) -* Extended the `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: - ```r - 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 -* Fixed an installation error on R-3.0 -* Added `info` argument to `as.mo()` to turn on/off the progress bar -* Fixed a bug where `col_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 error -* Fix for transforming numeric values to RSI (`as.rsi()`) when the `vctrs` package is loaded (i.e., when using tidyverse) -* Colour fix for using `barplot()` on an RSI class -* Added 25 common system codes for bacteria to the `microorganisms.codes` data set -* Added 16 common system codes for antimicrobial agents to the `antibiotics` data set -* Fix for using `skimr::skim()` on classes `mo`, `mic` and `disk` when using the just released `dplyr` v1.0.6 -* Updated `skimr::skim()` usage for MIC values to also include 25th and 75th percentiles -* Fix for plotting missing MIC/disk diffusion values -* Updated join functions to always use `dplyr` join functions if the `dplyr` package is installed - now also preserving grouped variables -* Antibiotic class selectors (such as `cephalosporins()`) now maintain the column order from the original data -* Fix for selecting columns using `fluoroquinolones()` -* `age()` now vectorises over both `x` and `reference` - -### Other -* As requested by CRAN administrators: decreased package size by 3 MB in costs of a slower loading time of the package -* All unit tests are now processed by the `tinytest` 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. - - -# 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 `` (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, ward, 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 `` and `` -* 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 - #> [1] 128 0.5 2 0.125 64 0.25 >=256 8 16 4 - x[x > 4] - #> Class - #> [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 [LPSN](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`, ``, and ``: - * 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 ``, see `as.rsi()`) are empty - -### 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 - -### 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, ward) %>% - 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. - -### 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() - ``` -* 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 `` -* 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 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: -* 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 ``, ``, `` and `` 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 - #> [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 ``, ``, ``, `` and ``. When using `tibble`s containing antimicrobial columns (class ``), "S" will print in green, "I" will print in yellow and "R" will print in red. Microbial IDs (class ``) 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 ``, ``, ``, `` and `` -* Added argument `excess` to the `kurtosis()` function (defaults to `FALSE`), to return the *excess kurtosis*, defined as the kurtosis minus three. - -### 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 `` and `` -* Fixed a bug in `bug_drug_combinations()` for when only one antibiotic was in the input data -* Changed the summary for class ``, 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`) - -### 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 ``, not `` 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. - -# 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` - -# AMR 1.0.1 - -### Changed -* 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) - -# 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: . 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/main/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 -* 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 - -# 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 - -# 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 - # S or I X X - - - # S or I R X X X X - # R R - X - X - # R - - - - - # S or I X X - - - # R - - - - - # - - - - - # -------------------------------------------------------------------- - ``` - - 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 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-causing *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 -* Fixed a note thrown by CRAN tests - -# AMR 0.7.0 - -#### New -* Support for translation of disk diffusion and MIC values to RSI values (i.e. antimicrobial interpretations). Supported guidelines are EUCAST (2011 to 2019) and CLSI (2011 to 2019). Use `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. -* Function `mo_name()` as alias of `mo_fullname()` -* Added guidelines of the WHO to determine multi-drug resistance (MDR) for TB (`mdr_tb()`) and added a new vignette about MDR. Read this tutorial [here on our website](https://msberends.gitlab.io/AMR/articles/MDR.html). - -#### Changed -* Fixed a critical bug in `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. -* Fixed a bug in `eucast_rules()` where antibiotics from WHONET software would not be recognised -* Completely reworked the `antibiotics` data set: - * All entries now have 3 different identifiers: - * Column `ab` contains a human readable EARS-Net code, used by ECDC and WHO/WHONET - this is the primary identifier used in this package - * Column `atc` contains the ATC code, used by WHO/WHOCC - * Column `cid` contains the CID code (Compound ID), used by PubChem - * Based on the Compound ID, almost 5,000 official brand names have been added from many different countries - * All references to antibiotics in our package now use EARS-Net codes, like `AMX` for amoxicillin - * Functions `atc_certe`, `ab_umcg` and `atc_trivial_nl` have been removed - * All `atc_*` functions are superseded by `ab_*` functions - * All output will be translated by using an included translation file which [can be viewed here](https://github.com/msberends/AMR/blob/main/data-raw/translations.tsv) -* Improvements to plotting AMR results with `ggplot_rsi()`: - * New argument `colours` to set the bar colours - * New arguments `title`, `subtitle`, `caption`, `x.title` and `y.title` to set titles and axis descriptions -* Improved intelligence of looking up antibiotic columns in a data set using `guess_ab_col()` -* Added ~5,000 more old taxonomic names to the `microorganisms.old` data set, which leads to better results finding when using the `as.mo()` function -* This package now honours the new EUCAST insight (2019) that S and I are but classified as susceptible, where I is defined as 'increased exposure' and not 'intermediate' anymore. For functions like `portion_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. -* The `age()` function gained a new argument `exact` to determine ages with decimals -* Removed deprecated functions `guess_mo()`, `guess_atc()`, `EUCAST_rules()`, `interpretive_reading()`, `rsi()` -* Frequency tables (`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: - ```r - septic_patients %>% - freq(age) %>% - boxplot() - # grouped boxplots: - septic_patients %>% - group_by(ward) %>% - freq(age) %>% - boxplot() - ``` -* Removed all hardcoded EUCAST rules and replaced them with a new reference file which [can be viewed here](https://github.com/msberends/AMR/blob/main/data-raw/eucast_rules.tsv) -* Added ceftazidim intrinsic resistance to *Streptococci* -* Changed default settings for `age_groups()`, to let groups of fives and tens end with 100+ instead of 120+ -* Fix for `freq()` for when all values are `NA` -* Fix for `first_isolate()` for when dates are missing -* Improved speed of `guess_ab_col()` -* Function `as.mo()` now gently interprets any number of whitespace characters (like tabs) as one space -* Function `as.mo()` now returns `UNKNOWN` for `"con"` (WHONET ID of 'contamination') and returns `NA` for `"xxx"`(WHONET ID of 'no growth') -* Small algorithm fix for `as.mo()` -* Removed viruses from data set `microorganisms.codes` and cleaned it up -* Fix for `mo_shortname()` where species would not be determined correctly - -#### Other -* Support for R 3.6.0 and later by providing support for [staged install](https://developer.r-project.org/Blog/public/2019/02/14/staged-install/index.html) - -# AMR 0.6.1 - -#### Changed -* Fixed a critical bug when using `eucast_rules()` with `verbose = TRUE` -* Coercion of microbial IDs are now written to the package namespace instead of the user's home folder, to comply with the CRAN policy - -# AMR 0.6.0 - -**New website!** - -We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.gitlab.io/AMR/) (built with the great [`pkgdown`](https://pkgdown.r-lib.org/)) - -* Contains the complete manual of this package and all of its functions with an explanation of their arguments -* Contains a comprehensive tutorial about how to conduct AMR data analysis, import data from WHONET or SPSS and many more. - -#### New -* **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](https://whonet.org/) and [EARS-Net](https://www.ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net) (European Antimicrobial Resistance Surveillance Network): - * Exported files from WHONET can be read and used in this package. For functions like `first_isolate()` and `eucast_rules()`, all arguments will be filled in automatically. - * This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the `antibiotics` data set now contains a column `ears_net`. - * The function `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: - ```r - 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: - ```r - 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 R - ``` -* All `ab_*` functions are deprecated and replaced by `atc_*` functions: - ```r - 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`](https://dplyr.tidyverse.org) 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()`: - ```r - 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.: - ```r - septic_patients %>% filter_first_isolate(...) - # or - filter_first_isolate(septic_patients, ...) - ``` - is equal to: - ```r - 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. - -#### Changed -* Function `eucast_rules()`: - * Updated EUCAST Clinical breakpoints to [version 9.0 of 1 January 2019](https://www.eucast.org/clinical_breakpoints/), the data set `septic_patients` now reflects these changes - * Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately - * Emphasised in manual that penicillin is meant as benzylpenicillin (ATC [J01CE01](https://www.whocc.no/atc_ddd_index/?code=J01CE01)) - * New info is returned when running this function, stating exactly what has been changed or added. Use `eucast_rules(..., verbose = TRUE)` to get a data set with all changed per bug and drug combination. -* Removed data sets `microorganisms.oldDT`, `microorganisms.prevDT`, `microorganisms.unprevDT` and `microorganismsDT` since they were no longer needed and only contained info already available in the `microorganisms` data set -* Added 65 antibiotics to the `antibiotics` data set, from the [Pharmaceuticals Community Register](https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm) of the European Commission -* Removed columns `atc_group1_nl` and `atc_group2_nl` from the `antibiotics` data set -* Functions `atc_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. -* Function `guess_mo()` is now deprecated in favour of `as.mo()` and will be removed in future versions -* Function `guess_atc()` is now deprecated in favour of `as.atc()` and will be removed in future versions -* Improvements for `as.mo()`: - * Now handles incorrect spelling, like `i` instead of `y` and `f` instead of `ph`: - ```r - # 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. - ```r - # 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 -* Function `first_isolate()`: - * Fixed a bug where distances between dates would not be calculated right - in the `septic_patients` data set this yielded a difference of 0.15% more isolates - * Will now use a column named like "patid" for the patient ID (argument `col_patientid`), when this argument was left blank - * Will now use a column named like "key(...)ab" or "key(...)antibiotics" for the key antibiotics (argument `col_keyantibiotics()`), when this argument was left blank - * Removed argument `output_logical`, the function will now always return a logical value - * Renamed argument `filter_specimen` to `specimen_group`, although using `filter_specimen` will still work -* A note to the manual pages of the `portion` 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) -* Merged data sets `microorganisms.certe` and `microorganisms.umcg` into `microorganisms.codes` -* Function `mo_taxonomy()` now contains the kingdom too -* Reduce false positives for `is.rsi.eligible()` using the new `threshold` argument -* New colours for `scale_rsi_colours()` -* Summaries of class `mo` will now return the top 3 and the unique count, e.g. using `summary(mo)` -* Small text updates to summaries of class `rsi` and `mic` -* Function `as.rsi()`: - * Now gives a warning when inputting MIC values - * Now accepts high and low resistance: `"HIGH S"` will return `S` -* Frequency tables (`freq()` function): - * Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes: - ```r - # 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 -* Function `scale_y_percent()` now contains the `limits` argument -* Automatic argument filling for `mdro()`, `key_antibiotics()` and `eucast_rules()` -* Updated examples for resistance prediction (`resistance_predict()` function) -* Fix for `as.mic()` to support more values ending in (several) zeroes -* if using different lengths of pattern and x in `%like%`, it will now return the call - -#### Other -* Updated licence text to emphasise GPL 2.0 and that this is an R package. - -# AMR 0.5.0 - -#### New -* Repository moved to GitLab -* Function `count_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_all` -* Function `get_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. -* Data sets `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`. -* Function `read.4D` to read from the 4D database of the MMB department of the UMCG -* Functions `mo_authors` and `mo_year` to get specific values about the scientific reference of a taxonomic entry - -#### Changed -* Functions `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: - * Now also applies rules from the EUCAST 'Breakpoint tables for bacteria', version 8.1, 2018, https://www.eucast.org/clinical_breakpoints/ (see Source of the function) - * New argument `rules` to specify which rules should be applied (expert rules, breakpoints, others or all) - * New argument `verbose` which can be set to `TRUE` to get very specific messages about which columns and rows were affected - * Better error handling when rules cannot be applied (i.e. new values could not be inserted) - * The number of affected values will now only be measured once per row/column combination - * Data set `septic_patients` now reflects these changes - * Added argument `pipe` for piperacillin (J01CA12), also to the `mdro` function - * Small fixes to EUCAST clinical breakpoint rules -* Added 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 - ```r - 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: - ```r - septic_patients %>% - group_by(ward) %>% - freq(gender) - ``` - * Support for (un)selecting columns: - ```r - septic_patients %>% - freq(ward) %>% - select(-count, -cum_count) # only get item, percent, cum_percent - ``` - * Check 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 epidermidis* -* Fix 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) - -#### Other -* New dependency on package `crayon`, to support formatted text in the console -* Dependency `tidyr` is now mandatory (went to `Import` field) since `portion_df` and `count_df` rely on it -* Updated vignettes to comply with README - - -# AMR 0.4.0 - -#### New -* The 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`: - * Taxonomic names: `mo_phylum`, `mo_class`, `mo_order`, `mo_family`, `mo_genus`, `mo_species`, `mo_subspecies` - * Semantic names: `mo_fullname`, `mo_shortname` - * Microbial properties: `mo_type`, `mo_gramstain` - * Author and year: `mo_ref` - - They also come with support for German, Dutch, French, Italian, Spanish and Portuguese: - ```r - 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: - ```r - 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 - * Extra function `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 variables -* Function `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: - ```r - as.mo("E. coli") - # [1] B_ESCHR_COL - as.mo("MRSA") - # [1] B_STPHY_AUR - as.mo("S group A") - # [1] B_STRPTC_GRA - ``` - And 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: - ```r - 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 100 - ``` -* Added 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: - * Column names inputs of `EUCAST_rules`, `first_isolate` and `key_antibiotics` - * Column names of datasets `microorganisms` and `septic_patients` - * All old syntaxes will still work with this version, but will throw warnings -* Function `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` - -#### Changed -* 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.: - ```r - 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. - ```r - 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` - ```r - my_matrix = with(septic_patients, matrix(c(age, gender), ncol = 2)) - freq(my_matrix) - ``` - For lists, subsetting is possible: - ```r - my_list = list(age = septic_patients$age, gender = septic_patients$gender) - my_list %>% freq(age) - my_list %>% freq(gender) - ``` - -#### Other -* More unit tests to ensure better integrity of functions - -# AMR 0.3.0 - -#### New -* **BREAKING**: `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. - * New function `portion_df` to get all portions of S, I and R of a data set with antibiotic columns, with support for grouped variables -* **BREAKING**: the methodology for determining first weighted isolates was changed. The antibiotics that are compared between isolates (call *key antibiotics*) to include more first isolates (afterwards called first *weighted* isolates) are now as follows: - * Universal: amoxicillin, amoxicillin/clavlanic acid, cefuroxime, piperacillin/tazobactam, ciprofloxacin, trimethoprim/sulfamethoxazole - * Gram-positive: vancomycin, teicoplanin, tetracycline, erythromycin, oxacillin, rifampicin - * Gram-negative: gentamicin, tobramycin, colistin, cefotaxime, ceftazidime, meropenem -* Support for `ggplot2` - * New functions `geom_rsi`, `facet_rsi`, `scale_y_percent`, `scale_rsi_colours` and `theme_rsi` - * New wrapper function `ggplot_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 - * Support for grouped variables, see `?ggplot_rsi` -* Determining bacterial ID: - * New functions `as.bactid` and `is.bactid` to transform/ look up microbial ID's. - * The existing function `guess_bactid` is now an alias of `as.bactid` - * New Becker classification for *Staphylococcus* to categorise them into Coagulase Negative *Staphylococci* (CoNS) and Coagulase Positve *Staphylococci* (CoPS) - * New Lancefield classification for *Streptococcus* to categorise them into Lancefield groups -* For convience, new descriptive statistical functions `kurtosis` and `skewness` that are lacking in base R - they are generic functions and have support for vectors, data.frames and matrices -* Function `g.test` to perform the X2 distributed [*G*-test](https://en.wikipedia.org/wiki/G-test), which use is the same as `chisq.test` -* ~~Function `ratio` to transform a vector of values to a preset ratio~~ - * ~~For example: `ratio(c(10, 500, 10), ratio = "1:2:1")` would return `130, 260, 130`~~ -* Support for Addins menu in RStudio to quickly insert `%in%` or `%like%` (and give them keyboard shortcuts), or to view the datasets that come with this package -* Function `p.symbol` to transform p values to their related symbols: `0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1` -* Functions `clipboard_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) -* New for frequency tables (function `freq`): - * A vignette to explain its usage - * Support for `rsi` (antimicrobial resistance) to use as input - * Support for `table` to use as input: `freq(table(x, y))` - * Support for existing functions `hist` and `plot` to use a frequency table as input: `hist(freq(df$age))` - * Support for `as.vector`, `as.data.frame`, `as_tibble` and `format` - * Support for quasiquotation: `freq(mydata, mycolumn)` is the same as `mydata %>% freq(mycolumn)` - * Function `top_freq` function to return the top/below *n* items as vector - * Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR) - * Possibility to globally set the default for the amount of items to print, with `options(max.print.freq = n)` where *n* is your preset value - -#### Changed -* Improvements for forecasting with `resistance_predict` and added more examples -* More antibiotics added as arguments for EUCAST rules -* Updated version of the `septic_patients` data set to better reflect the reality -* Pretty printing for tibbles removed as it is not really the scope of this package -* Printing of `mic` and `rsi` classes now returns all values - use `freq` to check distributions -* Improved speed of key antibiotics comparison for determining first isolates -* Column names for the `key_antibiotics` function are now generic: 6 for broadspectrum ABs, 6 for Gram-positive specific and 6 for Gram-negative specific ABs -* Speed improvement for the `abname` function -* `%like%` now supports multiple patterns -* Frequency tables are now actual `data.frame`s with altered console printing to make it look like a frequency table. Because of this, the argument `toConsole` is not longer needed. -* Fix for `freq` where the class of an item would be lost -* Small translational improvements to the `septic_patients` dataset and the column `bactid` now has the new class `"bactid"` -* Small improvements to the `microorganisms` dataset (especially for *Salmonella*) and the column `bactid` now has the new class `"bactid"` -* Combined MIC/RSI values will now be coerced by the `rsi` and `mic` functions: - * `as.rsi("<=0.002; S")` will return `S` - * `as.mic("<=0.002; S")` will return `<=0.002` -* Now possible to coerce MIC values with a space between operator and value, i.e. `as.mic("<= 0.002")` now works -* Classes `rsi` and `mic` do not add the attribute `package.version` anymore -* Added `"groups"` option for `atc_property(..., property)`. It will return a vector of the ATC hierarchy as defined by the [WHO](https://www.whocc.no/atc/structure_and_principles/). The new function `atc_groups` is a convenient wrapper around this. -* Build-in host check for `atc_property` as it requires the host set by `url` to be responsive -* Improved `first_isolate` algorithm to exclude isolates where bacteria ID or genus is unavailable -* Fix for warning *hybrid evaluation forced for row_number* ([`924b62`](https://github.com/tidyverse/dplyr/commit/924b62)) from the `dplyr` package v0.7.5 and above -* Support for empty values and for 1 or 2 columns as input for `guess_bactid` (now called `as.bactid`) - * So `yourdata %>% select(genus, species) %>% as.bactid()` now also works -* Other small fixes - -#### Other -* Added integration tests (check if everything works as expected) for all releases of R 3.1 and higher - * Linux and macOS: https://travis-ci.org/msberends/AMR - * Windows: https://ci.appveyor.com/project/msberends/amr -* Added thesis advisors to DESCRIPTION file - -# AMR 0.2.0 - -#### New -* Full support for Windows, Linux and macOS -* Full support for old R versions, only R-3.0.0 (April 2013) or later is needed (needed packages may have other dependencies) -* Function `n_rsi` to count cases where antibiotic test results were available, to be used in conjunction with `dplyr::summarise`, see ?rsi -* Function `guess_bactid` to **determine the ID** of a microorganism based on genus/species or known abbreviations like MRSA -* Function `guess_atc` to **determine the ATC** of an antibiotic based on name, trade name, or known abbreviations -* Function `freq` to create **frequency tables**, with additional info in a header -* Function `MDRO` to **determine Multi Drug Resistant Organisms (MDRO)** with support for country-specific guidelines. - * Exceptional resistances defined by EUCAST are also supported instead of countries alone - * Functions `BRMO` and `MRGN` are wrappers for Dutch and German guidelines, respectively -* New algorithm to determine weighted isolates, can now be `"points"` or `"keyantibiotics"`, see `?first_isolate` -* New print format for `tibble`s and `data.table`s - -#### Changed -* Fixed `rsi` class for vectors that contain only invalid antimicrobial interpretations -* Renamed dataset `ablist` to `antibiotics` -* Renamed dataset `bactlist` to `microorganisms` -* Added common abbreviations and trade names to the `antibiotics` dataset -* Added more microorganisms to the `microorganisms` dataset -* Added analysis examples on help page of dataset `septic_patients` -* Added support for character vector in `join` functions -* Added warnings when a join results in more rows after than before the join -* Altered `%like%` to make it case insensitive -* For arguments of functions `first_isolate` and `EUCAST_rules` column names are now case-insensitive -* Functions `as.rsi` and `as.mic` now add the package name and version as attributes - -#### Other -* Expanded `README.md` with more examples -* Added [ORCID](https://orcid.org) of authors to DESCRIPTION file -* Added unit testing with the `testthat` package -* Added build tests for Linux and macOS using Travis CI (https://travis-ci.org/msberends/AMR) -* Added line coverage checking using CodeCov (https://codecov.io/gh/msberends/AMR/tree/main/R) - -# AMR 0.1.1 - -* `EUCAST_rules` applies for amoxicillin even if ampicillin is missing -* Edited column names to comply with GLIMS, the laboratory information system -* Added more valid MIC values -* Renamed 'Daily Defined Dose' to 'Defined Daily Dose' -* Added barplots for `rsi` and `mic` classes - -# AMR 0.1.0 - -* First submission to CRAN. +For the changelog of older versions, please see [our archive](https://github.com/msberends/AMR/blob/v1.8.0/NEWS.md). diff --git a/R/ab.R b/R/ab.R index 4ecf4c15..dd9438dc 100755 --- a/R/ab.R +++ b/R/ab.R @@ -82,8 +82,8 @@ #' #' # use ab_* functions to get a specific properties (see ?ab_property); #' # they use as.ab() internally: -#' ab_name("J01FA01") # "Erythromycin" -#' ab_name("eryt") # "Erythromycin" +#' ab_name("J01FA01") +#' ab_name("eryt") #' #' \donttest{ #' if (require("dplyr")) { @@ -650,3 +650,20 @@ generalise_antibiotic_name <- function(x) { x <- gsub("(/| AND | WITH | W/|[+]|[-])+", " ", x, perl = TRUE) x } + +get_translate_ab <- function(translate_ab) { + translate_ab <- as.character(translate_ab)[1L] + if (translate_ab %in% c("TRUE", "official")) { + return("name") + } else if (translate_ab %in% c(NA_character_, "FALSE")) { + return(FALSE) + } else { + translate_ab <- tolower(translate_ab) + stop_ifnot(translate_ab %in% colnames(AMR::antibiotics), + "invalid value for 'translate_ab', this must be a column name of the antibiotics data set\n", + "or TRUE (equals 'name') or FALSE to not translate at all.", + call = FALSE + ) + translate_ab + } +} diff --git a/R/ab_from_text.R b/R/ab_from_text.R index 6ed1ed8b..c4c950db 100644 --- a/R/ab_from_text.R +++ b/R/ab_from_text.R @@ -59,7 +59,7 @@ #' @examples #' # mind the bad spelling of amoxicillin in this line, #' # straight from a true health care record: -#' ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds") +#' ab_from_text("28/03/2020 regular amoxicilliin 500mg po tid") #' #' ab_from_text("500 mg amoxi po and 400mg cipro iv") #' ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "dose") diff --git a/R/ab_property.R b/R/ab_property.R index e2b77669..65133cbb 100644 --- a/R/ab_property.R +++ b/R/ab_property.R @@ -59,38 +59,35 @@ #' @inheritSection AMR Reference Data Publicly Available #' @examples #' # all properties: -#' ab_name("AMX") # "Amoxicillin" -#' ab_atc("AMX") # "J01CA04" (ATC code from the WHO) -#' ab_cid("AMX") # 33613 (Compound ID from PubChem) -#' ab_synonyms("AMX") # a list with brand names of amoxicillin -#' ab_tradenames("AMX") # same -#' ab_group("AMX") # "Beta-lactams/penicillins" -#' ab_atc_group1("AMX") # "Beta-lactam antibacterials, penicillins" -#' ab_atc_group2("AMX") # "Penicillins with extended spectrum" -#' ab_url("AMX") # link to the official WHO page +#' ab_name("AMX") +#' ab_atc("AMX") +#' ab_cid("AMX") +#' ab_synonyms("AMX") +#' ab_tradenames("AMX") +#' ab_group("AMX") +#' ab_atc_group1("AMX") +#' ab_atc_group2("AMX") +#' ab_url("AMX") #' #' # smart lowercase tranformation -#' ab_name(x = c("AMC", "PLB")) # "Amoxicillin/clavulanic acid" "Polymyxin B" -#' ab_name( -#' x = c("AMC", "PLB"), -#' tolower = TRUE -#' ) # "amoxicillin/clavulanic acid" "polymyxin B" +#' ab_name(x = c("AMC", "PLB")) +#' ab_name(x = c("AMC", "PLB"), tolower = TRUE) #' #' # defined daily doses (DDD) -#' ab_ddd("AMX", "oral") # 1.5 -#' ab_ddd_units("AMX", "oral") # "g" -#' ab_ddd("AMX", "iv") # 3 -#' ab_ddd_units("AMX", "iv") # "g" +#' ab_ddd("AMX", "oral") +#' ab_ddd_units("AMX", "oral") +#' ab_ddd("AMX", "iv") +#' ab_ddd_units("AMX", "iv") #' #' ab_info("AMX") # all properties as a list #' #' # all ab_* functions use as.ab() internally, so you can go from 'any' to 'any': -#' ab_atc("AMP") # ATC code of AMP (ampicillin) -#' ab_group("J01CA01") # Drug group of ampicillins ATC code -#' ab_loinc("ampicillin") # LOINC codes of ampicillin -#' ab_name("21066-6") # "Ampicillin" (using LOINC) -#' ab_name(6249) # "Ampicillin" (using CID) -#' ab_name("J01CA01") # "Ampicillin" (using ATC) +#' ab_atc("AMP") +#' ab_group("J01CA01") +#' ab_loinc("ampicillin") +#' ab_name("21066-6") +#' ab_name(6249) +#' ab_name("J01CA01") #' #' # spelling from different languages and dyslexia are no problem #' ab_atc("ceftriaxon") @@ -244,20 +241,7 @@ ab_ddd <- function(x, administration = "oral", ...) { meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1) x <- as.ab(x, ...) - ddd_prop <- administration - # old behaviour - units <- list(...)$units - if (!is.null(units) && isTRUE(units)) { - if (message_not_thrown_before("ab_ddd", entire_session = TRUE)) { - warning_( - "in `ab_ddd()`: using `ab_ddd(..., units = TRUE)` is deprecated, use `ab_ddd_units()` to retrieve units instead.", - "This warning will be shown once per session." - ) - } - ddd_prop <- paste0(ddd_prop, "_units") - } else { - ddd_prop <- paste0(ddd_prop, "_ddd") - } + ddd_prop <- paste0(administration, "_ddd") out <- ab_validate(x = x, property = ddd_prop) if (any(ab_name(x, language = NULL) %like% "/" & is.na(out))) { @@ -277,16 +261,17 @@ ab_ddd_units <- function(x, administration = "oral", ...) { meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1) x <- as.ab(x, ...) - if (any(ab_name(x, language = NULL) %like% "/")) { + ddd_prop <- paste0(administration, "_units") + out <- ab_validate(x = x, property = ddd_prop) + + if (any(ab_name(x, language = NULL) %like% "/" & is.na(out))) { warning_( - "in `ab_ddd_units()`: DDDs of combined products are available for different dose combinations and not (yet) part of the AMR package.", + "in `ab_ddd_units()`: DDDs of some combined products are available for different dose combinations and not (yet) part of the AMR package.", "Please refer to the WHOCC website:\n", "www.whocc.no/ddd/list_of_ddds_combined_products/" ) } - - ddd_prop <- paste0(administration, "_units") - ab_validate(x = x, property = ddd_prop) + out } #' @rdname ab_property diff --git a/R/amr.R b/R/amr.R index c5b61889..8bdb459c 100644 --- a/R/amr.R +++ b/R/amr.R @@ -36,7 +36,7 @@ #' #' This work was published in the Journal of Statistical Software (Volume 104(3); \doi{10.18637/jss.v104.i03}) and formed the basis of two PhD theses (\doi{10.33612/diss.177417131} and \doi{10.33612/diss.192486375}). #' -#' After installing this package, \R knows `r format_included_data_number(microorganisms)` distinct microbial species and all `r format_included_data_number(rbind(antibiotics[, "atc", drop = FALSE], antivirals[, "atc", drop = FALSE]))` antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. +#' After installing this package, \R knows `r format_included_data_number(microorganisms)` distinct microbial species and all `r format_included_data_number(rbind(antibiotics[, "name", drop = FALSE], antivirals[, "name", drop = FALSE]))` antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. #' #' This package is fully independent of any other \R package and works on Windows, macOS and Linux with all versions of \R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This \R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. #' diff --git a/R/av.R b/R/av.R new file mode 100755 index 00000000..0ea0b2ff --- /dev/null +++ b/R/av.R @@ -0,0 +1,613 @@ +# ==================================================================== # +# TITLE # +# AMR: An R Package for Working with Antimicrobial Resistance Data # +# # +# SOURCE # +# https://github.com/msberends/AMR # +# # +# CITE AS # +# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # +# (2022). AMR: An R Package for Working with Antimicrobial Resistance # +# Data. Journal of Statistical Software, 104(3), 1-31. # +# doi:10.18637/jss.v104.i03 # +# # +# Developed at the University of Groningen, the Netherlands, in # +# collaboration with non-profit organisations Certe Medical # +# Diagnostics & Advice, and University Medical Center Groningen. # +# # +# This R package is free software; you can freely use and distribute # +# it for both personal and commercial purposes under the terms of the # +# GNU General Public License version 2.0 (GNU GPL-2), as published by # +# the Free Software Foundation. # +# We created this package for both routine data analysis and academic # +# research and it was publicly released in the hope that it will be # +# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # +# # +# Visit our website for the full manual and a complete tutorial about # +# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # +# ==================================================================== # + +#' Transform Input to an Antiviral Agent ID +#' +#' Use this function to determine the antiviral agent code of one or more antiviral agents. The data set [antivirals] will be searched for abbreviations, official names and synonyms (brand names). +#' @param x a [character] vector to determine to antiviral agent ID +#' @param flag_multiple_results a [logical] to indicate whether a note should be printed to the console that probably more than one antiviral agent code or name can be retrieved from a single input value. +#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode +#' @param ... arguments passed on to internal functions +#' @rdname as.av +#' @inheritSection WHOCC WHOCC +#' @details All entries in the [antivirals] data set have three different identifiers: a human readable EARS-Net code (column `ab`, used by ECDC and WHONET), an ATC code (column `atc`, used by WHO), and a CID code (column `cid`, Compound ID, used by PubChem). The data set contains more than 5,000 official brand names from many different countries, as found in PubChem. Not that some drugs contain multiple ATC codes. +#' +#' All these properties will be searched for the user input. The [as.av()] can correct for different forms of misspelling: +#' +#' * Wrong spelling of drug names (such as "acyclovir"), which corrects for most audible similarities such as f/ph, x/ks, c/z/s, t/th, etc. +#' * Too few or too many vowels or consonants +#' * Switching two characters (such as "aycclovir", often the case in clinical data, when doctors typed too fast) +#' * Digitalised paper records, leaving artefacts like 0/o/O (zero and O's), B/8, n/r, etc. +#' +#' Use the [`av_*`][av_property()] functions to get properties based on the returned antiviral agent ID, see *Examples*. +#' +#' Note: the [as.av()] and [`av_*`][av_property()] functions may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems. +#' @section Source: +#' World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/} +#' +#' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm} +#' @aliases av +#' @return A [character] [vector] with additional class [`ab`] +#' @seealso +#' * [antivirals] for the [data.frame] that is being used to determine ATCs +#' * [av_from_text()] for a function to retrieve antimicrobial drugs from clinical text (from health care records) +#' @inheritSection AMR Reference Data Publicly Available +#' @export +#' @examples +#' # these examples all return "ACI", the ID of aciclovir: +#' as.av("J05AB01") +#' as.av("J 05 AB 01") +#' as.av("Aciclovir") +#' as.av("aciclo") +#' as.av(" aciclo 123") +#' as.av("ACICL") +#' as.av("ACI") +#' as.av("Virorax") # trade name +#' as.av("Zovirax") # trade name +#' +#' as.av("acyklofir") # severe spelling error, yet works +#' +#' # use av_* functions to get a specific properties (see ?av_property); +#' # they use as.av() internally: +#' av_name("J05AB01") +#' av_name("acicl") +as.av <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) { + meet_criteria(x, allow_class = c("character", "numeric", "integer", "factor"), allow_NA = TRUE) + meet_criteria(flag_multiple_results, allow_class = "logical", has_length = 1) + meet_criteria(info, allow_class = "logical", has_length = 1) + + if (is.av(x)) { + return(x) + } + if (all(x %in% c(AMR_env$AV_lookup$av, NA))) { + # all valid AB codes, but not yet right class + return(set_clean_class(x, + new_class = c("av", "character") + )) + } + + initial_search <- is.null(list(...)$initial_search) + already_regex <- isTRUE(list(...)$already_regex) + fast_mode <- isTRUE(list(...)$fast_mode) + + x_bak <- x + x <- toupper(x) + + # remove diacritics + x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT") + x <- gsub('"', "", x, fixed = TRUE) + x <- gsub("(specimen|specimen date|specimen_date|spec_date|gender|^dates?$)", "", x, ignore.case = TRUE, perl = TRUE) + x_bak_clean <- x + if (already_regex == FALSE) { + x_bak_clean <- generalise_antibiotic_name(x_bak_clean) + } + + x <- unique(x_bak_clean) # this means that every x is in fact generalise_antibiotic_name(x) + x_new <- rep(NA_character_, length(x)) + x_unknown <- character(0) + x_unknown_ATCs <- character(0) + + note_if_more_than_one_found <- function(found, index, from_text) { + if (initial_search == TRUE && isTRUE(length(from_text) > 1)) { + avnames <- av_name(from_text, tolower = TRUE, initial_search = FALSE) + if (av_name(found[1L], language = NULL) %like% "(clavulanic acid|avibactam)") { + avnames <- avnames[!avnames %in% c("clavulanic acid", "avibactam")] + } + if (length(avnames) > 1) { + warning_( + "More than one result was found for item ", index, ": ", + vector_and(avnames, quotes = FALSE) + ) + } + } + found[1L] + } + + # Fill in names, AB codes, CID codes and ATC codes directly (`x` is already clean and uppercase) + known_names <- x %in% AMR_env$AV_lookup$generalised_name + x_new[known_names] <- AMR_env$AV_lookup$av[match(x[known_names], AMR_env$AV_lookup$generalised_name)] + known_codes_av <- x %in% AMR_env$AV_lookup$av + known_codes_atc <- vapply(FUN.VALUE = logical(1), x, function(x_) x_ %in% unlist(AMR_env$AV_lookup$atc), USE.NAMES = FALSE) + known_codes_cid <- x %in% AMR_env$AV_lookup$cid + x_new[known_codes_av] <- AMR_env$AV_lookup$av[match(x[known_codes_av], AMR_env$AV_lookup$av)] + x_new[known_codes_atc] <- AMR_env$AV_lookup$av[vapply( + FUN.VALUE = integer(1), + x[known_codes_atc], + function(x_) { + which(vapply( + FUN.VALUE = logical(1), + AMR_env$AV_lookup$atc, + function(atc) x_ %in% atc + ))[1L] + }, + USE.NAMES = FALSE + )] + x_new[known_codes_cid] <- AMR_env$AV_lookup$av[match(x[known_codes_cid], AMR_env$AV_lookup$cid)] + previously_coerced <- x %in% AMR_env$av_previously_coerced$x + x_new[previously_coerced & is.na(x_new)] <- AMR_env$av_previously_coerced$av[match(x[is.na(x_new) & x %in% AMR_env$av_previously_coerced$x], AMR_env$av_previously_coerced$x)] + already_known <- known_names | known_codes_av | known_codes_atc | known_codes_cid | previously_coerced + + # fix for NAs + x_new[is.na(x)] <- NA + already_known[is.na(x)] <- FALSE + + if (initial_search == TRUE && sum(already_known) < length(x)) { + progress <- progress_ticker(n = sum(!already_known), n_min = 25, print = info) # start if n >= 25 + on.exit(close(progress)) + } + + for (i in which(!already_known)) { + if (initial_search == TRUE) { + progress$tick() + } + + if (is.na(x[i]) || is.null(x[i])) { + next + } + if (identical(x[i], "") || + # prevent "bacteria" from coercing to TMP, since Bacterial is a brand name of it: + identical(tolower(x[i]), "bacteria")) { + x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1]) + next + } + if (x[i] %like_case% "[A-Z][0-9][0-9][A-Z][A-Z][0-9][0-9]") { + # seems an ATC code, but the available ones are in `already_known`, so: + x_unknown <- c(x_unknown, x[i]) + x_unknown_ATCs <- c(x_unknown_ATCs, x[i]) + x_new[i] <- NA_character_ + next + } + + if (fast_mode == FALSE && flag_multiple_results == TRUE && x[i] %like% "[ ]") { + from_text <- tryCatch(suppressWarnings(av_from_text(x[i], initial_search = FALSE, translate_av = FALSE)[[1]]), + error = function(e) character(0) + ) + } else { + from_text <- character(0) + } + + # old code for phenoxymethylpenicillin (Peni V) + if (x[i] == "PNV") { + x_new[i] <- "PHN" + next + } + + # exact LOINC code + loinc_found <- unlist(lapply( + AMR_env$AV_lookup$generalised_loinc, + function(s) x[i] %in% s + )) + found <- AMR_env$AV_lookup$av[loinc_found == TRUE] + if (length(found) > 0) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # exact synonym + synonym_found <- unlist(lapply( + AMR_env$AV_lookup$generalised_synonyms, + function(s) x[i] %in% s + )) + found <- AMR_env$AV_lookup$av[synonym_found == TRUE] + if (length(found) > 0) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # length of input is quite long, and Levenshtein distance is only max 2 + if (nchar(x[i]) >= 10) { + levenshtein <- as.double(utils::adist(x[i], AMR_env$AV_lookup$generalised_name)) + if (any(levenshtein <= 2)) { + found <- AMR_env$AV_lookup$av[which(levenshtein <= 2)] + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + } + + # allow characters that resemble others, but only continue when having more than 3 characters + if (nchar(x[i]) <= 3) { + x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1]) + next + } + x_spelling <- x[i] + if (already_regex == FALSE) { + x_spelling <- gsub("[IY]+", "[IY]+", x_spelling, perl = TRUE) + x_spelling <- gsub("(C|K|Q|QU|S|Z|X|KS)+", "(C|K|Q|QU|S|Z|X|KS)+", x_spelling, perl = TRUE) + x_spelling <- gsub("(PH|F|V)+", "(PH|F|V)+", x_spelling, perl = TRUE) + x_spelling <- gsub("(TH|T)+", "(TH|T)+", x_spelling, perl = TRUE) + x_spelling <- gsub("A+", "A+", x_spelling, perl = TRUE) + x_spelling <- gsub("E+", "E+", x_spelling, perl = TRUE) + x_spelling <- gsub("O+", "O+", x_spelling, perl = TRUE) + # allow any ending of -in/-ine and -im/-ime + x_spelling <- gsub("(\\[IY\\]\\+(N|M)|\\[IY\\]\\+(N|M)E\\+?)$", "[IY]+(N|M)E*", x_spelling, perl = TRUE) + # allow any ending of -ol/-ole + x_spelling <- gsub("(O\\+L|O\\+LE\\+)$", "O+LE*", x_spelling, perl = TRUE) + # allow any ending of -on/-one + x_spelling <- gsub("(O\\+N|O\\+NE\\+)$", "O+NE*", x_spelling, perl = TRUE) + # replace multiple same characters to single one with '+', like "ll" -> "l+" + x_spelling <- gsub("(.)\\1+", "\\1+", x_spelling, perl = TRUE) + # replace spaces and slashes with a possibility on both + x_spelling <- gsub("[ /]", "( .*|.*/)", x_spelling, perl = TRUE) + # correct for digital reading text (OCR) + x_spelling <- gsub("[NRD8B]", "[NRD8B]", x_spelling, perl = TRUE) + x_spelling <- gsub("(O|0)", "(O|0)+", x_spelling, perl = TRUE) + x_spelling <- gsub("++", "+", x_spelling, fixed = TRUE) + } + + # try if name starts with it + found <- AMR_env$AV_lookup[which(AMR_env$AV_lookup$generalised_name %like% paste0("^", x_spelling)), "av", drop = TRUE] + if (length(found) > 0) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + # try if name ends with it + found <- AMR_env$AV_lookup[which(AMR_env$AV_lookup$generalised_name %like% paste0(x_spelling, "$")), "av", drop = TRUE] + if (nchar(x[i]) >= 4 && length(found) > 0) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # and try if any synonym starts with it + synonym_found <- unlist(lapply( + AMR_env$AV_lookup$generalised_synonyms, + function(s) any(s %like% paste0("^", x_spelling)) + )) + found <- AMR_env$AV_lookup$av[synonym_found == TRUE] + if (length(found) > 0) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # INITIAL SEARCH - More uncertain results ---- + + if (initial_search == TRUE && fast_mode == FALSE) { + # only run on first try + + # try by removing all spaces + if (x[i] %like% " ") { + found <- suppressWarnings(as.av(gsub(" +", "", x[i], perl = TRUE), initial_search = FALSE)) + if (length(found) > 0 && !is.na(found)) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + } + + # try by removing all spaces and numbers + if (x[i] %like% " " || x[i] %like% "[0-9]") { + found <- suppressWarnings(as.av(gsub("[ 0-9]", "", x[i], perl = TRUE), initial_search = FALSE)) + if (length(found) > 0 && !is.na(found)) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + } + + # transform back from other languages and try again + x_translated <- paste(lapply( + strsplit(x[i], "[^A-Z0-9]"), + function(y) { + for (i in seq_len(length(y))) { + for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) { + y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]), + TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) & + !isFALSE(TRANSLATIONS$fixed)), "pattern"], + y[i] + ) + } + } + generalise_antibiotic_name(y) + } + )[[1]], + collapse = "/" + ) + x_translated_guess <- suppressWarnings(as.av(x_translated, initial_search = FALSE)) + if (!is.na(x_translated_guess)) { + x_new[i] <- x_translated_guess + next + } + + # now also try to coerce brandname combinations like "Amoxy/clavulanic acid" + x_translated <- paste(lapply( + strsplit(x_translated, "[^A-Z0-9 ]"), + function(y) { + for (i in seq_len(length(y))) { + y_name <- suppressWarnings(av_name(y[i], language = NULL, initial_search = FALSE)) + y[i] <- ifelse(!is.na(y_name), + y_name, + y[i] + ) + } + generalise_antibiotic_name(y) + } + )[[1]], + collapse = "/" + ) + x_translated_guess <- suppressWarnings(as.av(x_translated, initial_search = FALSE)) + if (!is.na(x_translated_guess)) { + x_new[i] <- x_translated_guess + next + } + + # try by removing all trailing capitals + if (x[i] %like_case% "[a-z]+[A-Z]+$") { + found <- suppressWarnings(as.av(gsub("[A-Z]+$", "", x[i], perl = TRUE), initial_search = FALSE)) + if (!is.na(found)) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + } + + # keep only letters + found <- suppressWarnings(as.av(gsub("[^A-Z]", "", x[i], perl = TRUE), initial_search = FALSE)) + if (!is.na(found)) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # try from a bigger text, like from a health care record, see ?av_from_text + # already calculated above if flag_multiple_results = TRUE + if (flag_multiple_results == TRUE) { + found <- from_text[1L] + } else { + found <- tryCatch(suppressWarnings(av_from_text(x[i], initial_search = FALSE, translate_av = FALSE)[[1]][1L]), + error = function(e) NA_character_ + ) + } + if (!is.na(found)) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # first 5 + found <- suppressWarnings(as.av(substr(x[i], 1, 5), initial_search = FALSE)) + if (!is.na(found)) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # make all consonants facultative + search_str <- gsub("([BCDFGHJKLMNPQRSTVWXZ])", "\\1*", x[i], perl = TRUE) + found <- suppressWarnings(as.av(search_str, initial_search = FALSE, already_regex = TRUE)) + # keep at least 4 normal characters + if (nchar(gsub(".\\*", "", search_str, perl = TRUE)) < 4) { + found <- NA + } + if (!is.na(found)) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # make all vowels facultative + search_str <- gsub("([AEIOUY])", "\\1*", x[i], perl = TRUE) + found <- suppressWarnings(as.av(search_str, initial_search = FALSE, already_regex = TRUE)) + # keep at least 5 normal characters + if (nchar(gsub(".\\*", "", search_str, perl = TRUE)) < 5) { + found <- NA + } + if (!is.na(found)) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # allow misspelling of vowels + x_spelling <- gsub("A+", "[AEIOU]+", x_spelling, fixed = TRUE) + x_spelling <- gsub("E+", "[AEIOU]+", x_spelling, fixed = TRUE) + x_spelling <- gsub("I+", "[AEIOU]+", x_spelling, fixed = TRUE) + x_spelling <- gsub("O+", "[AEIOU]+", x_spelling, fixed = TRUE) + x_spelling <- gsub("U+", "[AEIOU]+", x_spelling, fixed = TRUE) + found <- suppressWarnings(as.av(x_spelling, initial_search = FALSE, already_regex = TRUE)) + if (!is.na(found)) { + x_new[i] <- note_if_more_than_one_found(found, i, from_text) + next + } + + # try with switched character, like "mreopenem" + for (j in seq_len(nchar(x[i]))) { + x_switched <- paste0( + # beginning part: + substr(x[i], 1, j - 1), + # here is the switching of 2 characters: + substr(x[i], j + 1, j + 1), + substr(x[i], j, j), + # ending part: + substr(x[i], j + 2, nchar(x[i])) + ) + found <- suppressWarnings(as.av(x_switched, initial_search = FALSE)) + if (!is.na(found)) { + break + } + } + if (!is.na(found)) { + x_new[i] <- found[1L] + next + } + } # end of initial_search = TRUE + + # not found + x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1]) + } + + if (initial_search == TRUE && sum(already_known) < length(x)) { + close(progress) + } + + # save to package env to save time for next time + if (initial_search == TRUE) { + AMR_env$av_previously_coerced <- AMR_env$av_previously_coerced[which(!AMR_env$av_previously_coerced$x %in% x), , drop = FALSE] + AMR_env$av_previously_coerced <- unique(rbind(AMR_env$av_previously_coerced, + data.frame( + x = x, + av = x_new, + x_bak = x_bak[match(x, x_bak_clean)], + stringsAsFactors = FALSE + ), + stringsAsFactors = FALSE + )) + } + + # take failed ATC codes apart from rest + if (length(x_unknown_ATCs) > 0 && fast_mode == FALSE) { + warning_( + "in `as.av()`: these ATC codes are not (yet) in the antivirals data set: ", + vector_and(x_unknown_ATCs), "." + ) + } + x_unknown <- x_unknown[!x_unknown %in% x_unknown_ATCs] + x_unknown <- c(x_unknown, + AMR_env$av_previously_coerced$x_bak[which(AMR_env$av_previously_coerced$x %in% x & is.na(AMR_env$av_previously_coerced$av))]) + if (length(x_unknown) > 0 && fast_mode == FALSE) { + warning_( + "in `as.av()`: these values could not be coerced to a valid antiviral agent ID: ", + vector_and(x_unknown), "." + ) + } + + x_result <- x_new[match(x_bak_clean, x)] + if (length(x_result) == 0) { + x_result <- NA_character_ + } + + set_clean_class(x_result, + new_class = c("av", "character") + ) +} + +#' @rdname as.av +#' @export +is.av <- function(x) { + inherits(x, "av") +} + +# will be exported using s3_register() in R/zzz.R +pillar_shaft.av <- function(x, ...) { + out <- trimws(format(x)) + out[!is.na(x)] <- gsub("+", font_subtle("+"), out[!is.na(x)], fixed = TRUE) + out[is.na(x)] <- font_na(NA) + create_pillar_column(out, align = "left", min_width = 4) +} + +# will be exported using s3_register() in R/zzz.R +type_sum.av <- function(x, ...) { + "av" +} + +#' @method print av +#' @export +#' @noRd +print.av <- function(x, ...) { + cat("Class 'av'\n") + print(as.character(x), quote = FALSE) +} + +#' @method as.data.frame av +#' @export +#' @noRd +as.data.frame.av <- function(x, ...) { + nm <- deparse1(substitute(x)) + if (!"nm" %in% names(list(...))) { + as.data.frame.vector(as.av(x), ..., nm = nm) + } else { + as.data.frame.vector(as.av(x), ...) + } +} +#' @method [ av +#' @export +#' @noRd +"[.av" <- function(x, ...) { + y <- NextMethod() + attributes(y) <- attributes(x) + y +} +#' @method [[ av +#' @export +#' @noRd +"[[.av" <- function(x, ...) { + y <- NextMethod() + attributes(y) <- attributes(x) + y +} +#' @method [<- av +#' @export +#' @noRd +"[<-.av" <- function(i, j, ..., value) { + y <- NextMethod() + attributes(y) <- attributes(i) + return_after_integrity_check(y, "antiviral agent code", AMR_env$AV_lookup$av) +} +#' @method [[<- av +#' @export +#' @noRd +"[[<-.av" <- function(i, j, ..., value) { + y <- NextMethod() + attributes(y) <- attributes(i) + return_after_integrity_check(y, "antiviral agent code", AMR_env$AV_lookup$av) +} +#' @method c av +#' @export +#' @noRd +c.av <- function(...) { + x <- list(...)[[1L]] + y <- NextMethod() + attributes(y) <- attributes(x) + return_after_integrity_check(y, "antiviral agent code", AMR_env$AV_lookup$av) +} + +#' @method unique av +#' @export +#' @noRd +unique.av <- function(x, incomparables = FALSE, ...) { + y <- NextMethod() + attributes(y) <- attributes(x) + y +} + +#' @method rep av +#' @export +#' @noRd +rep.av <- function(x, ...) { + y <- NextMethod() + attributes(y) <- attributes(x) + y +} + +get_translate_av <- function(translate_av) { + translate_av <- as.character(translate_av)[1L] + if (translate_av %in% c("TRUE", "official")) { + return("name") + } else if (translate_av %in% c(NA_character_, "FALSE")) { + return(FALSE) + } else { + translate_av <- tolower(translate_av) + stop_ifnot(translate_av %in% colnames(AMR::antivirals), + "invalid value for 'translate_av', this must be a column name of the antivirals data set\n", + "or TRUE (equals 'name') or FALSE to not translate at all.", + call = FALSE + ) + translate_av + } +} diff --git a/R/av_from_text.R b/R/av_from_text.R new file mode 100644 index 00000000..4157e5ee --- /dev/null +++ b/R/av_from_text.R @@ -0,0 +1,186 @@ +# ==================================================================== # +# TITLE # +# AMR: An R Package for Working with Antimicrobial Resistance Data # +# # +# SOURCE # +# https://github.com/msberends/AMR # +# # +# CITE AS # +# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # +# (2022). AMR: An R Package for Working with Antimicrobial Resistance # +# Data. Journal of Statistical Software, 104(3), 1-31. # +# doi:10.18637/jss.v104.i03 # +# # +# Developed at the University of Groningen, the Netherlands, in # +# collaboration with non-profit organisations Certe Medical # +# Diagnostics & Advice, and University Medical Center Groningen. # +# # +# This R package is free software; you can freely use and distribute # +# it for both personal and commercial purposes under the terms of the # +# GNU General Public License version 2.0 (GNU GPL-2), as published by # +# the Free Software Foundation. # +# We created this package for both routine data analysis and academic # +# research and it was publicly released in the hope that it will be # +# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # +# # +# Visit our website for the full manual and a complete tutorial about # +# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # +# ==================================================================== # + +#' Retrieve Antiviral Drug Names and Doses from Clinical Text +#' +#' Use this function on e.g. clinical texts from health care records. It returns a [list] with all antiviral drugs, doses and forms of administration found in the texts. +#' @param text text to analyse +#' @param type type of property to search for, either `"drug"`, `"dose"` or `"administration"`, see *Examples* +#' @param collapse a [character] to pass on to `paste(, collapse = ...)` to only return one [character] per element of `text`, see *Examples* +#' @param translate_av if `type = "drug"`: a column name of the [antivirals] data set to translate the antibiotic abbreviations to, using [av_property()]. Defaults to `FALSE`. Using `TRUE` is equal to using "name". +#' @param thorough_search a [logical] to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to `TRUE` will take considerably more time than when using `FALSE`. At default, it will turn `TRUE` when all input elements contain a maximum of three words. +#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode +#' @param ... arguments passed on to [as.av()] +#' @details This function is also internally used by [as.av()], although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the [as.av()] function may use very long regular expression to match brand names of antiviral agents. This may fail on some systems. +#' +#' ### Argument `type` +#' At default, the function will search for antiviral drug names. All text elements will be searched for official names, ATC codes and brand names. As it uses [as.av()] internally, it will correct for misspelling. +#' +#' With `type = "dose"` (or similar, like "dosing", "doses"), all text elements will be searched for [numeric] values that are higher than 100 and do not resemble years. The output will be [numeric]. It supports any unit (g, mg, IE, etc.) and multiple values in one clinical text, see *Examples*. +#' +#' With `type = "administration"` (or abbreviations, like "admin", "adm"), all text elements will be searched for a form of drug administration. It supports the following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal and vaginal. Abbreviations for oral (such as 'po', 'per os') will become "oral", all values for intravenous (such as 'iv', 'intraven') will become "iv". It supports multiple values in one clinical text, see *Examples*. +#' +#' ### Argument `collapse` +#' Without using `collapse`, this function will return a [list]. This can be convenient to use e.g. inside a `mutate()`):\cr +#' `df %>% mutate(avx = av_from_text(clinical_text))` +#' +#' The returned AV codes can be transformed to official names, groups, etc. with all [`av_*`][av_property()] functions such as [av_name()] and [av_group()], or by using the `translate_av` argument. +#' +#' With using `collapse`, this function will return a [character]:\cr +#' `df %>% mutate(avx = av_from_text(clinical_text, collapse = "|"))` +#' @export +#' @return A [list], or a [character] if `collapse` is not `NULL` +#' @examples +#' av_from_text("28/03/2020 valaciclovir po tid") +#' av_from_text("28/03/2020 valaciclovir po tid", type = "admin") +av_from_text <- function(text, + type = c("drug", "dose", "administration"), + collapse = NULL, + translate_av = FALSE, + thorough_search = NULL, + info = interactive(), + ...) { + if (missing(type)) { + type <- type[1L] + } + + meet_criteria(text) + meet_criteria(type, allow_class = "character", has_length = 1) + meet_criteria(collapse, has_length = 1, allow_NULL = TRUE) + meet_criteria(translate_av, allow_NULL = FALSE) # get_translate_av() will be more informative about what's allowed + meet_criteria(thorough_search, allow_class = "logical", has_length = 1, allow_NULL = TRUE) + meet_criteria(info, allow_class = "logical", has_length = 1) + + type <- tolower(trimws2(type)) + + text <- tolower(as.character(text)) + text_split_all <- strsplit(text, "[ ;.,:\\|]") + progress <- progress_ticker(n = length(text_split_all), n_min = 5, print = info) + on.exit(close(progress)) + + if (type %like% "(drug|ab|anti)") { + translate_av <- get_translate_av(translate_av) + + if (isTRUE(thorough_search) || + (isTRUE(is.null(thorough_search)) && max(vapply(FUN.VALUE = double(1), text_split_all, length), na.rm = TRUE) <= 3)) { + text_split_all <- text_split_all[nchar(text_split_all) >= 4 & grepl("[a-z]+", text_split_all)] + result <- lapply(text_split_all, function(text_split) { + progress$tick() + suppressWarnings( + as.av(text_split, ...) + ) + }) + } else { + # no thorough search + names_atc <- substr(c(AMR::antivirals$name, AMR::antivirals$atc), 1, 5) + synonyms <- unlist(AMR::antivirals$synonyms) + synonyms <- synonyms[nchar(synonyms) >= 4] + # regular expression must not be too long, so split synonyms in two: + synonyms_part1 <- synonyms[seq_len(0.5 * length(synonyms))] + synonyms_part2 <- synonyms[!synonyms %in% synonyms_part1] + to_regex <- function(x) { + paste0( + "^(", + paste0(unique(gsub("[^a-z0-9]+", "", sort(tolower(x)))), collapse = "|"), + ").*" + ) + } + result <- lapply(text_split_all, function(text_split) { + progress$tick() + suppressWarnings( + as.av( + unique(c( + text_split[text_split %like_case% to_regex(names_atc)], + text_split[text_split %like_case% to_regex(synonyms_part1)], + text_split[text_split %like_case% to_regex(synonyms_part2)] + )), + ... + ) + ) + }) + } + + close(progress) + + result <- lapply(result, function(out) { + out <- out[!is.na(out)] + if (length(out) == 0) { + as.av(NA) + } else { + if (!isFALSE(translate_av)) { + out <- av_property(out, property = translate_av, initial_search = FALSE) + } + out + } + }) + } else if (type %like% "dos") { + text_split_all <- strsplit(text, " ", fixed = TRUE) + result <- lapply(text_split_all, function(text_split) { + text_split <- text_split[text_split %like% "^[0-9]{2,}(/[0-9]+)?[a-z]*$"] + # only left part of "/", like 500 in "500/125" + text_split <- gsub("/.*", "", text_split) + text_split <- gsub(",", ".", text_split, fixed = TRUE) # foreign system using comma as decimal sep + text_split <- as.double(gsub("[^0-9.]", "", text_split)) + # minimal 100 units/mg and no years that unlikely doses + text_split <- text_split[text_split >= 100 & !text_split %in% c(1951:1999, 2001:2049)] + + if (length(text_split) > 0) { + text_split + } else { + NA_real_ + } + }) + } else if (type %like% "adm") { + result <- lapply(text_split_all, function(text_split) { + text_split <- text_split[text_split %like% "(^iv$|intraven|^po$|per os|oral|implant|inhal|instill|nasal|paren|rectal|sublingual|buccal|trans.*dermal|vaginal)"] + if (length(text_split) > 0) { + text_split <- gsub("(^po$|.*per os.*)", "oral", text_split) + text_split <- gsub("(^iv$|.*intraven.*)", "iv", text_split) + text_split + } else { + NA_character_ + } + }) + } else { + stop_("`type` must be either 'drug', 'dose' or 'administration'") + } + + # collapse text if needed + if (!is.null(collapse)) { + result <- vapply(FUN.VALUE = character(1), result, function(x) { + if (length(x) == 1 & all(is.na(x))) { + NA_character_ + } else { + paste0(x, collapse = collapse) + } + }) + } + + result +} diff --git a/R/av_property.R b/R/av_property.R new file mode 100644 index 00000000..6f3d0265 --- /dev/null +++ b/R/av_property.R @@ -0,0 +1,290 @@ +# ==================================================================== # +# TITLE # +# AMR: An R Package for Working with Antimicrobial Resistance Data # +# # +# SOURCE # +# https://github.com/msberends/AMR # +# # +# CITE AS # +# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # +# (2022). AMR: An R Package for Working with Antimicrobial Resistance # +# Data. Journal of Statistical Software, 104(3), 1-31. # +# doi:10.18637/jss.v104.i03 # +# # +# Developed at the University of Groningen, the Netherlands, in # +# collaboration with non-profit organisations Certe Medical # +# Diagnostics & Advice, and University Medical Center Groningen. # +# # +# This R package is free software; you can freely use and distribute # +# it for both personal and commercial purposes under the terms of the # +# GNU General Public License version 2.0 (GNU GPL-2), as published by # +# the Free Software Foundation. # +# We created this package for both routine data analysis and academic # +# research and it was publicly released in the hope that it will be # +# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # +# # +# Visit our website for the full manual and a complete tutorial about # +# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # +# ==================================================================== # + +#' Get Properties of an Antiviral Agent +#' +#' Use these functions to return a specific property of an antiviral agent from the [antivirals] data set. All input values will be evaluated internally with [as.av()]. +#' @param x any (vector of) text that can be coerced to a valid antiviral agent code with [as.av()] +#' @param tolower a [logical] to indicate whether the first [character] of every output should be transformed to a lower case [character]. +#' @param property one of the column names of one of the [antivirals] data set: `vector_or(colnames(antivirals), sort = FALSE)`. +#' @param language language of the returned text, defaults to system language (see [get_AMR_locale()]) and can also be set with `getOption("AMR_locale")`. Use `language = NULL` or `language = ""` to prevent translation. +#' @param administration way of administration, either `"oral"` or `"iv"` +#' @param open browse the URL using [utils::browseURL()] +#' @param ... other arguments passed on to [as.av()] +#' @details All output [will be translated][translate] where possible. +#' +#' The function [av_url()] will return the direct URL to the official WHO website. A warning will be returned if the required ATC code is not available. +#' @inheritSection as.av Source +#' @rdname av_property +#' @name av_property +#' @return +#' - An [integer] in case of [av_cid()] +#' - A named [list] in case of [av_info()] and multiple [av_atc()]/[av_synonyms()]/[av_tradenames()] +#' - A [double] in case of [av_ddd()] +#' - A [character] in all other cases +#' @export +#' @seealso [antivirals] +#' @inheritSection AMR Reference Data Publicly Available +#' @examples +#' # all properties: +#' av_name("ACI") +#' av_atc("ACI") +#' av_cid("ACI") +#' av_synonyms("ACI") +#' av_tradenames("ACI") +#' av_group("ACI") +#' av_url("ACI") +#' +#' # smart lowercase tranformation +#' av_name(x = c("ACI", "VALA")) +#' av_name(x = c("ACI", "VALA"), tolower = TRUE) +#' +#' # defined daily doses (DDD) +#' av_ddd("ACI", "oral") +#' av_ddd_units("ACI", "oral") +#' av_ddd("ACI", "iv") +#' av_ddd_units("ACI", "iv") +#' +#' av_info("ACI") # all properties as a list +#' +#' # all av_* functions use as.av() internally, so you can go from 'any' to 'any': +#' av_atc("ACI") +#' av_group("J05AB01") +#' av_loinc("abacavir") +#' av_name("29113-8") +#' av_name(135398513) +#' av_name("J05AB01") +av_name <- function(x, language = get_AMR_locale(), tolower = FALSE, ...) { + meet_criteria(x, allow_NA = TRUE) + language <- validate_language(language) + meet_criteria(tolower, allow_class = "logical", has_length = 1) + + x <- translate_into_language(av_validate(x = x, property = "name", ...), language = language, only_affect_ab_names = TRUE) + if (tolower == TRUE) { + # use perl to only transform the first character + # as we want "polymyxin B", not "polymyxin b" + x <- gsub("^([A-Z])", "\\L\\1", x, perl = TRUE) + } + x +} + +#' @rdname av_property +#' @export +av_cid <- function(x, ...) { + meet_criteria(x, allow_NA = TRUE) + av_validate(x = x, property = "cid", ...) +} + +#' @rdname av_property +#' @export +av_synonyms <- function(x, ...) { + meet_criteria(x, allow_NA = TRUE) + syns <- av_validate(x = x, property = "synonyms", ...) + names(syns) <- x + if (length(syns) == 1) { + unname(unlist(syns)) + } else { + syns + } +} + +#' @rdname av_property +#' @export +av_tradenames <- function(x, ...) { + meet_criteria(x, allow_NA = TRUE) + av_synonyms(x, ...) +} + +#' @rdname av_property +#' @export +av_group <- function(x, language = get_AMR_locale(), ...) { + meet_criteria(x, allow_NA = TRUE) + language <- validate_language(language) + translate_into_language(av_validate(x = x, property = "atc_group", ...), language = language, only_affect_ab_names = TRUE) +} + +#' @rdname av_property +#' @export +av_atc <- function(x, ...) { + meet_criteria(x, allow_NA = TRUE) + # ATCs in the antivirals data set are not a list + av_validate(x = x, property = "atc", ...) +} + +#' @rdname av_property +#' @export +av_loinc <- function(x, ...) { + meet_criteria(x, allow_NA = TRUE) + loincs <- av_validate(x = x, property = "loinc", ...) + names(loincs) <- x + if (length(loincs) == 1) { + unname(unlist(loincs)) + } else { + loincs + } +} + +#' @rdname av_property +#' @export +av_ddd <- function(x, administration = "oral", ...) { + meet_criteria(x, allow_NA = TRUE) + meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1) + + x <- as.av(x, ...) + ddd_prop <- paste0(administration, "_ddd") + out <- av_validate(x = x, property = ddd_prop) + + if (any(av_name(x, language = NULL) %like% "/" & is.na(out))) { + warning_( + "in `av_ddd()`: DDDs of some combined products are available for different dose combinations and not (yet) part of the AMR package.", + "Please refer to the WHOCC website:\n", + "www.whocc.no/ddd/list_of_ddds_combined_products/" + ) + } + out +} + +#' @rdname av_property +#' @export +av_ddd_units <- function(x, administration = "oral", ...) { + meet_criteria(x, allow_NA = TRUE) + meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1) + + x <- as.av(x, ...) + ddd_prop <- paste0(administration, "_units") + out <- av_validate(x = x, property = ddd_prop) + + if (any(av_name(x, language = NULL) %like% "/" & is.na(out))) { + warning_( + "in `av_ddd_units()`: DDDs of some combined products are available for different dose combinations and not (yet) part of the AMR package.", + "Please refer to the WHOCC website:\n", + "www.whocc.no/ddd/list_of_ddds_combined_products/" + ) + } + out +} + +#' @rdname av_property +#' @export +av_info <- function(x, language = get_AMR_locale(), ...) { + meet_criteria(x, allow_NA = TRUE) + language <- validate_language(language) + + x <- as.av(x, ...) + list( + av = as.character(x), + cid = av_cid(x), + name = av_name(x, language = language), + group = av_group(x, language = language), + atc = av_atc(x), + tradenames = av_tradenames(x), + loinc = av_loinc(x), + ddd = list( + oral = list( + amount = av_ddd(x, administration = "oral"), + units = av_ddd_units(x, administration = "oral") + ), + iv = list( + amount = av_ddd(x, administration = "iv"), + units = av_ddd_units(x, administration = "iv") + ) + ) + ) +} + + +#' @rdname av_property +#' @export +av_url <- function(x, open = FALSE, ...) { + meet_criteria(x, allow_NA = TRUE) + meet_criteria(open, allow_class = "logical", has_length = 1) + + av <- as.av(x = x, ...) + atcs <- av_atc(av, only_first = TRUE) + u <- paste0("https://www.whocc.no/atc_ddd_index/?code=", atcs, "&showdescription=no") + u[is.na(atcs)] <- NA_character_ + names(u) <- av_name(av) + + NAs <- av_name(av, tolower = TRUE, language = NULL)[!is.na(av) & is.na(atcs)] + if (length(NAs) > 0) { + warning_("in `av_url()`: no ATC code available for ", vector_and(NAs, quotes = FALSE), ".") + } + + if (open == TRUE) { + if (length(u) > 1 && !is.na(u[1L])) { + warning_("in `av_url()`: only the first URL will be opened, as `browseURL()` only suports one string.") + } + if (!is.na(u[1L])) { + utils::browseURL(u[1L]) + } + } + u +} + +#' @rdname av_property +#' @export +av_property <- function(x, property = "name", language = get_AMR_locale(), ...) { + meet_criteria(x, allow_NA = TRUE) + meet_criteria(property, is_in = colnames(AMR::antivirals), has_length = 1) + meet_criteria(language, is_in = c(LANGUAGES_SUPPORTED, ""), has_length = 1, allow_NULL = TRUE, allow_NA = TRUE) + translate_into_language(av_validate(x = x, property = property, ...), language = language) +} + +av_validate <- function(x, property, ...) { + if (tryCatch(all(x[!is.na(x)] %in% AMR_env$AV_lookup$av), error = function(e) FALSE)) { + # special case for av_* functions where class is already 'av' + x <- AMR_env$AV_lookup[match(x, AMR_env$AV_lookup$av), property, drop = TRUE] + } else { + # try to catch an error when inputting an invalid argument + # so the 'call.' can be set to FALSE + tryCatch(x[1L] %in% AMR_env$AV_lookup[1, property, drop = TRUE], + error = function(e) stop(e$message, call. = FALSE) + ) + + if (!all(x %in% AMR_env$AV_lookup[, property, drop = TRUE])) { + x <- as.av(x, ...) + if (all(is.na(x)) && is.list(AMR_env$AV_lookup[, property, drop = TRUE])) { + x <- rep(NA_character_, length(x)) + } else { + x <- AMR_env$AV_lookup[match(x, AMR_env$AV_lookup$av), property, drop = TRUE] + } + } + } + + if (property == "av") { + return(set_clean_class(x, new_class = c("av", "character"))) + } else if (property == "cid") { + return(as.integer(x)) + } else if (property %like% "ddd") { + return(as.double(x)) + } else { + x[is.na(x)] <- NA + return(x) + } +} diff --git a/R/data.R b/R/data.R index 36acfe20..36504655 100755 --- a/R/data.R +++ b/R/data.R @@ -48,15 +48,17 @@ #' - `loinc`\cr All LOINC codes (Logical Observation Identifiers Names and Codes) associated with the name of the antimicrobial agent. Use [ab_loinc()] to retrieve them quickly, see [ab_property()]. #' #' ### For the [antivirals] data set: a [tibble][tibble::tibble] with `r nrow(antivirals)` observations and `r ncol(antivirals)` variables: +#' - `av`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available +#' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO #' - `atc`\cr ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC #' - `cid`\cr Compound ID as found in PubChem -#' - `name`\cr Official name as used by WHONET/EARS-Net or the WHO #' - `atc_group`\cr Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC #' - `synonyms`\cr Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID #' - `oral_ddd`\cr Defined Daily Dose (DDD), oral treatment #' - `oral_units`\cr Units of `oral_ddd` #' - `iv_ddd`\cr Defined Daily Dose (DDD), parenteral treatment #' - `iv_units`\cr Units of `iv_ddd` +#' - `loinc`\cr All LOINC codes (Logical Observation Identifiers Names and Codes) associated with the name of the antimicrobial agent. #' @details Properties that are based on an ATC code are only available when an ATC is available. These properties are: `atc_group1`, `atc_group2`, `oral_ddd`, `oral_units`, `iv_ddd` and `iv_units`. #' #' Synonyms (i.e. trade names) were derived from the PubChem Compound ID (column `cid`) and consequently only available where a CID is available. diff --git a/R/mdro.R b/R/mdro.R index 32a70557..c68fa32a 100755 --- a/R/mdro.R +++ b/R/mdro.R @@ -248,11 +248,6 @@ mdro <- function(x = NULL, pct_required_classes <- pct_required_classes / 100 } - if (!is.null(list(...)$country)) { - warning_("in `mdro()`: using `country` is deprecated, use `guideline` instead. See ?mdro") - guideline <- list(...)$country - } - guideline.bak <- guideline if (is.list(guideline)) { # Custom MDRO guideline --------------------------------------------------- diff --git a/R/rsi_calc.R b/R/rsi_calc.R index 78a269fa..31bb7d59 100755 --- a/R/rsi_calc.R +++ b/R/rsi_calc.R @@ -375,20 +375,3 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both" out <- as_original_data_class(out, class(data.bak)) structure(out, class = c("rsi_df", class(out))) } - -get_translate_ab <- function(translate_ab) { - translate_ab <- as.character(translate_ab)[1L] - if (translate_ab %in% c("TRUE", "official")) { - return("name") - } else if (translate_ab %in% c(NA_character_, "FALSE")) { - return(FALSE) - } else { - translate_ab <- tolower(translate_ab) - stop_ifnot(translate_ab %in% colnames(AMR::antibiotics), - "invalid value for 'translate_ab', this must be a column name of the antibiotics data set\n", - "or TRUE (equals 'name') or FALSE to not translate at all.", - call = FALSE - ) - translate_ab - } -} diff --git a/R/sysdata.rda b/R/sysdata.rda index 51c6f132..9340f2e4 100644 Binary files a/R/sysdata.rda and b/R/sysdata.rda differ diff --git a/R/vctrs.R b/R/vctrs.R index 19759820..0c165a66 100644 --- a/R/vctrs.R +++ b/R/vctrs.R @@ -70,6 +70,20 @@ vec_cast.ab.character <- function(x, to, ...) { return_after_integrity_check(x, "antimicrobial code", as.character(AMR_env$AB_lookup$ab)) } +# S3: av +vec_ptype2.character.av <- function(x, y, ...) { + x +} +vec_ptype2.av.character <- function(x, y, ...) { + y +} +vec_cast.character.av <- function(x, to, ...) { + as.character(x) +} +vec_cast.av.character <- function(x, to, ...) { + return_after_integrity_check(x, "antiviral agent code", as.character(AMR_env$AV_lookup$av)) +} + # S3: mo vec_ptype2.character.mo <- function(x, y, ...) { x diff --git a/R/zzz.R b/R/zzz.R index 80294f15..5e41b98c 100755 --- a/R/zzz.R +++ b/R/zzz.R @@ -50,6 +50,11 @@ AMR_env$ab_previously_coerced <- data.frame( ab = character(0), stringsAsFactors = FALSE ) +AMR_env$av_previously_coerced <- data.frame( + x = character(0), + av = character(0), + stringsAsFactors = FALSE +) AMR_env$rsi_interpretation_history <- data.frame( datetime = Sys.time()[0], index = integer(0), @@ -87,11 +92,13 @@ if (utf8_supported && !is_latex) { # developers of the vctrs package: # https://github.com/r-lib/vctrs/blob/05968ce8e669f73213e3e894b5f4424af4f46316/R/register-s3.R s3_register("pillar::pillar_shaft", "ab") + s3_register("pillar::pillar_shaft", "av") s3_register("pillar::pillar_shaft", "mo") s3_register("pillar::pillar_shaft", "rsi") s3_register("pillar::pillar_shaft", "mic") s3_register("pillar::pillar_shaft", "disk") s3_register("tibble::type_sum", "ab") + s3_register("tibble::type_sum", "av") s3_register("tibble::type_sum", "mo") s3_register("tibble::type_sum", "rsi") s3_register("tibble::type_sum", "mic") @@ -129,6 +136,11 @@ if (utf8_supported && !is_latex) { s3_register("vctrs::vec_ptype2", "ab.character") s3_register("vctrs::vec_cast", "character.ab") s3_register("vctrs::vec_cast", "ab.character") + # S3: av + s3_register("vctrs::vec_ptype2", "character.av") + s3_register("vctrs::vec_ptype2", "av.character") + s3_register("vctrs::vec_cast", "character.av") + s3_register("vctrs::vec_cast", "av.character") # S3: mo s3_register("vctrs::vec_ptype2", "character.mo") s3_register("vctrs::vec_ptype2", "mo.character") @@ -168,6 +180,7 @@ if (utf8_supported && !is_latex) { # reference data - they have additional columns compared to `antibiotics` and `microorganisms` to improve speed # they cannot be part of R/sysdata.rda since CRAN thinks it would make the package too large (+3 MB) AMR_env$AB_lookup <- create_AB_lookup() + AMR_env$AV_lookup <- create_AV_lookup() AMR_env$MO_lookup <- create_MO_lookup() } @@ -190,6 +203,10 @@ create_AB_lookup <- function() { cbind(AMR::antibiotics, AB_LOOKUP) } +create_AV_lookup <- function() { + cbind(AMR::antivirals, AV_LOOKUP) +} + create_MO_lookup <- function() { MO_lookup <- AMR::microorganisms diff --git a/_pkgdown.yml b/_pkgdown.yml index 63981416..17721691 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -102,9 +102,9 @@ navbar: - text: "Get properties of an antibiotic" icon: "fa-capsules" href: "reference/ab_property.html" # reference instead of an article - # - text: "Other: benchmarks" - # icon: "fa-shipping-fast" - # href: "articles/benchmarks.html" + - text: "Get properties of an antiviral agent" + icon: "fa-capsules" + href: "reference/av_property.html" # reference instead of an article - text: "Manual" icon: "fa-book-open" href: "reference/index.html" @@ -175,8 +175,19 @@ reference: - "`mean_amr_distance`" - "`resistance_predict`" - "`guess_ab_col`" + + - title: "Other: antiviral drugs" + desc: > + This package also provides extensive support for antiviral agents, even though it is not the primary + scope of this package. Working with data containing information about antiviral drugs was never easier. + Use these functions to get valid properties of antiviral drugs from any input or to clean your input. + You can even retrieve drug names and doses from clinical text records, using `av_from_text()`. + contents: + - "`as.av`" + - "`av_property`" + - "`av_from_text`" - - title: "Background information on included data" + - title: "Other: background information on included data" desc: > Some pages about our package and its external sources. Be sure to read our [How To's](./../articles/index.html) for more information about how to work with functions in this package. diff --git a/data-raw/_pre_commit_hook.R b/data-raw/_pre_commit_hook.R index c133ab42..ef526409 100644 --- a/data-raw/_pre_commit_hook.R +++ b/data-raw/_pre_commit_hook.R @@ -267,17 +267,19 @@ AB_BETALACTAMS <- c(AB_PENICILLINS, AB_CEPHALOSPORINS, AB_CARBAPENEMS) # this will be used for documentation: DEFINED_AB_GROUPS <- ls(envir = globalenv()) DEFINED_AB_GROUPS <- DEFINED_AB_GROUPS[!DEFINED_AB_GROUPS %in% globalenv_before_ab] -create_AB_lookup <- function() { - AMR_env$AB_lookup <- AMR::antibiotics - AMR_env$AB_lookup$generalised_name <- generalise_antibiotic_name(AMR_env$AB_lookup$name) - AMR_env$AB_lookup$generalised_synonyms <- lapply(AMR_env$AB_lookup$synonyms, generalise_antibiotic_name) - AMR_env$AB_lookup$generalised_abbreviations <- lapply(AMR_env$AB_lookup$abbreviations, generalise_antibiotic_name) - AMR_env$AB_lookup$generalised_loinc <- lapply(AMR_env$AB_lookup$loinc, generalise_antibiotic_name) - AMR_env$AB_lookup$generalised_all <- unname(lapply( - as.list(as.data.frame(t(AMR_env$AB_lookup[, +create_AB_AV_lookup <- function(df) { + new_df <- df + new_df$generalised_name <- generalise_antibiotic_name(new_df$name) + new_df$generalised_synonyms <- lapply(new_df$synonyms, generalise_antibiotic_name) + if ("abbreviations" %in% colnames(df)) { + new_df$generalised_abbreviations <- lapply(new_df$abbreviations, generalise_antibiotic_name) + } + new_df$generalised_loinc <- lapply(new_df$loinc, generalise_antibiotic_name) + new_df$generalised_all <- unname(lapply( + as.list(as.data.frame(t(new_df[, c( - "ab", "atc", "cid", "name", - colnames(AMR_env$AB_lookup)[colnames(AMR_env$AB_lookup) %like% "generalised"] + colnames(new_df)[colnames(new_df) %in% c("ab", "av", "atc", "cid", "name")], + colnames(new_df)[colnames(new_df) %like% "generalised"] ), drop = FALSE ]), @@ -288,9 +290,10 @@ create_AB_lookup <- function() { x[x != ""] } )) - AMR_env$AB_lookup[, colnames(AMR_env$AB_lookup)[colnames(AMR_env$AB_lookup) %like% "^generalised"]] + new_df[, colnames(new_df)[colnames(new_df) %like% "^generalised"]] } -AB_LOOKUP <- create_AB_lookup() +AB_LOOKUP <- create_AB_AV_lookup(AMR::antibiotics) +AV_LOOKUP <- create_AB_AV_lookup(AMR::antivirals) # Export to package as internal data ---- usethis::ui_info(paste0("Updating internal package data")) @@ -304,6 +307,7 @@ suppressMessages(usethis::use_data(EUCAST_RULES_DF, MO_FULLNAME_LOWER, MO_PREVALENT_GENERA, AB_LOOKUP, + AV_LOOKUP, AB_AMINOGLYCOSIDES, AB_AMINOPENICILLINS, AB_ANTIFUNGALS, diff --git a/data-raw/antivirals.dta b/data-raw/antivirals.dta index 8e44a7a6..b13180d9 100644 Binary files a/data-raw/antivirals.dta and b/data-raw/antivirals.dta differ diff --git a/data-raw/antivirals.feather b/data-raw/antivirals.feather index edc82042..5191be79 100644 Binary files a/data-raw/antivirals.feather and b/data-raw/antivirals.feather differ diff --git a/data-raw/antivirals.parquet b/data-raw/antivirals.parquet index 026c3e69..c5669d72 100644 Binary files a/data-raw/antivirals.parquet and b/data-raw/antivirals.parquet differ diff --git a/data-raw/antivirals.rds b/data-raw/antivirals.rds index 179c296c..1f1fae1f 100644 Binary files a/data-raw/antivirals.rds and b/data-raw/antivirals.rds differ diff --git a/data-raw/antivirals.sas b/data-raw/antivirals.sas index 04b8e933..1fa696f3 100644 Binary files a/data-raw/antivirals.sas and b/data-raw/antivirals.sas differ diff --git a/data-raw/antivirals.sav b/data-raw/antivirals.sav index f77ec9cc..4100da48 100644 Binary files a/data-raw/antivirals.sav and b/data-raw/antivirals.sav differ diff --git a/data-raw/antivirals.txt b/data-raw/antivirals.txt index aa1bfeea..a0feedda 100644 --- a/data-raw/antivirals.txt +++ b/data-raw/antivirals.txt @@ -1,103 +1,121 @@ -"atc" "cid" "name" "atc_group" "synonyms" "oral_ddd" "oral_units" "iv_ddd" "iv_units" -"J05AF06" 441300 "Abacavir" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Abacavir,Abacavir sulfate,Ziagen" 0.6 "g" -"J05AB01" 135398513 "Aciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Acicloftal,Aciclovier,Aciclovir,Aciclovirum,Activir,AcycloFoam,Acycloguanosine,Acyclovir,Acyclovir Lauriad,ACYCLOVIR SODIUM,Avirax,Cargosil,Cyclovir,Genvir,Gerpevir,Hascovir,Herpevir,Maynar,Poviral,Sitavig,Sitavir,Vipral,Virolex,Viropump,Virorax,Zovirax,Zovirax topical,Zyclir" 4 "g" 4 "g" -"J05AF08" 60871 "Adefovir dipivoxil" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Adefovir di ester,Adefovir dipivoxil,Adefovir Dipivoxil,Adefovir dipivoxyl,Adefovir pivoxil,Adefovirdipivoxl,Bisadenine,BISADENINE,BisPMEA,Hepsera,Preveon,YouHeDing" 10 "mg" -"J05AE05" 65016 "Amprenavir" "Protease inhibitors" "Agenerase,Amprenavir,Amprenavirum,Prozei,Vertex" 1.2 "g" -"J05AP06" 16076883 "Asunaprevir" "Antivirals for treatment of HCV infections" "Asunaprevir,Sunvepra" -"J05AE08" 148192 "Atazanavir" "Protease inhibitors" "Atazanavir,Atazanavir Base,Latazanavir,Reyataz,Zrivada" 0.3 "g" -"J05AR15" 86583336 "Atazanavir and cobicistat" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR23" "Atazanavir and ritonavir" "Antivirals for treatment of HIV infections, combinations" "" 0.3 "g" -"J05AP03" 10324367 "Boceprevir" "Antivirals for treatment of HCV infections" "Bocepravir,Boceprevir,Victrelis" 2.4 "g" -"J05AB15" 446727 "Brivudine" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Bridic,Brivox,Brivudin,Brivudina,Brivudine,Brivudinum,BrVdUrd,Helpin,Zerpex,Zostex" 0.125 "g" -"J05AB12" 60613 "Cidofovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Cidofovir,Cidofovir anhydrous,Cidofovir gel,Cidofovirum,Forvade,Vistide" 25 "mg" -"J05AF12" 73115 "Clevudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Clevudine,Levovir,Revovir" 30 "mg" -"J05AP07" 25154714 "Daclatasvir" "Antivirals for treatment of HCV infections" "Daclatasvir,Daklinza" 60 "mg" -"J05AE10" 213039 "Darunavir" "Protease inhibitors" "Darunavir,Darunavirum,Prezista,Prezista Naive" 1.2 "g" -"J05AR14" "Darunavir and cobicistat" "Antivirals for treatment of HIV infections, combinations" "" -"J05AP09" 56640146 "Dasabuvir" "Antivirals for treatment of HCV infections" "Dasabuvir" 0.5 "g" -"J05AP52" "Dasabuvir, ombitasvir, paritaprevir and ritonavir" "Antivirals for treatment of HCV infections" "" -"J05AG02" 5625 "Delavirdine" "Non-nucleoside reverse transcriptase inhibitors" "BHAP der,Delavirdin,Delavirdina,Delavirdine,Delavirdinum,PIPERAZINE,Rescriptor" 1.2 "g" -"J05AF02" 135398739 "Didanosine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Didanosina,Didanosine,Didanosinum,Dideoxyinosine,DIDEOXYINOSINE,Hypoxanthine ddN,Videx,Videx EC" 0.4 "g" -"J05AX12" 54726191 "Dolutegravir" "Other antivirals" "Dolutegravir,Dolutegravir Sodium,Soltegravir,Tivicay" 50 "mg" -"J05AR21" 131801472 "Dolutegravir and rilpivirine" "Antivirals for treatment of HIV infections, combinations" "" -"J05AG06" 58460047 "Doravirine" "Non-nucleoside reverse transcriptase inhibitors" "Doravirine,Pifeltro" -"J05AG03" 64139 "Efavirenz" "Non-nucleoside reverse transcriptase inhibitors" "Efavirenz,Efavirenzum,Eravirenz,Stocrin,Strocin,Sustiva" 0.6 "g" -"J05AP54" 91669168 "Elbasvir and grazoprevir" "Antivirals for treatment of HCV infections" "" -"J05AX11" 5277135 "Elvitegravir" "Other antivirals" "Elvitegravir,Vitekta" -"J05AF09" 60877 "Emtricitabine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Coviracil,Emtricitabin,Emtricitabina,Emtricitabine,Emtricitabinum,Emtritabine,Emtriva,Racivir" 0.2 "g" -"J05AR17" 90469070 "Emtricitabine and tenofovir alafenamide" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR20" "Emtricitabine, tenofovir alafenamide and bictegravir" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR19" "Emtricitabine, tenofovir alafenamide and rilpivirine" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR22" "Emtricitabine, tenofovir alafenamide, darunavir and cobicistat" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR18" "Emtricitabine, tenofovir alafenamide, elvitegravir and cobicistat" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR06" "Emtricitabine, tenofovir disoproxil and efavirenz" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR08" "Emtricitabine, tenofovir disoproxil and rilpivirine" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR09" "Emtricitabine, tenofovir disoproxil, elvitegravir and cobicistat" "Antivirals for treatment of HIV infections, combinations" "" -"J05AX07" 16130199 "Enfuvirtide" "Other antivirals" "Enfurvitide,Enfuvirtide,Fuzeon,Pentafuside" 0.18 "g" -"J05AX17" 10089466 "Enisamium iodide" "Other antivirals" "Enisamium iodide" 1.5 "g" -"J05AF10" 135398508 "Entecavir" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Baraclude,Entecavir,Entecavir anhydrous,Entecavirum" 0.5 "mg" -"J05AG04" 193962 "Etravirine" "Non-nucleoside reverse transcriptase inhibitors" "DAPY deriv,Etravine,Etravirine,Intelence" 0.4 "g" -"J05AP04" 42601552 "Faldaprevir" "Antivirals for treatment of HCV infections" "Faldaprevir" -"J05AB09" 3324 "Famciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Famciclovir,Famciclovirum,Famvir,Oravir" 0.75 "g" -"J05AE07" 131536 "Fosamprenavir" "Protease inhibitors" "Amprenavir phosphate,Fosamprenavir,Lexiva,Telzir" 1.4 "g" -"J05AD01" 3415 "Foscarnet" "Phosphonic acid derivatives" "Forscarnet,Forscarnet sodium,Foscarmet,Foscarnet,Phosphonoformate,Phosphonoformic acid" 6.5 "g" -"J05AD02" 546 "Fosfonet" "Phosphonic acid derivatives" "Fosfonet,Fosfonet sodium,Fosfonet Sodium,Fosfonoacetate,Fosfonoacetic acid,Phosphonacetate,Phosphonacetic acid" -"J05AB06" 135398740 "Ganciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Citovirax,Cymevan,Cymeven,Cymevene,Cytovene,Cytovene IV,Ganciclovir,Ganciclovirum,Gancyclovir,Hydroxyacyclovir,Virgan,Vitrasert,Zirgan" 3 "g" 0.5 "g" -"J05AP57" "Glecaprevir and pibrentasvir" "Antivirals for treatment of HCV infections" "" -"J05AX23" "Ibalizumab" "Other antivirals" "" -"J05AB02" 5905 "Idoxuridine" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Antizona,Dendrid,Emanil,Heratil,Herpesil,Herpid,Herpidu,Herplex,HERPLEX,Herplex liquifilm,Idexur,Idossuridina,Idoxene,Idoxuridin,Idoxuridina,Idoxuridine,Idoxuridinum,Idu Oculos,Iducher,Idulea,Iduoculos,Iduridin,Iduviran,Iododeoxyridine,Iododeoxyuridine,Iodoxuridine,Joddeoxiuridin,Kerecid,Kerecide,Ophthalmadine,Spectanefran,Stoxil,Synmiol,Virudox" -"J05AE02" 5362440 "Indinavir" "Protease inhibitors" "Compound J,Crixivan,Indinavir,Indinavir anhydrous,Propolis+Indinavir" 2.4 "g" -"J05AX05" 135449284 "Inosine pranobex" "Other antivirals" "Aviral,Delimmun,Immunovir,Imunovir,Inosine pranobex,Inosiplex,Isoprinosin,Isoprinosina,Isoprinosine,Isoviral,Methisoprinol,Methysoprinol,Metisoprinol,Viruxan" 3 "g" -"J05AF05" 60825 "Lamivudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Epivir,Hepitec,Heptivir,Heptodin,Heptovir,Lamivir,Lamivudin,Lamivudina,Lamivudine,Lamivudinum,Zeffix" 0.3 "g" -"J05AR02" "Lamivudine and abacavir" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR16" 73386700 "Lamivudine and raltegravir" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR12" "Lamivudine and tenofovir disoproxil" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR13" "Lamivudine, abacavir and dolutegravir" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR24" "Lamivudine, tenofovir disoproxil and doravirine" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR11" "Lamivudine, tenofovir disoproxil and efavirenz" "Antivirals for treatment of HIV infections, combinations" "" -"J05AX18" 45138674 "Letermovir" "Other antivirals" "Letermovir,Prevymis" 0.48 "g" 0.48 "g" -"J05AR10" 11979606 "Lopinavir and ritonavir" "Antivirals for treatment of HIV infections, combinations" "Aluvia,Kaletra" 0.8 "g" -"J05AX02" 24839946 "Lysozyme" "Other antivirals" "Lysozyme chloride,Lysozyme Chloride,Lysozyme G" -"J05AX09" 3002977 "Maraviroc" "Other antivirals" "Celsentri,Maraviroc,Selzentry" 0.6 "g" -"J05AX10" 471161 "Maribavir" "Other antivirals" "Benzimidavir,Camvia,Maribavir" -"J05AA01" 667492 "Metisazone" "Thiosemicarbazones" "Kemoviran,Marboran,Marborane,Methisazon,Methisazone,Methsazone,Metisazon,Metisazona,Metisazone,Metisazonum,Viruzona" -"J05AX01" 71655 "Moroxydine" "Other antivirals" "Bimolin,Flumidine,Influmine,Moroxidina,Moroxydine,Moroxydinum,Vironil,Virugon,Virumin,Wirumin" 0.3 "g" -"J05AE04" 64143 "Nelfinavir" "Protease inhibitors" "Nelfinavir,Viracept" 2.25 "g" -"J05AG01" 4463 "Nevirapine" "Non-nucleoside reverse transcriptase inhibitors" "Nevirapine,Nevirapine anhydrous,Viramune,Viramune IR,Viramune XR" 0.4 "g" -"J05AP53" "Ombitasvir, paritaprevir and ritonavir" "Antivirals for treatment of HCV infections" "" -"J05AH02" 65028 "Oseltamivir" "Neuraminidase inhibitors" "Agucort,Oseltamivir,Tamiflu,Tamvir" 0.15 "g" -"J05AB13" 135398748 "Penciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Adenovir,Denavir,Penciceovir,Penciclovir,Penciclovirum,Pencyclovir,Vectavir" -"J05AX21" 9942657 "Pentanedioic acid imidazolyl ethanamide" "Other antivirals" "Ingamine" 90 "mg" -"J05AH03" 154234 "Peramivir" "Neuraminidase inhibitors" "PeramiFlu,Peramivir,Rapiacta,RAPIVAB" -"J05AX06" 1684 "Pleconaril" "Other antivirals" "Picovir,Pleconaril,Pleconarilis" -"J05AX08" 54671008 "Raltegravir" "Other antivirals" "Isentress,Raltegravir" 0.8 "g" -"J05AP01" 37542 "Ribavirin" "Antivirals for treatment of HCV infections" "Copegus,Cotronak,Drug: Ribavirin,Ravanex,Rebetol,Rebetron,Rebretron,Ribacine,Ribamide,Ribamidil,Ribamidyl,Ribasphere,Ribavirin,Ribavirin Capsules,Ribavirina,Ribavirine,Ribavirinum,Ribovirin,Tribavirin,Varazid,Vilona,Viramid,Viramide,Virazid,Virazide,Virazole" 1 "g" -"J05AG05" 6451164 "Rilpivirine" "Non-nucleoside reverse transcriptase inhibitors" "Edurant,Rilpivirine" 25 "mg" -"J05AC02" 5071 "Rimantadine" "Cyclic amines" "Remantadine,Riamantadine,Rimant,RIMANTADIN,Rimantadin A,Rimantadina,Rimantadine,Rimantadinum" 0.2 "g" -"J05AE03" 392622 "Ritonavir" "Protease inhibitors" "Norvir,Norvir Sec,Norvir Softgel,Ritonavir,Ritonavire,Ritonavirum" 1.2 "g" -"J05AE01" 441243 "Saquinavir" "Protease inhibitors" "Fortovase,Invirase,Saquinavir" 1.8 "g" -"J05AP05" 24873435 "Simeprevir" "Antivirals for treatment of HCV infections" "Olysio,Simeprevir sodium" 0.15 "g" -"J05AP08" 45375808 "Sofosbuvir" "Antivirals for treatment of HCV infections" "Hepcinat,Hepcvir,Sofosbuvir,Sovaldi,SOVALDI,SoviHep" 0.4 "g" -"J05AP51" 72734365 "Sofosbuvir and ledipasvir" "Antivirals for treatment of HCV infections" "" -"J05AP55" 91885554 "Sofosbuvir and velpatasvir" "Antivirals for treatment of HCV infections" "Epclusa Tablet" -"J05AP56" "Sofosbuvir, velpatasvir and voxilaprevir" "Antivirals for treatment of HCV infections" "" -"J05AF04" 18283 "Stavudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Estavudina,Sanilvudine,Stavudin,Stavudine,Stavudinum,Zerit Xr,Zerut XR" 80 "mg" -"J05AR07" 15979285 "Stavudine, lamivudine and nevirapine" "Antivirals for treatment of HIV infections, combinations" "STAVUDIINE" -"J05AP02" 3010818 "Telaprevir" "Antivirals for treatment of HCV infections" "Incivek,Incivo,Telaprevir,Telavic" 2.25 "g" -"J05AF11" 159269 "Telbivudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Epavudine,Sebivo,Telbivudin,Telbivudine,Tyzeka" 0.6 "g" -"J05AF13" 9574768 "Tenofovir alafenamide" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Vemlidy" 25 "mg" -"J05AF07" 5481350 "Tenofovir disoproxil" "Nucleoside and nucleotide reverse transcriptase inhibitors" "BisPMPA,PMPA prodrug,Tenofovir,Viread" 0.245 "g" -"J05AR03" "Tenofovir disoproxil and emtricitabine" "Antivirals for treatment of HIV infections, combinations" "" -"J05AX19" 5475 "Tilorone" "Other antivirals" "Amiksin,Amixin,Amixin IC,Amyxin,Tiloron,Tilorona,Tilorone,Tiloronum" 0.125 "g" -"J05AE09" 54682461 "Tipranavir" "Protease inhibitors" "Aptivus,Tipranavir" 1 "g" -"J05AC03" 64377 "Tromantadine" "Cyclic amines" "Tromantadina,Tromantadine,Tromantadinum,Viruserol" -"J05AX13" 131411 "Umifenovir" "Other antivirals" "Arbidol,Arbidol base,Umifenovir" 0.8 "g" -"J05AB11" 135398742 "Valaciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Talavir,Valaciclovir,Valaciclovirum,ValACV,Valcivir,Valcyclovir,Valtrex,Virval,Zelitrex" 3 "g" -"J05AB14" 135413535 "Valganciclovir" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Cymeval,Valganciclovir" 0.9 "g" -"J05AB03" 21704 "Vidarabine" "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "Adenine arabinoside,Araadenosine,Arabinoside adenine,Arabinosyl adenine,Arabinosyladenine,Spongoadenosine,Vidarabin,Vidarabina,Vidarabine,Vidarabine anhydrous,Vidarabinum,Vira A,Vira ATM" -"J05AF03" 24066 "Zalcitabine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Dideoxycytidine,Interferon AD + ddC,Zalcitabine,Zalcitibine" 2.25 "mg" -"J05AH01" 60855 "Zanamivir" "Neuraminidase inhibitors" "MODIFIED SIALIC ACID,Relenza,Zanamavir,Zanamir,Zanamivi,Zanamivir,Zanamivir hydrate" -"J05AF01" 35370 "Zidovudine" "Nucleoside and nucleotide reverse transcriptase inhibitors" "Azidothymidine,AZT Antiviral,Beta interferon,Compound S,Propolis+AZT,Retrovir,Zidovudina,Zidovudine,ZIDOVUDINE,Zidovudine EP III,Zidovudinum" 0.6 "g" 0.6 "g" -"J05AR01" "Zidovudine and lamivudine" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR04" "Zidovudine, lamivudine and abacavir" "Antivirals for treatment of HIV infections, combinations" "" -"J05AR05" "Zidovudine, lamivudine and nevirapine" "Antivirals for treatment of HIV infections, combinations" "" +"av" "name" "atc" "cid" "atc_group" "synonyms" "oral_ddd" "oral_units" "iv_ddd" "iv_units" "loinc" +"ABA" "Abacavir" "J05AF06" 441300 "Nucleoside and nucleotide reverse transcriptase inhibitors" "abacavir sulfate,avacavir,ziagen" 0.6 "g" "29113-8,78772-1,78773-9,79134-3,80118-3" +"ACI" "Aciclovir" "J05AB01" 135398513 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "acicloftal,aciclovier,aciclovirum,activir,acyclofoam,acycloguanosine,acyclovir,acyclovir lauriad,avaclyr,cargosil,cyclovir,genvir,gerpevir,hascovir,maynar,novirus,poviral,sitavig,sitavir,vipral,viropump,virorax,zovirax,zyclir" 4 "g" 4 "g" "" +"ADD" "Adefovir dipivoxil" "J05AF08" 60871 "Nucleoside and nucleotide reverse transcriptase inhibitors" "adefovir di,adefovir di ester,adefovir dipivoxyl,adefovir pivoxil,adefovirdipivoxl,bisadenine,bispmea,hepsera,preveon,youheding" 10 "mg" "" +"AME" "Amenamevir" "J05AX26" 11397521 "Other antivirals" "amenalief" 0.4 "g" "" +"AMP" "Amprenavir" "J05AE05" 65016 "Protease inhibitors" "agenerase,carbamate,prozei" 1.2 "g" "29114-6,31028-4,78791-1" +"ASU" "Asunaprevir" "J05AP06" 16076883 "Antivirals for treatment of HCV infections" "sunvepra,sunvepratrade" 0.2 "g" "" +"ATA" "Atazanavir" "J05AE08" 148192 "Protease inhibitors" "atazanavir base,latazanavir,reyataz,zrivada" 0.3 "g" "41470-6,78796-0,78797-8,80142-3,80143-1" +"ATA+COBI" "Atazanavir/cobicistat" "J05AR15" 86583336 "Antivirals for treatment of HIV infections, combinations" "" "" +"ATA+RIT" "Atazanavir/ritonavir" "J05AR23" 25134325 "Antivirals for treatment of HIV infections, combinations" "" 0.3 "g" "" +"BAM" "Baloxavir marboxil" "J05AX25" 124081896 "Other antivirals" "xofluza" 40 "mg" "" +"BOC" "Boceprevir" "J05AP03" 10324367 "Antivirals for treatment of HCV infections" "victrelis" 2.4 "g" "" +"BRIN" "Brincidofovir" "J05AB17" 483477 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "cidofovir prodrug,tembexa" "" +"BRIV" "Brivudine" "J05AB15" 446727 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "bridic,brivox,brivudin,brivudina,brivudinum,brvdurd,helpin,zerpex,zostex" 0.125 "g" "" +"BUL" "Bulevirtide" "J05AX28" "Other antivirals" "" "" +"CAB" "Cabotegravir" "J05AJ04" 54713659 "Integrase inhibitors" "cabenuva" 30 "mg" 10 "mg" "" +"CID" "Cidofovir" "J05AB12" 60613 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "cidofovir anhydrous,cidofovir gel,cidofovir hydrate,cidofovirum,forvade,hpmpc dihydrate,phosphonic acid,vistide" 25 "mg" "" +"CLE" "Clevudine" "J05AF12" 73115 "Nucleoside and nucleotide reverse transcriptase inhibitors" "levovir,revovir" 30 "mg" "" +"COBL" "Coblopasvir" "J05AP12" 58316387 "Antivirals for treatment of HCV infections" "" "" +"DAC" "Daclatasvir" "J05AP07" 25154714 "Antivirals for treatment of HCV infections" "daklinza" 60 "mg" "" +"DAC+ASU+BEC" "Daclatasvir/asunaprevir/beclabuvir" "J05AP58" "Antivirals for treatment of HCV infections" "" "" +"DAR" "Darunavir" "J05AE10" 213039 "Protease inhibitors" "carbamate,darunavirum,derunavir,prezista,prezista naive" 1.2 "g" "57954-0" +"DAR+COBI" "Darunavir/cobicistat" "J05AR14" 57327017 "Antivirals for treatment of HIV infections, combinations" "" "" +"DAR+RIT" "Darunavir/ritonavir" "J05AR26" "Antivirals for treatment of HIV infections, combinations" "" "" +"DAS" "Dasabuvir" "J05AP09" 56640146 "Antivirals for treatment of HCV infections" "" 0.5 "g" "" +"DAS+OMB+PAR+RIT" "Dasabuvir/ombitasvir/paritaprevir/ritonavir" "J05AP52" "Antivirals for treatment of HCV infections" "" "" +"DEL" "Delavirdine" "J05AG02" 5625 "Non-nucleoside reverse transcriptase inhibitors" "piperazine,rescriptor" 1.2 "g" "27082-7,29115-3" +"DID" "Didanosine" "J05AF02" 135398739 "Nucleoside and nucleotide reverse transcriptase inhibitors" "didanosina,didanosinum,dideoxyinosine,hypoxanthine ddn,videx ec" 0.4 "g" "29116-1,48307-3" +"DOL" "Dolutegravir" "J05AJ03" 54726191 "Integrase inhibitors" "dolutegravir dtg,soltegravir,tivicay" 50 "mg" "" +"DOL+RIL" "Dolutegravir/rilpivirine" "J05AR21" 131801472 "Antivirals for treatment of HIV infections, combinations" "" "" +"DOR" "Doravirine" "J05AG06" 58460047 "Non-nucleoside reverse transcriptase inhibitors" "pifeltro" 0.1 "g" "" +"EFA" "Efavirenz" "J05AG03" 64139 "Non-nucleoside reverse transcriptase inhibitors" "efavirenz teva,efavirenzum,eravirenz,stocrin,strocin,sustiva,viraday" 0.6 "g" "29117-9,33928-3,51907-4,51908-2" +"ELB" "Elbasvir" "J05AP10" 71661251 "Antivirals for treatment of HCV infections" "methyl carbamate" 50 "mg" "" +"ELB+GRA" "Elbasvir/grazoprevir" "J05AP54" 91669168 "Antivirals for treatment of HCV infections" "zepatier" "" +"ELV" "Elvitegravir" "J05AJ02" 5277135 "Integrase inhibitors" "vitekta" "88986-5" +"EMT" "Emtricitabine" "J05AF09" 60877 "Nucleoside and nucleotide reverse transcriptase inhibitors" "coviracil,emtricitabinum,emtritabine,emtriva,racivir" 0.2 "g" "" +"EMT+TEA" "Emtricitabine/tenofovir alafenamide" "J05AR17" 90469070 "Antivirals for treatment of HIV infections, combinations" "descovy" "" +"EMT+TEA+BIC" "Emtricitabine/tenofovir alafenamide/bictegravir" "J05AR20" "Antivirals for treatment of HIV infections, combinations" "" "" +"EMT+TEA+RIL" "Emtricitabine/tenofovir alafenamide/rilpivirine" "J05AR19" "Antivirals for treatment of HIV infections, combinations" "" "" +"EMT+TEA+DAR+COBI" "Emtricitabine/tenofovir alafenamide/darunavir/cobicistat" "J05AR22" "Antivirals for treatment of HIV infections, combinations" "" "" +"EMT+TEA+ELV+COBI" "Emtricitabine/tenofovir alafenamide/elvitegravir/cobicistat" "J05AR18" "Antivirals for treatment of HIV infections, combinations" "" "" +"EMT+TED+EFA" "Emtricitabine/tenofovir disoproxil/efavirenz" "J05AR06" "Antivirals for treatment of HIV infections, combinations" "" "" +"EMT+TED+RIL" "Emtricitabine/tenofovir disoproxil/rilpivirine" "J05AR08" "Antivirals for treatment of HIV infections, combinations" "" "" +"EMT+TED+ELV+COBI" "Emtricitabine/tenofovir disoproxil/elvitegravir/cobicistat" "J05AR09" "Antivirals for treatment of HIV infections, combinations" "" "" +"ENF" "Enfuvirtide" "J05AX07" 16130199 "Other antivirals" "enfurvitide,fuzeon,pentafuside" 0.18 "g" "" +"ENI" "Enisamium iodide" "J05AX17" 10089466 "Other antivirals" "amizon" 1.5 "g" "" +"ENT" "Entecavir" "J05AF10" 135398508 "Nucleoside and nucleotide reverse transcriptase inhibitors" "baraclude,entecavir anhydrous" 0.5 "mg" "" +"ETR" "Etravirine" "J05AG04" 193962 "Non-nucleoside reverse transcriptase inhibitors" "dapy deriv,etravine,intelence" 0.4 "g" "57961-5" +"FAL" "Faldaprevir" "J05AP04" 42601552 "Antivirals for treatment of HCV infections" "" "" +"FAM" "Famciclovir" "J05AB09" 3324 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "famciclovirum,famvir,oravir" 0.75 "g" "" +"FAV" "Favipiravir" "J05AX27" 492405 "Other antivirals" "avigan,fapilavir,favilavir" 1.6 "g" "" +"FOSA" "Fosamprenavir" "J05AE07" 131536 "Protease inhibitors" "amprenavir phosphate,carbamate,lexiva,telzir" 1.4 "g" "" +"FOSC" "Foscarnet" "J05AD01" 3415 "Phosphonic acid derivatives" "forscarnet,foscarmet,foscavir,phosphonoformate,phosphonoformic acid" 6.5 "g" "" +"FOSF" "Fosfonet" "J05AD02" 546 "Phosphonic acid derivatives" "fosfonet sodium,fosfonoacetate,fosfonoacetic acid,phosphonacetate,phosphonacetic acid,phosphonoaceticacid" "" +"FOST" "Fostemsavir" "J05AX29" 11319217 "Other antivirals" "rukobia" 1.2 "g" "" +"GAN" "Ganciclovir" "J05AB06" 135398740 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "citovirax,cymevan,cymeven,cymevene,cytovene,ganciclovirum,gancyclovir,hydroxyacyclovir,virgan,vitrasert,zirgan" 3 "g" 0.5 "g" "15367-6,25256-9,59798-9,59799-7,60077-5,60078-3" +"GLE+PIB" "Glecaprevir/pibrentasvir" "J05AP57" 85471918 "Antivirals for treatment of HCV infections" "" "" +"GRA" "Grazoprevir" "J05AP11" 44603531 "Antivirals for treatment of HCV infections" "" 0.1 "g" "" +"IBA" "Ibalizumab" "J05AX23" "Other antivirals" "" "" +"IDO" "Idoxuridine" "J05AB02" 5905 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "antizona,dendrid,heratil,herplex,idossuridina,idoxene,idoxuridin,idoxuridina,idoxuridinum,iduoculos,iduridin,iododeoxyridine,iododeoxyuridine,iodoxuridine,joddeoxiuridin,kerecid,stoxil,virudox" "" +"IND" "Indinavir" "J05AE02" 5362440 "Protease inhibitors" "compound j,crixivan,indinavir anhydrous,propolis+indinavir" 2.4 "g" "29118-7,31033-4,51918-1" +"INP" "Inosine pranobex" "J05AX05" 135449284 "Other antivirals" "aviral,delimmun,groprinosin,immunovir,imunovir,imunoviral,inosiplex,isoprinosin,isoprinosina,isoprinosine,isoviral,methisoprinol,modimmunal,pranosina,pranosine,viruxan" 3 "g" "" +"LAM" "Lamivudine" "J05AF05" 60825 "Nucleoside and nucleotide reverse transcriptase inhibitors" "epivir,hepitec,heptivir,heptodin,heptovir,lamivir,lamivudeine,lamivudine teva,lamivudinum,virolam,zeffix" 0.3 "g" "29119-5,49226-4" +"LAM+ABA" "Lamivudine/abacavir" "J05AR02" "Antivirals for treatment of HIV infections, combinations" "" "" +"LAM+DOL" "Lamivudine/dolutegravir" "J05AR25" "Antivirals for treatment of HIV infections, combinations" "" "" +"LAM+RAL" "Lamivudine/raltegravir" "J05AR16" 73386700 "Antivirals for treatment of HIV infections, combinations" "" "" +"LAM+TED" "Lamivudine/tenofovir disoproxil" "J05AR12" "Antivirals for treatment of HIV infections, combinations" "" "" +"LAM+ABA+DOL" "Lamivudine/abacavir/dolutegravir" "J05AR13" "Antivirals for treatment of HIV infections, combinations" "" "" +"LAM+TED+DOL" "Lamivudine/tenofovir disoproxil/dolutegravir" "J05AR27" "Antivirals for treatment of HIV infections, combinations" "" "" +"LAM+TED+DOR" "Lamivudine/tenofovir disoproxil/doravirine" "J05AR24" "Antivirals for treatment of HIV infections, combinations" "" "" +"LAM+TED+EFA" "Lamivudine/tenofovir disoproxil/efavirenz" "J05AR11" "Antivirals for treatment of HIV infections, combinations" "" "" +"LAN" "Laninamivir" "J05AH04" 502272 "Neuraminidase inhibitors" "" "" +"LEN" "Lenacapavir" "J05AX31" 133082658 "Other antivirals" "" "" +"LET" "Letermovir" "J05AX18" 45138674 "Other antivirals" "acetic acid,prevymis" 0.48 "g" 0.48 "g" "" +"LOP+RIT" "Lopinavir/ritonavir" "J05AR10" 11979606 "Antivirals for treatment of HIV infections, combinations" "aluvia,kaletra,lopimune" 0.8 "g" "" +"LYS" "Lysozyme" "J05AX02" 16130991 "Other antivirals" "" "" +"MARA" "Maraviroc" "J05AX09" 3002977 "Other antivirals" "celsentri,selzentry" 0.6 "g" "88987-3" +"MARI" "Maribavir" "J05AX10" 471161 "Other antivirals" "benzimidavir,camvia" "" +"MET" "Metisazone" "J05AA01" 667492 "Thiosemicarbazones" "kemoviran,marboran,marborane,methisazon,methisazone,methsazone,metisazon,metisazona,metisazonum,viruzona" "" +"MOR" "Moroxydine" "J05AX01" 71655 "Other antivirals" "bimolin,moroxidina,moroxydinum,virugon,virumin,wirumin" 0.3 "g" "" +"NEL" "Nelfinavir" "J05AE04" 64143 "Protease inhibitors" "viracept" 2.25 "g" "29120-3,32647-0,35113-0,51923-1" +"NEV" "Nevirapine" "J05AG01" 4463 "Non-nucleoside reverse transcriptase inhibitors" "nevirapine anhydrous,nevirapine teva,nevirapine),viramune,viramune ir,viramune xr" 0.4 "g" "29121-1,32646-2,51925-6" +"OMB+PAR+RIT" "Ombitasvir/paritaprevir/ritonavir" "J05AP53" "Antivirals for treatment of HCV infections" "" "" +"OSE" "Oseltamivir" "J05AH02" 65028 "Neuraminidase inhibitors" "agucort,tamiflu,tamvir" 0.15 "g" "" +"PEN" "Penciclovir" "J05AB13" 135398748 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "adenovir,denavir,penciceovir,penciclovirum,pencyclovir,vectavir" "60140-1,60141-9" +"PAIE" "Pentanedioic acid imidazolyl ethanamide" "J05AX21" 9942657 "Other antivirals" "ingamine" 90 "mg" "" +"PER" "Peramivir" "J05AH03" 154234 "Neuraminidase inhibitors" "peramiflu,peramivir anhydrous,rapiacta,rapivab" 0.6 "g" "" +"PLE" "Pleconaril" "J05AX06" 1684 "Other antivirals" "picovir,pleconarilis" "" +"RAL" "Raltegravir" "J05AJ01" 54671008 "Integrase inhibitors" "isentress" 0.8 "g" "72835-2" +"REM" "Remdesivir" "J05AB16" 121304016 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "veklury" 0.1 "g" "" +"RIB" "Ribavirin" "J05AP01" 37542 "Antivirals for treatment of HCV infections" "copegus,cotronak,ravanex,rebetol,rebetron,rebretron,ribacine,ribamide,ribamidil,ribamidyl,ribasphere,ribavirin capsules,ribavirin mylan,ribavirin teva,ribavirina,ribavirine,ribavirinum,tribavirin,varazid,vilona,viramid,virazid,virazide,virazole" 1 "g" "41469-8" +"RIL" "Rilpivirine" "J05AG05" 6451164 "Non-nucleoside reverse transcriptase inhibitors" "edurant,rilpivirina" 25 "mg" 15 "mg" "80547-3" +"RIM" "Rimantadine" "J05AC02" 5071 "Cyclic amines" "ethanamine,rimant,rimantadin,rimantadin a,rimantadina,rimantadinum" 0.2 "g" "" +"RIT" "Ritonavir" "J05AE03" 392622 "Protease inhibitors" "empetus,norvir,norvir softgel,ritomune,ritonavirum,ritovir,viekirax,viriton" 1.2 "g" "29122-9,31027-6,51929-8,51930-6" +"SAQ" "Saquinavir" "J05AE01" 441243 "Protease inhibitors" "fortovase,invirase,saquinavirum" 1.8 "g" "19051-2,29123-7,51932-2" +"SIM" "Simeprevir" "J05AP05" 24873435 "Antivirals for treatment of HCV infections" "olysio,simeprevir sodium" 0.15 "g" "" +"SOF" "Sofosbuvir" "J05AP08" 45375808 "Antivirals for treatment of HCV infections" "hepcinat,hepcvir,sovaldi,sovihep" 0.4 "g" "" +"SOF+LED" "Sofosbuvir/ledipasvir" "J05AP51" 72734365 "Antivirals for treatment of HCV infections" "harvoni" "" +"SOF+VEL" "Sofosbuvir/velpatasvir" "J05AP55" 91885554 "Antivirals for treatment of HCV infections" "epclusa,epclusa tablet" "" +"SOF+VEL+VOX" "Sofosbuvir/velpatasvir/voxilaprevir" "J05AP56" "Antivirals for treatment of HCV infections" "" "" +"STA" "Stavudine" "J05AF04" 18283 "Nucleoside and nucleotide reverse transcriptase inhibitors" "estavudina,sanilvudine,stavudinum,zerit xr,zerut xr" 80 "mg" "29124-5,49227-2" +"STA+LAM+NEV" "Stavudine/lamivudine/nevirapine" "J05AR07" 15979285 "Antivirals for treatment of HIV infections, combinations" "" "" +"TEC" "Tecovirimat" "J05AX24" 16124688 "Other antivirals" "" "" +"TELA" "Telaprevir" "J05AP02" 3010818 "Antivirals for treatment of HCV infections" "incivek,incivo,telavic" 2.25 "g" "" +"TELB" "Telbivudine" "J05AF11" 159269 "Nucleoside and nucleotide reverse transcriptase inhibitors" "epavudine,sebivo,telbivudin,tyzeka" 0.6 "g" "" +"TEA" "Tenofovir alafenamide" "J05AF13" 9574768 "Nucleoside and nucleotide reverse transcriptase inhibitors" "vemlidy" 25 "mg" "" +"TED" "Tenofovir disoproxil" "J05AF07" 5481350 "Nucleoside and nucleotide reverse transcriptase inhibitors" "bispmpa,pmpa prodrug,tenofovir,tenofovir bis,tenofovirdisoproxil,viread" 0.245 "g" "" +"TED+EMT" "Tenofovir disoproxil/emtricitabine" "J05AR03" "Antivirals for treatment of HIV infections, combinations" "" "" +"TIL" "Tilorone" "J05AX19" 5475 "Other antivirals" "amixin ic,tiloron,tilorona,tiloronum" 0.125 "g" "" +"TIP" "Tipranavir" "J05AE09" 54682461 "Protease inhibitors" "aptivus" 1 "g" "57383-2" +"TRO" "Tromantadine" "J05AC03" 64377 "Cyclic amines" "tromantadina,tromantadinum" "" +"UMI" "Umifenovir" "J05AX13" 131411 "Other antivirals" "arbidol,arbidol base" 0.8 "g" "" +"VALA" "Valaciclovir" "J05AB11" 135398742 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "talavir,valacv,valacyclovir,valcivir,valcyclovir,valtrex,virval,zelitrex" 3 "g" "" +"VALG" "Valganciclovir" "J05AB14" 135413535 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "cymeval" 0.9 "g" "74960-6" +"VID" "Vidarabine" "J05AB03" 21704 "Nucleosides and nucleotides excl. reverse transcriptase inhibitors" "adenine arabinoside,araadenosine,arabinoside adenine,arabinosyl adenine,arabinosyladenine,spongoadenosine,vidarabin,vidarabina,vidarabine anhydrous,vidarabinum,vira a,vira atm" 0.7 "g" "" +"ZAL" "Zalcitabine" "J05AF03" 24066 "Nucleoside and nucleotide reverse transcriptase inhibitors" "dideoxycytidine,interferon ad + ddc,zalcitibine" 2.25 "mg" "29125-2" +"ZAN" "Zanamivir" "J05AH01" 60855 "Neuraminidase inhibitors" "modified sialic acid,relenza,zanamavir,zanamivi,zanamivirhydrate" 1.2 "g" "" +"ZID" "Zidovudine" "J05AF01" 35370 "Nucleoside and nucleotide reverse transcriptase inhibitors" "azidothymidine,beta interferon,compound s,propolis+azt,retrovir,trizivir,zidovudina,zidovudinum" 0.6 "g" 0.6 "g" "29126-0,6894-0" +"ZID+LAM" "Zidovudine/lamivudine" "J05AR01" "Antivirals for treatment of HIV infections, combinations" "" "" +"ZID+LAM+ABA" "Zidovudine/lamivudine/abacavir" "J05AR04" "Antivirals for treatment of HIV infections, combinations" "" "" +"ZID+LAM+NEV" "Zidovudine/lamivudine/nevirapine" "J05AR05" "Antivirals for treatment of HIV infections, combinations" "" "" diff --git a/data-raw/antivirals.xlsx b/data-raw/antivirals.xlsx index 99b1022f..0efccba8 100644 Binary files a/data-raw/antivirals.xlsx and b/data-raw/antivirals.xlsx differ diff --git a/data-raw/av.md5 b/data-raw/av.md5 index 123d2e6d..78189fc9 100644 --- a/data-raw/av.md5 +++ b/data-raw/av.md5 @@ -1 +1 @@ -246da79545e045edac7c3ec445b3a04e +009fea3738cdb6390dccd470cb27f015 diff --git a/data-raw/loinc.R b/data-raw/loinc.R index d46719df..28d4b095 100644 --- a/data-raw/loinc.R +++ b/data-raw/loinc.R @@ -62,7 +62,7 @@ for (i in seq_len(nrow(antibiotics))) { # sort and fix for empty values for (i in 1:nrow(antibiotics)) { loinc <- as.character(sort(unique(tolower(antibiotics[i, "loinc"][[1]])))) - antibiotics[i, "loinc"][[1]] <- ifelse(length(syn[!syn == ""]) == 0, list(""), list(loinc)) + antibiotics[i, "loinc"][[1]] <- ifelse(length(loinc[!loinc == ""]) == 0, list(""), list(loinc)) } # remember to update R/aa_globals.R for the documentation diff --git a/data-raw/reproduction_of_antibiotics.R b/data-raw/reproduction_of_antibiotics.R index da78cd8c..d7ac718d 100644 --- a/data-raw/reproduction_of_antibiotics.R +++ b/data-raw/reproduction_of_antibiotics.R @@ -192,7 +192,7 @@ abx2$abbr <- lapply(as.list(abx2$abbr), function(x) unlist(strsplit(x, "|", fixe # vector with official names, returns vector with CIDs get_CID <- function(ab) { CID <- rep(NA_integer_, length(ab)) - p <- progress_ticker(n = length(ab), min_time = 0) + p <- AMR:::progress_ticker(n = length(ab), min_time = 0) for (i in 1:length(ab)) { p$tick() @@ -248,7 +248,7 @@ antibiotics[is.na(CIDs), ] %>% View() # returns list with synonyms (brand names), with CIDs as names get_synonyms <- function(CID, clean = TRUE) { synonyms <- rep(NA_character_, length(CID)) - p <- progress_ticker(n = length(CID), min_time = 0) + p <- AMR:::progress_ticker(n = length(CID), min_time = 0) for (i in 1:length(CID)) { p$tick() diff --git a/data-raw/reproduction_of_antivirals.R b/data-raw/reproduction_of_antivirals.R index ff6bfc57..6659e431 100644 --- a/data-raw/reproduction_of_antivirals.R +++ b/data-raw/reproduction_of_antivirals.R @@ -27,14 +27,18 @@ # how to conduct AMR data analysis: https://msberends.github.io/AMR/ # # ==================================================================== # -# get all data from the WHOCC website +library(dplyr) +library(tidyr) +library(rvest) +# get all data from the WHOCC website get_atc_table <- function(atc_group) { # give as input J0XXX, like atc_group = "J05AB" downloaded <- read_html(paste0("https://www.whocc.no/atc_ddd_index/?code=", atc_group, "&showdescription=no")) table_title <- downloaded %>% - html_nodes(paste0('a[href="./?code=', atc_group, '"]')) %>% + html_nodes(paste0('a[href^="./?code=', atc_group, '&"]')) %>% html_text() + table_title <- table_title[tolower(table_title) != "show text from guidelines"][1] table_content <- downloaded %>% html_nodes("table") %>% html_table(header = TRUE) %>% @@ -59,12 +63,13 @@ get_atc_table <- function(atc_group) { } # these are the relevant groups for input: https://www.whocc.no/atc_ddd_index/?code=J05A (J05 only contains J05A) -atc_groups <- c("J05AA", "J05AB", "J05AC", "J05AD", "J05AE", "J05AF", "J05AG", "J05AH", "J05AP", "J05AR", "J05AX") +atc_groups <- c("J05AA", "J05AB", "J05AC", "J05AD", "J05AE", "J05AF", "J05AG", "J05AH", "J05AJ", "J05AP", "J05AR", "J05AX") # get the first antivirals <- get_atc_table(atc_groups[1]) # bind all others to it for (i in 2:length(atc_groups)) { + message(atc_groups[i], "...") antivirals <- rbind(antivirals, get_atc_table(atc_groups[i])) } @@ -73,7 +78,8 @@ antivirals <- antivirals %>% arrange(name) %>% as.data.frame(stringsAsFactors = FALSE) -# add PubChem Compound ID (cid) and their trade names - functions are in file to create `antibiotics` data set +# add PubChem Compound ID (cid) and their trade names +# see `data-raw/reproduction_of_antibiotics` for get_CID() and get_synonyms() CIDs <- get_CID(antivirals$name) # these could not be found: antivirals[is.na(CIDs), ] %>% View() @@ -92,7 +98,7 @@ synonyms <- lapply( antivirals <- antivirals %>% transmute(atc, - cid = CIDs, + cid = as.double(CIDs), name, atc_group, synonyms = unname(synonyms), @@ -100,7 +106,79 @@ antivirals <- antivirals %>% oral_units, iv_ddd, iv_units - ) + ) %>% + AMR:::dataset_UTF8_to_ASCII() + +av_codes <- tibble(name = antivirals$name %>% + strsplit("(, | and )") %>% + unlist() %>% + unique() %>% + sort()) %>% + mutate(av_1st = toupper(abbreviate(name, minlength = 3, use.classes = FALSE))) %>% + filter(!name %in% c("acid", "dipivoxil", "disoproxil", "marboxil", "alafenamide")) + +replace_with_av_code <- function(name) { + unname(av_codes$av_1st[match(name, av_codes$name)]) +} + +names_codes <- antivirals %>% + separate(name, + into = paste0("name", c(1:7)), + sep = "(, | and )", + remove = FALSE, + fill = "right") %>% + # remove empty columns + select(!where(function(x) all(is.na(x)))) %>% + mutate_at(vars(matches("name[1-9]")), replace_with_av_code) %>% + unite(av, matches("name[1-9]"), sep = "+", na.rm = TRUE) %>% + mutate(name = gsub("(, | and )", "/", name)) +substr(names_codes$name, 1, 1) <- toupper(substr(names_codes$name, 1, 1)) + +antivirals <- bind_cols( + names_codes %>% select(av, name), + antivirals %>% select(-name) +) +class(antivirals$av) <- c("av", "character") +antivirals <- antivirals %>% AMR:::dataset_UTF8_to_ASCII() + +# add loinc, see 'data-raw/loinc.R' +loinc_df <- read.csv("data-raw/Loinc.csv", + row.names = NULL, + stringsAsFactors = FALSE) + +loinc_df <- loinc_df %>% filter(CLASS == "DRUG/TOX") +av_names <- antivirals %>% + pull(name) %>% + paste0(collapse = "|") %>% + paste0("(", ., ")") + +antivirals$loinc <- as.list(rep(NA_character_, nrow(antivirals))) +for (i in seq_len(nrow(antivirals))) { + message(i) + loinc_ab <- loinc_df %>% + filter(COMPONENT %like% paste0("^", antivirals$name[i])) %>% + pull(LOINC_NUM) + if (length(loinc_ab) > 0) { + antivirals$loinc[i] <- list(loinc_ab) + } +} +# sort and fix for empty values +for (i in 1:nrow(antivirals)) { + loinc <- as.character(sort(unique(tolower(antivirals[i, "loinc", drop = TRUE][[1]])))) + antivirals[i, "loinc"][[1]] <- ifelse(length(loinc[!loinc == ""]) == 0, list(""), list(loinc)) +} + +# de-duplicate synonyms +for (i in 1:nrow(antivirals)) { + syn <- as.character(sort(unique(tolower(antivirals[i, "synonyms", drop = TRUE][[1]])))) + syn <- syn[!syn %in% tolower(antivirals[i, "name", drop = TRUE])] + antivirals[i, "synonyms"][[1]] <- ifelse(length(syn[!syn == ""]) == 0, list(""), list(syn)) +} + +antivirals <- antivirals %>% AMR:::dataset_UTF8_to_ASCII() + +# check it +antivirals # save it -usethis::use_data(antivirals, overwrite = TRUE) +usethis::use_data(antivirals, overwrite = TRUE, internal = FALSE, compress = "xz", version = 2) diff --git a/data/antivirals.rda b/data/antivirals.rda index 675f5c2d..419287c5 100644 Binary files a/data/antivirals.rda and b/data/antivirals.rda differ diff --git a/index.md b/index.md index b7eb8c7d..1f10e723 100644 --- a/index.md +++ b/index.md @@ -6,7 +6,7 @@ The `AMR` package is a [free and open-source](#copyright) R package with [zero d This work was published in the Journal of Statistical Software (Volume 104(3); [DOI 10.18637/jss.v104.i03](https://doi.org/10.18637/jss.v104.i03)) and formed the basis of two PhD theses ([DOI 10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and [DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)). -After installing this package, R knows [**~49,000 distinct microbial species**](./reference/microorganisms.html) and all [**~570 antibiotic, antimycotic and antiviral drugs**](./reference/antibiotics.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl), and is being [actively and durably maintained](./news) by two public healthcare organisations in the Netherlands. +After installing this package, R knows [**~49,000 distinct microbial species**](./reference/microorganisms.html) and all [**~600 antibiotic, antimycotic and antiviral drugs**](./reference/antibiotics.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl), and is being [actively and durably maintained](./news) by two public healthcare organisations in the Netherlands. ##### Used in 175 countries, translated to 16 languages diff --git a/inst/tinytest/test-ab_property.R b/inst/tinytest/test-ab_property.R index b6e514a2..89cd0afb 100644 --- a/inst/tinytest/test-ab_property.R +++ b/inst/tinytest/test-ab_property.R @@ -45,10 +45,8 @@ expect_identical(ab_name(21319, language = NULL), "Flucloxacillin") expect_identical(ab_name("J01CF05", language = NULL), "Flucloxacillin") expect_identical(ab_ddd("AMX", "oral"), 1.5) -expect_warning(ab_ddd("AMX", "oral", units = TRUE)) # old behaviour expect_identical(ab_ddd_units("AMX", "iv"), "g") expect_identical(ab_ddd("AMX", "iv"), 3) -expect_identical(ab_ddd_units("AMX", "iv"), "g") expect_identical(ab_name(x = c("AMC", "PLB"), language = NULL), c("Amoxicillin/clavulanic acid", "Polymyxin B")) expect_identical( diff --git a/inst/tinytest/test-av.R b/inst/tinytest/test-av.R new file mode 100755 index 00000000..3daa1e1d --- /dev/null +++ b/inst/tinytest/test-av.R @@ -0,0 +1,80 @@ +# ==================================================================== # +# TITLE # +# AMR: An R Package for Working with Antimicrobial Resistance Data # +# # +# SOURCE # +# https://github.com/msberends/AMR # +# # +# CITE AS # +# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # +# (2022). AMR: An R Package for Working with Antimicrobial Resistance # +# Data. Journal of Statistical Software, 104(3), 1-31. # +# doi:10.18637/jss.v104.i03 # +# # +# Developed at the University of Groningen, the Netherlands, in # +# collaboration with non-profit organisations Certe Medical # +# Diagnostics & Advice, and University Medical Center Groningen. # +# # +# This R package is free software; you can freely use and distribute # +# it for both personal and commercial purposes under the terms of the # +# GNU General Public License version 2.0 (GNU GPL-2), as published by # +# the Free Software Foundation. # +# We created this package for both routine data analysis and academic # +# research and it was publicly released in the hope that it will be # +# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # +# # +# Visit our website for the full manual and a complete tutorial about # +# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # +# ==================================================================== # + +expect_equal( + as.character(as.av(c( + "J05AB01", + "J 05 AB 01", + "Aciclovir", + "aciclo", + " aciclo 123", + "ACICL", + "ACI", + "Virorax", + "Zovirax" + ))), + rep("ACI", 9) +) + +expect_identical(class(as.av("acic")), c("av", "character")) +expect_identical(class(antivirals$av), c("av", "character")) +expect_true(is.av(as.av("acic"))) +expect_stdout(print(as.av("acic"))) +expect_stdout(print(data.frame(a = as.av("acic")))) + +expect_warning(as.av("J00AA00")) # ATC not yet available in data set +expect_warning(as.av("UNKNOWN")) + +expect_stdout(print(as.av("acic"))) + +expect_equal( + as.character(as.av("zovirax")), + "ACI" +) + +expect_equal( + as.character(as.av(c("Abacaivr", "Celvudine"))), + c("ABA", "CLE") +) + +expect_warning(as.av("Abacavir Clevudine")) + +# based on Levenshtein distance +expect_identical(av_name("adevofir dypifo", language = NULL), "Adefovir dipivoxil") + +# assigning and subsetting +x <- antivirals$av +expect_inherits(x[1], "av") +expect_inherits(x[[1]], "av") +expect_inherits(c(x[1], x[9]), "av") +expect_inherits(unique(x[1], x[9]), "av") +expect_inherits(rep(x[1], 2), "av") +expect_warning(x[1] <- "invalid code") +expect_warning(x[[1]] <- "invalid code") +expect_warning(c(x[1], "test")) diff --git a/inst/tinytest/test-av_from_text.R b/inst/tinytest/test-av_from_text.R new file mode 100644 index 00000000..dfa144a2 --- /dev/null +++ b/inst/tinytest/test-av_from_text.R @@ -0,0 +1,58 @@ +# ==================================================================== # +# TITLE # +# AMR: An R Package for Working with Antimicrobial Resistance Data # +# # +# SOURCE # +# https://github.com/msberends/AMR # +# # +# CITE AS # +# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # +# (2022). AMR: An R Package for Working with Antimicrobial Resistance # +# Data. Journal of Statistical Software, 104(3), 1-31. # +# doi:10.18637/jss.v104.i03 # +# # +# Developed at the University of Groningen, the Netherlands, in # +# collaboration with non-profit organisations Certe Medical # +# Diagnostics & Advice, and University Medical Center Groningen. # +# # +# This R package is free software; you can freely use and distribute # +# it for both personal and commercial purposes under the terms of the # +# GNU General Public License version 2.0 (GNU GPL-2), as published by # +# the Free Software Foundation. # +# We created this package for both routine data analysis and academic # +# research and it was publicly released in the hope that it will be # +# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # +# # +# Visit our website for the full manual and a complete tutorial about # +# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # +# ==================================================================== # + +expect_identical( + av_from_text("28/03/2020 regular aciclovir 500mg po tds")[[1]], + as.av("Aciclovir") +) +expect_identical( + av_from_text("28/03/2020 regular aciclovir 500mg po tds", thorough_search = TRUE)[[1]], + as.av("Aciclovir") +) +expect_identical( + av_from_text("28/03/2020 regular aciclovir 500mg po tds", thorough_search = FALSE)[[1]], + as.av("Aciclovir") +) +expect_identical( + av_from_text("28/03/2020 regular aciclovir 500mg po tds", translate_av = TRUE)[[1]], + "Aciclovir" +) +expect_identical( + av_from_text("administered aciclo and valaciclo", collapse = ", ")[[1]], + "ACI, VALA" +) + +expect_identical( + av_from_text("28/03/2020 regular aciclo 500mg po tds", type = "dose")[[1]], + 500 +) +expect_identical( + av_from_text("28/03/2020 regular aciclo 500mg po tds", type = "admin")[[1]], + "oral" +) diff --git a/inst/tinytest/test-av_property.R b/inst/tinytest/test-av_property.R new file mode 100644 index 00000000..1599343e --- /dev/null +++ b/inst/tinytest/test-av_property.R @@ -0,0 +1,64 @@ +# ==================================================================== # +# TITLE # +# AMR: An R Package for Working with Antimicrobial Resistance Data # +# # +# SOURCE # +# https://github.com/msberends/AMR # +# # +# CITE AS # +# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # +# (2022). AMR: An R Package for Working with Antimicrobial Resistance # +# Data. Journal of Statistical Software, 104(3), 1-31. # +# doi:10.18637/jss.v104.i03 # +# # +# Developed at the University of Groningen, the Netherlands, in # +# collaboration with non-profit organisations Certe Medical # +# Diagnostics & Advice, and University Medical Center Groningen. # +# # +# This R package is free software; you can freely use and distribute # +# it for both personal and commercial purposes under the terms of the # +# GNU General Public License version 2.0 (GNU GPL-2), as published by # +# the Free Software Foundation. # +# We created this package for both routine data analysis and academic # +# research and it was publicly released in the hope that it will be # +# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # +# # +# Visit our website for the full manual and a complete tutorial about # +# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # +# ==================================================================== # + +expect_identical(av_name("ACI", language = NULL), "Aciclovir") +expect_identical(av_atc("ACI"), "J05AB01") +expect_identical(av_cid("ACI"), as.integer(135398513)) + +expect_inherits(av_tradenames("ACI"), "character") +expect_inherits(av_tradenames(c("ACI", "ACI")), "list") + +expect_identical(av_group("ACI", language = NULL),"Nucleosides and nucleotides excl. reverse transcriptase inhibitors") + +expect_identical(av_name(135398513, language = NULL), "Aciclovir") +expect_identical(av_name("J05AB01", language = NULL), "Aciclovir") + +expect_identical(av_ddd("ACI", "oral"), 4) +expect_identical(av_ddd_units("ACI", "iv"), "g") +expect_identical(av_ddd("ACI", "iv"), 4) + +expect_identical( + av_name(x = c("ACI", "VALA"), tolower = TRUE, language = NULL), + c("aciclovir", "valaciclovir") +) + +expect_inherits(av_info("ACI"), "list") + +expect_error(av_property("acic", "invalid property")) +expect_error(av_name("acic", language = "INVALID")) +expect_stdout(print(av_name("acic", language = NULL))) + +expect_equal(av_name("29113-8", language = NULL), "Abacavir") +expect_equal( + av_loinc("Abacavir"), + c("29113-8", "78772-1", "78773-9", "79134-3", "80118-3") +) + +expect_true(av_url("ACI") %like% "whocc.no") +expect_warning(av_url("ASP")) diff --git a/inst/tinytest/test-mdro.R b/inst/tinytest/test-mdro.R index 19b37fae..a4389d1c 100755 --- a/inst/tinytest/test-mdro.R +++ b/inst/tinytest/test-mdro.R @@ -27,8 +27,6 @@ # how to conduct AMR data analysis: https://msberends.github.io/AMR/ # # ==================================================================== # -expect_error(suppressWarnings(mdro(example_isolates, country = "invalid", col_mo = "mo", info = TRUE))) -expect_error(suppressWarnings(mdro(example_isolates, country = "fr", info = TRUE))) expect_error(mdro(example_isolates, guideline = c("BRMO", "MRGN"), info = TRUE)) expect_error(mdro(example_isolates, col_mo = "invalid", info = TRUE)) diff --git a/man/AMR.Rd b/man/AMR.Rd index 79c08c68..2b23df89 100644 --- a/man/AMR.Rd +++ b/man/AMR.Rd @@ -32,7 +32,7 @@ Welcome to the \code{AMR} package. This work was published in the Journal of Statistical Software (Volume 104(3); \doi{10.18637/jss.v104.i03}) and formed the basis of two PhD theses (\doi{10.33612/diss.177417131} and \doi{10.33612/diss.192486375}). -After installing this package, \R knows ~49,000 distinct microbial species and all ~580 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. +After installing this package, \R knows ~49,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. This package is fully independent of any other \R package and works on Windows, macOS and Linux with all versions of \R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This \R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. diff --git a/man/ab_from_text.Rd b/man/ab_from_text.Rd index 91cbf33d..6dc8bb5e 100644 --- a/man/ab_from_text.Rd +++ b/man/ab_from_text.Rd @@ -60,7 +60,7 @@ With using \code{collapse}, this function will return a \link{character}:\cr \examples{ # mind the bad spelling of amoxicillin in this line, # straight from a true health care record: -ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds") +ab_from_text("28/03/2020 regular amoxicilliin 500mg po tid") ab_from_text("500 mg amoxi po and 400mg cipro iv") ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "dose") diff --git a/man/ab_property.Rd b/man/ab_property.Rd index 5bd4ca61..da836a7e 100644 --- a/man/ab_property.Rd +++ b/man/ab_property.Rd @@ -109,38 +109,35 @@ All data sets in this \code{AMR} package (about microorganisms, antibiotics, R/S \examples{ # all properties: -ab_name("AMX") # "Amoxicillin" -ab_atc("AMX") # "J01CA04" (ATC code from the WHO) -ab_cid("AMX") # 33613 (Compound ID from PubChem) -ab_synonyms("AMX") # a list with brand names of amoxicillin -ab_tradenames("AMX") # same -ab_group("AMX") # "Beta-lactams/penicillins" -ab_atc_group1("AMX") # "Beta-lactam antibacterials, penicillins" -ab_atc_group2("AMX") # "Penicillins with extended spectrum" -ab_url("AMX") # link to the official WHO page +ab_name("AMX") +ab_atc("AMX") +ab_cid("AMX") +ab_synonyms("AMX") +ab_tradenames("AMX") +ab_group("AMX") +ab_atc_group1("AMX") +ab_atc_group2("AMX") +ab_url("AMX") # smart lowercase tranformation -ab_name(x = c("AMC", "PLB")) # "Amoxicillin/clavulanic acid" "Polymyxin B" -ab_name( - x = c("AMC", "PLB"), - tolower = TRUE -) # "amoxicillin/clavulanic acid" "polymyxin B" +ab_name(x = c("AMC", "PLB")) +ab_name(x = c("AMC", "PLB"), tolower = TRUE) # defined daily doses (DDD) -ab_ddd("AMX", "oral") # 1.5 -ab_ddd_units("AMX", "oral") # "g" -ab_ddd("AMX", "iv") # 3 -ab_ddd_units("AMX", "iv") # "g" +ab_ddd("AMX", "oral") +ab_ddd_units("AMX", "oral") +ab_ddd("AMX", "iv") +ab_ddd_units("AMX", "iv") ab_info("AMX") # all properties as a list # all ab_* functions use as.ab() internally, so you can go from 'any' to 'any': -ab_atc("AMP") # ATC code of AMP (ampicillin) -ab_group("J01CA01") # Drug group of ampicillins ATC code -ab_loinc("ampicillin") # LOINC codes of ampicillin -ab_name("21066-6") # "Ampicillin" (using LOINC) -ab_name(6249) # "Ampicillin" (using CID) -ab_name("J01CA01") # "Ampicillin" (using ATC) +ab_atc("AMP") +ab_group("J01CA01") +ab_loinc("ampicillin") +ab_name("21066-6") +ab_name(6249) +ab_name("J01CA01") # spelling from different languages and dyslexia are no problem ab_atc("ceftriaxon") diff --git a/man/antibiotics.Rd b/man/antibiotics.Rd index 22bc4261..d50ef438 100644 --- a/man/antibiotics.Rd +++ b/man/antibiotics.Rd @@ -4,7 +4,7 @@ \name{antibiotics} \alias{antibiotics} \alias{antivirals} -\title{Data Sets with 585 Antimicrobial Drugs} +\title{Data Sets with 603 Antimicrobial Drugs} \format{ \subsection{For the \link{antibiotics} data set: a \link[tibble:tibble]{tibble} with 483 observations and 14 variables:}{ \itemize{ @@ -25,21 +25,23 @@ } } -\subsection{For the \link{antivirals} data set: a \link[tibble:tibble]{tibble} with 102 observations and 9 variables:}{ +\subsection{For the \link{antivirals} data set: a \link[tibble:tibble]{tibble} with 120 observations and 11 variables:}{ \itemize{ +\item \code{av}\cr Antibiotic ID as used in this package (such as \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available +\item \code{name}\cr Official name as used by WHONET/EARS-Net or the WHO \item \code{atc}\cr ATC codes (Anatomical Therapeutic Chemical) as defined by the WHOCC \item \code{cid}\cr Compound ID as found in PubChem -\item \code{name}\cr Official name as used by WHONET/EARS-Net or the WHO \item \code{atc_group}\cr Official pharmacological subgroup (3rd level ATC code) as defined by the WHOCC \item \code{synonyms}\cr Synonyms (often trade names) of a drug, as found in PubChem based on their compound ID \item \code{oral_ddd}\cr Defined Daily Dose (DDD), oral treatment \item \code{oral_units}\cr Units of \code{oral_ddd} \item \code{iv_ddd}\cr Defined Daily Dose (DDD), parenteral treatment \item \code{iv_units}\cr Units of \code{iv_ddd} +\item \code{loinc}\cr All LOINC codes (Logical Observation Identifiers Names and Codes) associated with the name of the antimicrobial agent. } } -An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 102 rows and 9 columns. +An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 120 rows and 11 columns. } \source{ \itemize{ diff --git a/man/as.ab.Rd b/man/as.ab.Rd index 7e2e8b4e..29034bcd 100644 --- a/man/as.ab.Rd +++ b/man/as.ab.Rd @@ -87,8 +87,8 @@ ab_atc("seephthriaaksone") # and even this works # use ab_* functions to get a specific properties (see ?ab_property); # they use as.ab() internally: -ab_name("J01FA01") # "Erythromycin" -ab_name("eryt") # "Erythromycin" +ab_name("J01FA01") +ab_name("eryt") \donttest{ if (require("dplyr")) { diff --git a/man/as.av.Rd b/man/as.av.Rd new file mode 100644 index 00000000..1629bb0f --- /dev/null +++ b/man/as.av.Rd @@ -0,0 +1,91 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/av.R +\name{as.av} +\alias{as.av} +\alias{av} +\alias{is.av} +\title{Transform Input to an Antiviral Agent ID} +\usage{ +as.av(x, flag_multiple_results = TRUE, info = interactive(), ...) + +is.av(x) +} +\arguments{ +\item{x}{a \link{character} vector to determine to antiviral agent ID} + +\item{flag_multiple_results}{a \link{logical} to indicate whether a note should be printed to the console that probably more than one antiviral agent code or name can be retrieved from a single input value.} + +\item{info}{a \link{logical} to indicate whether a progress bar should be printed, defaults to \code{TRUE} only in interactive mode} + +\item{...}{arguments passed on to internal functions} +} +\value{ +A \link{character} \link{vector} with additional class \code{\link{ab}} +} +\description{ +Use this function to determine the antiviral agent code of one or more antiviral agents. The data set \link{antivirals} will be searched for abbreviations, official names and synonyms (brand names). +} +\details{ +All entries in the \link{antivirals} data set have three different identifiers: a human readable EARS-Net code (column \code{ab}, used by ECDC and WHONET), an ATC code (column \code{atc}, used by WHO), and a CID code (column \code{cid}, Compound ID, used by PubChem). The data set contains more than 5,000 official brand names from many different countries, as found in PubChem. Not that some drugs contain multiple ATC codes. + +All these properties will be searched for the user input. The \code{\link[=as.av]{as.av()}} can correct for different forms of misspelling: +\itemize{ +\item Wrong spelling of drug names (such as "acyclovir"), which corrects for most audible similarities such as f/ph, x/ks, c/z/s, t/th, etc. +\item Too few or too many vowels or consonants +\item Switching two characters (such as "aycclovir", often the case in clinical data, when doctors typed too fast) +\item Digitalised paper records, leaving artefacts like 0/o/O (zero and O's), B/8, n/r, etc. +} + +Use the \code{\link[=av_property]{av_*}} functions to get properties based on the returned antiviral agent ID, see \emph{Examples}. + +Note: the \code{\link[=as.av]{as.av()}} and \code{\link[=av_property]{av_*}} functions may use very long regular expression to match brand names of antimicrobial agents. This may fail on some systems. +} +\section{Source}{ + +World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/} + +European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm} +} + +\section{WHOCC}{ + +\if{html}{\figure{logo_who.png}{options: height="60" style=margin-bottom:"5"} \cr} +This package contains \strong{all ~550 antibiotic, antimycotic and antiviral drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm}). + +These have become the gold standard for international drug utilisation monitoring and research. + +The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest. + +\strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.} See \url{https://www.whocc.no/copyright_disclaimer/.} +} + +\section{Reference Data Publicly Available}{ + +All data sets in this \code{AMR} package (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit \href{https://msberends.github.io/AMR/articles/datasets.html}{our website for the download links}. The actual files are of course available on \href{https://github.com/msberends/AMR/tree/main/data-raw}{our GitHub repository}. +} + +\examples{ +# these examples all return "ACI", the ID of aciclovir: +as.av("J05AB01") +as.av("J 05 AB 01") +as.av("Aciclovir") +as.av("aciclo") +as.av(" aciclo 123") +as.av("ACICL") +as.av("ACI") +as.av("Virorax") # trade name +as.av("Zovirax") # trade name + +as.av("acyklofir") # severe spelling error, yet works + +# use av_* functions to get a specific properties (see ?av_property); +# they use as.av() internally: +av_name("J05AB01") +av_name("acicl") +} +\seealso{ +\itemize{ +\item \link{antivirals} for the \link{data.frame} that is being used to determine ATCs +\item \code{\link[=av_from_text]{av_from_text()}} for a function to retrieve antimicrobial drugs from clinical text (from health care records) +} +} diff --git a/man/av_from_text.Rd b/man/av_from_text.Rd new file mode 100644 index 00000000..090c33e6 --- /dev/null +++ b/man/av_from_text.Rd @@ -0,0 +1,63 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/av_from_text.R +\name{av_from_text} +\alias{av_from_text} +\title{Retrieve Antiviral Drug Names and Doses from Clinical Text} +\usage{ +av_from_text( + text, + type = c("drug", "dose", "administration"), + collapse = NULL, + translate_av = FALSE, + thorough_search = NULL, + info = interactive(), + ... +) +} +\arguments{ +\item{text}{text to analyse} + +\item{type}{type of property to search for, either \code{"drug"}, \code{"dose"} or \code{"administration"}, see \emph{Examples}} + +\item{collapse}{a \link{character} to pass on to \code{paste(, collapse = ...)} to only return one \link{character} per element of \code{text}, see \emph{Examples}} + +\item{translate_av}{if \code{type = "drug"}: a column name of the \link{antivirals} data set to translate the antibiotic abbreviations to, using \code{\link[=av_property]{av_property()}}. Defaults to \code{FALSE}. Using \code{TRUE} is equal to using "name".} + +\item{thorough_search}{a \link{logical} to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to \code{TRUE} will take considerably more time than when using \code{FALSE}. At default, it will turn \code{TRUE} when all input elements contain a maximum of three words.} + +\item{info}{a \link{logical} to indicate whether a progress bar should be printed, defaults to \code{TRUE} only in interactive mode} + +\item{...}{arguments passed on to \code{\link[=as.av]{as.av()}}} +} +\value{ +A \link{list}, or a \link{character} if \code{collapse} is not \code{NULL} +} +\description{ +Use this function on e.g. clinical texts from health care records. It returns a \link{list} with all antiviral drugs, doses and forms of administration found in the texts. +} +\details{ +This function is also internally used by \code{\link[=as.av]{as.av()}}, although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the \code{\link[=as.av]{as.av()}} function may use very long regular expression to match brand names of antiviral agents. This may fail on some systems. +\subsection{Argument \code{type}}{ + +At default, the function will search for antiviral drug names. All text elements will be searched for official names, ATC codes and brand names. As it uses \code{\link[=as.av]{as.av()}} internally, it will correct for misspelling. + +With \code{type = "dose"} (or similar, like "dosing", "doses"), all text elements will be searched for \link{numeric} values that are higher than 100 and do not resemble years. The output will be \link{numeric}. It supports any unit (g, mg, IE, etc.) and multiple values in one clinical text, see \emph{Examples}. + +With \code{type = "administration"} (or abbreviations, like "admin", "adm"), all text elements will be searched for a form of drug administration. It supports the following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal and vaginal. Abbreviations for oral (such as 'po', 'per os') will become "oral", all values for intravenous (such as 'iv', 'intraven') will become "iv". It supports multiple values in one clinical text, see \emph{Examples}. +} + +\subsection{Argument \code{collapse}}{ + +Without using \code{collapse}, this function will return a \link{list}. This can be convenient to use e.g. inside a \code{mutate()}):\cr +\code{df \%>\% mutate(avx = av_from_text(clinical_text))} + +The returned AV codes can be transformed to official names, groups, etc. with all \code{\link[=av_property]{av_*}} functions such as \code{\link[=av_name]{av_name()}} and \code{\link[=av_group]{av_group()}}, or by using the \code{translate_av} argument. + +With using \code{collapse}, this function will return a \link{character}:\cr +\code{df \%>\% mutate(avx = av_from_text(clinical_text, collapse = "|"))} +} +} +\examples{ +av_from_text("28/03/2020 valaciclovir po tid") +av_from_text("28/03/2020 valaciclovir po tid", type = "admin") +} diff --git a/man/av_property.Rd b/man/av_property.Rd new file mode 100644 index 00000000..2015bd97 --- /dev/null +++ b/man/av_property.Rd @@ -0,0 +1,117 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/av_property.R +\name{av_property} +\alias{av_property} +\alias{av_name} +\alias{av_cid} +\alias{av_synonyms} +\alias{av_tradenames} +\alias{av_group} +\alias{av_atc} +\alias{av_loinc} +\alias{av_ddd} +\alias{av_ddd_units} +\alias{av_info} +\alias{av_url} +\title{Get Properties of an Antiviral Agent} +\usage{ +av_name(x, language = get_AMR_locale(), tolower = FALSE, ...) + +av_cid(x, ...) + +av_synonyms(x, ...) + +av_tradenames(x, ...) + +av_group(x, language = get_AMR_locale(), ...) + +av_atc(x, ...) + +av_loinc(x, ...) + +av_ddd(x, administration = "oral", ...) + +av_ddd_units(x, administration = "oral", ...) + +av_info(x, language = get_AMR_locale(), ...) + +av_url(x, open = FALSE, ...) + +av_property(x, property = "name", language = get_AMR_locale(), ...) +} +\arguments{ +\item{x}{any (vector of) text that can be coerced to a valid antiviral agent code with \code{\link[=as.av]{as.av()}}} + +\item{language}{language of the returned text, defaults to system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}}) and can also be set with \code{getOption("AMR_locale")}. Use \code{language = NULL} or \code{language = ""} to prevent translation.} + +\item{tolower}{a \link{logical} to indicate whether the first \link{character} of every output should be transformed to a lower case \link{character}.} + +\item{...}{other arguments passed on to \code{\link[=as.av]{as.av()}}} + +\item{administration}{way of administration, either \code{"oral"} or \code{"iv"}} + +\item{open}{browse the URL using \code{\link[utils:browseURL]{utils::browseURL()}}} + +\item{property}{one of the column names of one of the \link{antivirals} data set: \code{vector_or(colnames(antivirals), sort = FALSE)}.} +} +\value{ +\itemize{ +\item An \link{integer} in case of \code{\link[=av_cid]{av_cid()}} +\item A named \link{list} in case of \code{\link[=av_info]{av_info()}} and multiple \code{\link[=av_atc]{av_atc()}}/\code{\link[=av_synonyms]{av_synonyms()}}/\code{\link[=av_tradenames]{av_tradenames()}} +\item A \link{double} in case of \code{\link[=av_ddd]{av_ddd()}} +\item A \link{character} in all other cases +} +} +\description{ +Use these functions to return a specific property of an antiviral agent from the \link{antivirals} data set. All input values will be evaluated internally with \code{\link[=as.av]{as.av()}}. +} +\details{ +All output \link[=translate]{will be translated} where possible. + +The function \code{\link[=av_url]{av_url()}} will return the direct URL to the official WHO website. A warning will be returned if the required ATC code is not available. +} +\section{Source}{ + +World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/} + +European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm} +} + +\section{Reference Data Publicly Available}{ + +All data sets in this \code{AMR} package (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit \href{https://msberends.github.io/AMR/articles/datasets.html}{our website for the download links}. The actual files are of course available on \href{https://github.com/msberends/AMR/tree/main/data-raw}{our GitHub repository}. +} + +\examples{ +# all properties: +av_name("ACI") +av_atc("ACI") +av_cid("ACI") +av_synonyms("ACI") +av_tradenames("ACI") +av_group("ACI") +av_url("ACI") + +# smart lowercase tranformation +av_name(x = c("ACI", "VALA")) +av_name(x = c("ACI", "VALA"), tolower = TRUE) + +# defined daily doses (DDD) +av_ddd("ACI", "oral") +av_ddd_units("ACI", "oral") +av_ddd("ACI", "iv") +av_ddd_units("ACI", "iv") + +av_info("ACI") # all properties as a list + +# all av_* functions use as.av() internally, so you can go from 'any' to 'any': +av_atc("ACI") +av_group("J05AB01") +av_loinc("abacavir") +av_name("29113-8") +av_name(135398513) +av_name("J05AB01") +} +\seealso{ +\link{antivirals} +} diff --git a/vignettes/datasets.Rmd b/vignettes/datasets.Rmd index f0cff568..e7ee87ab 100644 --- a/vignettes/datasets.Rmd +++ b/vignettes/datasets.Rmd @@ -156,7 +156,7 @@ microorganisms %>% ``` -## `antibiotics`: Antibiotic Agents +## `antibiotics`: Antibiotic (+Antifungal) Drugs `r structure_txt(antibiotics)` @@ -173,6 +173,7 @@ This data set contains all EARS-Net and ATC codes gathered from WHO and WHONET, * [ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology](https://www.whocc.no/atc_ddd_index/) (note: this may not be used for commercial purposes, but is freely available from the WHO CC website for personal use) * [PubChem by the US National Library of Medicine](https://pubchem.ncbi.nlm.nih.gov) * [WHONET software 2019](https://whonet.org) +* [LOINC (Logical Observation Identifiers Names and Codes)](https://loinc.org) ### Example content @@ -183,7 +184,7 @@ antibiotics %>% ``` -## `antivirals`: Antiviral Agents +## `antivirals`: Antiviral Drugs `r structure_txt(antivirals)` @@ -191,7 +192,7 @@ This data set is in R available as `antivirals`, after you load the `AMR` packag `r download_txt("antivirals")` -The tab-separated text file and Microsoft Excel workbook, and SAS, SPSS and Stata files all contain the trade names as comma separated values. +The tab-separated text file and Microsoft Excel workbook, and SAS, SPSS and Stata files all contain the trade names and LOINC codes as comma separated values. ### Source @@ -199,6 +200,7 @@ This data set contains all ATC codes gathered from WHO and all compound IDs from * [ATC/DDD index from WHO Collaborating Centre for Drug Statistics Methodology](https://www.whocc.no/atc_ddd_index/) (note: this may not be used for commercial purposes, but is freely available from the WHO CC website for personal use) * [PubChem by the US National Library of Medicine](https://pubchem.ncbi.nlm.nih.gov) +* [LOINC (Logical Observation Identifiers Names and Codes)](https://loinc.org) ### Example content