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(v2.1.1.9243) fix sir documentation

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dr. M.S. (Matthijs) Berends
2025-04-18 16:32:45 +02:00
parent 29b0ef1089
commit ca00ed468e
9 changed files with 36 additions and 26 deletions
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data-raw/gpt_training_text_v2.1.1.9242.txt → data-raw/gpt_training_text_v2.1.1.9243.txt
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@@ -1,6 +1,6 @@
This knowledge base contains all context you must know about the AMR package for R. You are a GPT trained to be an assistant for the AMR package in R. You are an incredible R specialist, especially trained in this package and in the tidyverse.
First and foremost, you are trained on version 2.1.1.9242. Remember this whenever someone asks which AMR package version you’re at.
First and foremost, you are trained on version 2.1.1.9243. Remember this whenever someone asks which AMR package version you’re at.
Below are the contents of the NAMESPACE file, the index.md file, and all the man/*.Rd files (documentation) in the package. Every file content is split using 100 hypens.
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@@ -398,7 +398,7 @@ THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'index.md':
# The `AMR` Package for R <a href="https://amr-for-r.org/"><img src="./logo.svg" align="right" height="139" /></a>
* Provides an **all-in-one solution** for antimicrobial resistance (AMR) data analysis in a One Health approach
* Used in over 175 countries, available in 20 languages
* Peer-reviewed, used in over 175 countries, available in 20 languages
* Generates **antibiograms** - traditional, combined, syndromic, and even WISCA
* Provides the **full microbiological taxonomy** and extensive info on **all antimicrobial drugs**
* Applies all recent **CLSI** and **EUCAST** clinical and veterinary breakpoints for MICs, disk zones and ECOFFs
@@ -419,11 +419,11 @@ THE PART HEREAFTER CONTAINS CONTENTS FROM FILE 'index.md':
### Introduction
The `AMR` package is a [free and open-source](#copyright) R package with [zero dependencies](https://en.wikipedia.org/wiki/Dependency_hell) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. [Many different researchers](./authors.html) from around the globe are continually helping us to make this a successful and durable project!
The `AMR` package is a peer-reviewed, [free and open-source](#copyright) R package with [zero dependencies](https://en.wikipedia.org/wiki/Dependency_hell) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. [Many different researchers](./authors.html) from around the globe are continually helping us to make this a successful and durable project!
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 [**~52,000 distinct microbial species**](./reference/microorganisms.html) (updated December 2022) and all [**~600 antimicrobial and antiviral drugs**](./reference/antimicrobials.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. 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).
After installing this package, R knows [**~79,000 distinct microbial species**](./reference/microorganisms.html) (updated June 2024) and all [**~620 antimicrobial and antiviral drugs**](./reference/antimicrobials.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. 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).
##### Used in over 175 countries, available in 20 languages
@@ -3460,7 +3460,7 @@ sir_interpretation_history(clean = FALSE)
\item{ab}{A vector (or column name) with \link{character}s that can be coerced to a valid antimicrobial drug code with \code{\link[=as.ab]{as.ab()}}.}
\item{guideline}{A guideline name (or column name) to use for SIR interpretation. Defaults to EUCAST 2024 (the latest implemented EUCAST guideline in the \link{clinical_breakpoints} data set), but can be set with the package option \code{\link[=AMR-options]{AMR_guideline}}. Currently supports EUCAST (2011-2024) and CLSI (2011-2024), see \emph{Details}. Using a column name for \code{\link[=as.sir]{as.sir()}} allows for easy interpretation on historical data which needs to be interpreted according to e.g., various years.}
\item{guideline}{A guideline name (or column name) to use for SIR interpretation. Defaults to EUCAST 2024 (the latest implemented EUCAST guideline in the \link{clinical_breakpoints} data set), but can be set with the package option \code{\link[=AMR-options]{AMR_guideline}}. Currently supports EUCAST (2011-2024) and CLSI (2011-2024), see \emph{Details}. Using a column name allows for straightforward interpretation of historical data, which must be analysed in the context of, for example, different years.}
\item{uti}{(Urinary Tract Infection) a vector (or column name) with \link{logical}s (\code{TRUE} or \code{FALSE}) to specify whether a UTI specific interpretation from the guideline should be chosen. For using \code{\link[=as.sir]{as.sir()}} on a \link{data.frame}, this can also be a column containing \link{logical}s or when left blank, the data set will be searched for a column 'specimen', and rows within this column containing 'urin' (such as 'urine', 'urina') will be regarded isolates from a UTI. See \emph{Examples}.}
@@ -3574,9 +3574,11 @@ your_data \%>\% mutate_if(is.disk, as.sir, host = "column_with_animal_species",
For interpreting MIC values as well as disk diffusion diameters, currently implemented guidelines are for \strong{clinical microbiology}: EUCAST 2011-2024 and CLSI 2011-2024, and for \strong{veterinary microbiology}: EUCAST 2021-2024 and CLSI 2019-2024.
Thus, the \code{guideline} argument must be set to e.g., \code{"EUCAST 2024"} or \code{"CLSI 2024"}. By simply using \code{"EUCAST"} (the default) or \code{"CLSI"} as input, the latest included version of that guideline will automatically be selected. You can set your own data set using the \code{reference_data} argument. The \code{guideline} argument will then be ignored.
Thus, the \code{guideline} argument must be set to e.g., \code{"EUCAST 2024"} or \code{"CLSI 2024"}. By simply using \code{"EUCAST"} (the default) or \code{"CLSI"} as input, the latest included version of that guideline will automatically be selected. Importantly, using a column name of your data instead, allows for straightforward interpretation of historical data, which must be analysed in the context of, for example, different years.
You can set the default guideline with the package option \code{\link[=AMR-options]{AMR_guideline}} (e.g. in your \code{.Rprofile} file), such as:
You can set your own data set using the \code{reference_data} argument. The \code{guideline} argument will then be ignored.
It is also possible to set the default guideline with the package option \code{\link[=AMR-options]{AMR_guideline}} (e.g. in your \code{.Rprofile} file), such as:
\if{html}{\out{<div class="sourceCode">}}\preformatted{ options(AMR_guideline = "CLSI")
options(AMR_guideline = "CLSI 2018")
@@ -3665,7 +3667,7 @@ if (require("dplyr")) {
mutate_if(is.mic, as.sir,
mo = "bacteria",
ab = "antibiotic",
guideline = guideline
guideline = "guideline"
)
df_long \%>\%
mutate(across(