Note: some changes in this version were suggested by anonymous reviewers from the journal we submitted our manuscipt about this package to. We are those reviewers very grateful for going through our code so thoroughly!
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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](http://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()`.
* Support for the newest [EUCAST Clinical Breakpoint Tables v.10.0](https://www.eucast.org/clinical_breakpoints/), valid from 1 January 2020. This affects translation of MIC and disk zones using `as.rsi()` and inferred resistance and susceptibility using `eucast_rules()`.
* The repository of this package now contains a clean version of the EUCAST and CLSI guidelines from 2011-2020 to translate MIC and disk diffusion values to R/SI: <https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt>. This **allows for machine reading these guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. This file used to process the EUCAST Clinical Breakpoints Excel file [can be found here](https://github.com/msberends/AMR/blob/master/data-raw/read_EUCAST.R).
* Support for LOINC and SNOMED codes
* Support for LOINC codes in the `antibiotics` data set. Use `ab_loinc()` to retrieve LOINC codes, or use a LOINC code for input in any `ab_*` function:
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# AMR 0.9.0
### Breaking
* Adopted Adeolu *et al.* (2016), [PMID 27620848](https://www.ncbi.nlm.nih.gov/pubmed/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.
* 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") ...
@ -591,7 +591,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
@@ -591,7 +591,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
* 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://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net) (European Antimicrobial Resistance Surveillance Network):
* 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 parameters 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.
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#### Changed
* Function `eucast_rules()`:
* Updated EUCAST Clinical breakpoints to [version 9.0 of 1 January 2019](http://www.eucast.org/clinical_breakpoints/), the data set `septic_patients` now reflects these changes
* 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.
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@@ -776,7 +776,7 @@ We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.git
* 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, http://www.eucast.org/clinical_breakpoints/ (see Source of the 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 parameter `rules` to specify which rules should be applied (expert rules, breakpoints, others or all)
* New parameter `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)
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* 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](http://www.eucast.org/expert_rules_and_intrinsic_resistance) are also supported instead of countries alone
* [Exceptional resistances defined by EUCAST](https://www.eucast.org/expert_rules_and_intrinsic_resistance/) 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
#' All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this `AMR` package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find [all download links on our website](https://msberends.github.io/AMR/articles/datasets.html), which is automatically updated with every code change.
#' @section Read more on our website!:
#' On our website <https://msberends.github.io/AMR> you can find [a comprehensive tutorial](https://msberends.github.io/AMR/articles/AMR.html) about how to conduct AMR analysis, the [complete documentation of all functions](https://msberends.github.io/AMR/reference) (which reads a lot easier than here in R) and [an example analysis using WHONET data](https://msberends.github.io/AMR/articles/WHONET.html). As we would like to better understand the backgrounds and needs of our users, please [participate in our survey](https://msberends.github.io/AMR/survey.html)!
#' On our website <https://msberends.github.io/AMR/> you can find [a comprehensive tutorial](https://msberends.github.io/AMR/articles/AMR.html) about how to conduct AMR analysis, the [complete documentation of all functions](https://msberends.github.io/AMR/reference/) and [an example analysis using WHONET data](https://msberends.github.io/AMR/articles/WHONET.html). As we would like to better understand the backgrounds and needs of our users, please [participate in our survey](https://msberends.github.io/AMR/survey.html)!
#' @section Contact Us:
#' For suggestions, comments or questions, please contact us at:
#' @section About the records from DSMZ (see source):
#' Names of prokaryotes are defined as being validly published by the International Code of Nomenclature of Bacteria. Validly published are all names which are included in the Approved Lists of Bacterial Names and the names subsequently published in the International Journal of Systematic Bacteriology (IJSB) and, from January 2000, in the International Journal of Systematic and Evolutionary Microbiology (IJSEM) as original articles or in the validation lists.
#' In February 2020, the DSMZ records were merged with the List of Prokaryotic names with Standing in Nomenclature (LPSN).
#' @source Catalogue of Life: Annual Checklist (public online taxonomic database), <http://www.catalogueoflife.org> (check included annual version with [catalogue_of_life_version()]).
#' @param include_unknown logical to determine whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
#' @param ... parameters passed on to the [first_isolate()] function
#' @details **WHY THIS IS SO IMPORTANT** \cr
#' To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode [(ref)](https://www.ncbi.nlm.nih.gov/pubmed/17304462). If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all *S. aureus* isolates would be overestimated, because you included this MRSA more than once. It would be [selection bias](https://en.wikipedia.org/wiki/Selection_bias).
#' To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode [(ref)](https:/pubmed.ncbi.nlm.nih.gov/17304462/). If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all *S. aureus* isolates would be overestimated, because you included this MRSA more than once. It would be [selection bias](https://en.wikipedia.org/wiki/Selection_bias).
#'
#' All isolates with a microbial ID of `NA` will be excluded as first isolate.
#' @description Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. A normal distribution has a kurtosis of 3 and a excess kurtosis of 0.
#' @inheritSection lifecycle Stable lifecycle
#' @param x a vector of values, a [`matrix`] or a [data.frame]
#' @param x a vector of values, a [matrix] or a [data.frame]
#' @param na.rm a logical to indicate whether `NA` values should be stripped before the computation proceeds
#' @param excess a logical to indicate whether the *excess kurtosis* should be returned, defined as the kurtosis minus 3.
#' The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6
#' - `guideline = "BRMO"`\cr
#' The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)" ([link](https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH))
#' The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)" ([link](https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh))
#'
#' Please suggest your own (country-specific) guidelines by letting us know: <https://github.com/msberends/AMR/issues/new>.
#' Calculate the matching score for microorganisms
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@@ -27,7 +31,7 @@
#' @section Matching score for microorganisms:
#' With ambiguous user input in [as.mo()] and all the [`mo_*`][mo_property()] functions, the returned results are chosen based on their matching score using [mo_matching_score()]. This matching score \eqn{m}, is calculated as:
