mirror of https://github.com/msberends/AMR.git
49 lines
2.3 KiB
Plaintext
49 lines
2.3 KiB
Plaintext
---
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title: "How to apply EUCAST rules"
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author: "Matthijs S. Berends"
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date: '`r format(Sys.Date(), "%d %B %Y")`'
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output:
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rmarkdown::html_vignette:
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toc: true
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toc_depth: 3
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vignette: >
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%\VignetteIndexEntry{How to apply EUCAST rules}
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%\VignetteEncoding{UTF-8}
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%\VignetteEngine{knitr::rmarkdown}
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editor_options:
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chunk_output_type: console
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---
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```{r setup, include = FALSE, results = 'markup'}
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knitr::opts_chunk$set(
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collapse = TRUE,
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comment = "#",
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fig.width = 7.5,
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fig.height = 4.5
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)
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library(AMR)
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```
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## Introduction
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What are EUCAST rules? The European Committee on Antimicrobial Susceptibility Testing (EUCAST) states [on their website](http://www.eucast.org/expert_rules_and_intrinsic_resistance/):
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> *EUCAST expert rules are a tabulated collection of expert knowledge on intrinsic resistances, exceptional resistance phenotypes and interpretive rules that may be applied to antimicrobial susceptibility testing in order to reduce errors and make appropriate recommendations for reporting particular resistances.*
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In Europe, a lot of medical microbiological laboratories already apply these rules ([Brown *et al.*, 2015](https://www.eurosurveillance.org/content/10.2807/1560-7917.ES2015.20.2.21008)). Our package features their latest insights on intrinsic resistance and exceptional phenotypes (version 9.0, 2019). Moreover, the `eucast_rules()` function we use for this purpose can also apply additional rules, like forcing <help title="ATC: J01CA01">ampicillin</help> = R in isolates when <help title="ATC: J01CR02">amoxicillin/clavulanic acid</help> = R.
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## Examples
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These rules can be used to discard impossible bug-drug combinations in your data. For example, *Klebsiella* produces beta-lactamase that prevents ampicillin (or amoxicillin) from working against it. In other words, every strain of *Klebsiella* is resistant to ampicillin.
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Sometimes, laboratory data can still contain such strains with ampicillin being susceptible to ampicillin. This could be because an antibiogram is available before an identification is available, and the antibiogram is then not re-interpreted based on the identification (namely, *Klebsiella*). EUCAST expert rules solves this:
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```{r, warning = FALSE, message = FALSE}
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oops <- data.frame(mo = c("Klebsiella",
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"Escherichia"),
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ampicillin = "S")
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oops
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eucast_rules(oops, info = FALSE)
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```
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