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reference/as.ab.md
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# Transform Input to an Antibiotic ID
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Use this function to determine the antimicrobial drug code of one or
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more antimicrobials. The data set
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[antimicrobials](https://amr-for-r.org/reference/antimicrobials.md) will
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be searched for abbreviations, official names and synonyms (brand
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names).
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## Usage
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``` r
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as.ab(x, flag_multiple_results = TRUE, language = get_AMR_locale(),
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info = interactive(), ...)
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is.ab(x)
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ab_reset_session()
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```
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## Arguments
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- x:
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A [character](https://rdrr.io/r/base/character.html) vector to
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determine to antibiotic ID.
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- flag_multiple_results:
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A [logical](https://rdrr.io/r/base/logical.html) to indicate whether a
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note should be printed to the console that probably more than one
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antibiotic drug code or name can be retrieved from a single input
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value.
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- language:
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Language to coerce input values from any of the 28 supported
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languages - default to the system language if supported (see
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[`get_AMR_locale()`](https://amr-for-r.org/reference/translate.md)).
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- info:
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A [logical](https://rdrr.io/r/base/logical.html) to indicate whether a
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progress bar should be printed - the default is `TRUE` only in
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interactive mode.
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- ...:
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Arguments passed on to internal functions.
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## Value
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A [character](https://rdrr.io/r/base/character.html)
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[vector](https://rdrr.io/r/base/vector.html) with additional class `ab`
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## Details
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All entries in the
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[antimicrobials](https://amr-for-r.org/reference/antimicrobials.md) data
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set have three different identifiers: a human readable EARS-Net code
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(column `ab`, used by ECDC and WHONET), an ATC code (column `atc`, used
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by WHO), and a CID code (column `cid`, Compound ID, used by PubChem).
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The data set contains more than 5,000 official brand names from many
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different countries, as found in PubChem. Not that some drugs contain
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multiple ATC codes.
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All these properties will be searched for the user input. The `as.ab()`
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can correct for different forms of misspelling:
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- Wrong spelling of drug names (such as "tobramicin" or "gentamycin"),
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which corrects for most audible similarities such as f/ph, x/ks,
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c/z/s, t/th, etc.
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- Too few or too many vowels or consonants
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- Switching two characters (such as "mreopenem", often the case in
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clinical data, when doctors typed too fast)
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- Digitalised paper records, leaving artefacts like 0/o/O (zero and
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O's), B/8, n/r, etc.
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Use the [`ab_*`](https://amr-for-r.org/reference/ab_property.md)
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functions to get properties based on the returned antibiotic ID, see
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*Examples*.
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Note: the `as.ab()` and
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[`ab_*`](https://amr-for-r.org/reference/ab_property.md) functions may
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use very long regular expression to match brand names of antimicrobial
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drugs. This may fail on some systems.
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You can add your own manual codes to be considered by `as.ab()` and all
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[`ab_*`](https://amr-for-r.org/reference/ab_property.md) functions, see
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[`add_custom_antimicrobials()`](https://amr-for-r.org/reference/add_custom_antimicrobials.md).
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## Source
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World Health Organization (WHO) Collaborating Centre for Drug Statistics
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Methodology: <https://atcddd.fhi.no/atc_ddd_index/>
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European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER:
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<https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>
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## WHOCC
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This package contains **all ~550 antibiotic, antimycotic and antiviral
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drugs** and their Anatomical Therapeutic Chemical (ATC) codes, ATC
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groups and Defined Daily Dose (DDD) from the World Health Organization
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Collaborating Centre for Drug Statistics Methodology (WHOCC,
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<https://atcddd.fhi.no>) and the Pharmaceuticals Community Register of
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the European Commission
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(<https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>).
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These have become the gold standard for international drug utilisation
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monitoring and research.
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The WHOCC is located in Oslo at the Norwegian Institute of Public Health
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and funded by the Norwegian government. The European Commission is the
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executive of the European Union and promotes its general interest.
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**NOTE: The WHOCC copyright does not allow use for commercial purposes,
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unlike any other info from this package.** See
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<https://atcddd.fhi.no/copyright_disclaimer/.>
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## Download Our Reference Data
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All reference data sets in the AMR package - including information on
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microorganisms, antimicrobials, and clinical breakpoints - are freely
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available for download in multiple formats: R, MS Excel, Apache Feather,
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Apache Parquet, SPSS, and Stata.
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For maximum compatibility, we also provide machine-readable,
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tab-separated plain text files suitable for use in any software,
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including laboratory information systems.
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Visit [our website for direct download
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links](https://amr-for-r.org/articles/datasets.html), or explore the
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actual files in [our GitHub
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repository](https://github.com/msberends/AMR/tree/main/data-raw/datasets).
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## See also
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- [antimicrobials](https://amr-for-r.org/reference/antimicrobials.md)
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for the [data.frame](https://rdrr.io/r/base/data.frame.html) that is
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being used to determine ATCs
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- [`ab_from_text()`](https://amr-for-r.org/reference/ab_from_text.md)
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for a function to retrieve antimicrobial drugs from clinical text
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(from health care records)
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## Examples
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``` r
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# these examples all return "ERY", the ID of erythromycin:
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as.ab("J01FA01")
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#> Class 'ab'
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#> [1] ERY
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as.ab("J 01 FA 01")
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#> Class 'ab'
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#> [1] ERY
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as.ab("Erythromycin")
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#> Class 'ab'
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#> [1] ERY
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as.ab("eryt")
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#> Class 'ab'
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#> [1] ERY
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as.ab("ERYT")
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#> Class 'ab'
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#> [1] ERY
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as.ab("ERY")
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#> Class 'ab'
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#> [1] ERY
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as.ab("eritromicine") # spelled wrong, yet works
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#> Class 'ab'
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#> [1] ERY
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as.ab("Erythrocin") # trade name
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#> Class 'ab'
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#> [1] ERY
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# spelling from different languages and dyslexia are no problem
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ab_atc("ceftriaxon")
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#> [1] "J01DD04" "QJ01DD04"
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ab_atc("cephtriaxone") # small spelling error
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#> [1] "J01DD04" "QJ01DD04"
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ab_atc("cephthriaxone") # or a bit more severe
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#> [1] "J01DD04" "QJ01DD04"
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ab_atc("seephthriaaksone") # and even this works
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#> [1] "J01DD04" "QJ01DD04"
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# use ab_* functions to get a specific properties (see ?ab_property);
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# they use as.ab() internally:
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ab_name("J01FA01")
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#> [1] "Erythromycin"
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ab_name("eryt")
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#> [1] "Erythromycin"
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# \donttest{
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if (require("dplyr")) {
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# you can quickly rename 'sir' columns using set_ab_names() with dplyr:
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example_isolates %>%
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set_ab_names(where(is.sir), property = "atc")
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}
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#> # A tibble: 2,000 × 46
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#> date patient age gender ward mo J01CE01 J01CF04 J01CF05
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#> <date> <chr> <dbl> <chr> <chr> <mo> <sir> <sir> <sir>
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#> 1 2002-01-02 A77334 65 F Clinical B_ESCHR_COLI R NA NA
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#> 2 2002-01-03 A77334 65 F Clinical B_ESCHR_COLI R NA NA
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#> 3 2002-01-07 067927 45 F ICU B_STPHY_EPDR R NA R
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#> 4 2002-01-07 067927 45 F ICU B_STPHY_EPDR R NA R
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#> 5 2002-01-13 067927 45 F ICU B_STPHY_EPDR R NA R
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#> 6 2002-01-13 067927 45 F ICU B_STPHY_EPDR R NA R
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#> 7 2002-01-14 462729 78 M Clinical B_STPHY_AURS R NA S
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#> 8 2002-01-14 462729 78 M Clinical B_STPHY_AURS R NA S
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#> 9 2002-01-16 067927 45 F ICU B_STPHY_EPDR R NA R
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#> 10 2002-01-17 858515 79 F ICU B_STPHY_EPDR R NA S
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#> # ℹ 1,990 more rows
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#> # ℹ 37 more variables: J01CA04 <sir>, J01CR02 <sir>, J01CA01 <sir>,
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#> # J01CR05 <sir>, J01DB04 <sir>, J01DE01 <sir>, J01DC02 <sir>, J01DC01 <sir>,
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#> # J01DD01 <sir>, J01DD02 <sir>, J01DD04 <sir>, J01GB03 <sir>, J01GB01 <sir>,
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#> # J01GB06 <sir>, J01GB04 <sir>, J01EA01 <sir>, J01EE01 <sir>, J01XE01 <sir>,
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#> # J01XX01 <sir>, J01XX08 <sir>, J01MA02 <sir>, J01MA14 <sir>, J01XA01 <sir>,
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#> # J01XA02 <sir>, J01AA07 <sir>, J01AA12 <sir>, J01AA02 <sir>, …
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# }
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```
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