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# Apply EUCAST rules

Source: `vignettes/EUCAST.Rmd`
`EUCAST.Rmd`

## Introduction

What are EUCAST rules? The European Committee on Antimicrobial Susceptibility Testing (EUCAST) states on their website:

> EUCAST expert rules (see below) are a tabulated collection of expert knowledge on interpretive rules, expected resistant phenotypes and expected susceptible phenotypes which should be applied to antimicrobial susceptibility testing in order to reduce testing, reduce errors and make appropriate recommendations for reporting particular resistances.

In Europe, a lot of medical microbiological laboratories already apply these rules (Brown et al., 2015). Our package features their latest insights on expected resistant phenotypes (v1.2, 2023).

## Examples

These rules can be used to discard improbable bug-drug combinations in your data. For example, Klebsiella produces beta-lactamase that prevents ampicillin (or amoxicillin) from working against it. In other words, practically every strain of Klebsiella is resistant to ampicillin.

Sometimes, laboratory data can still contain such strains with Klebsiella 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. The `eucast_rules()` function resolves this, by applying the latest ‘EUCAST Expected Resistant Phenotypes’ guideline:

    oops <- tibble::tibble(
      mo = c(
        "Klebsiella pneumoniae",
        "Escherichia coli"
      ),
      ampicillin = as.sir("S")
    )
    oops
    #> # A tibble: 2 × 2
    #>   mo                    ampicillin
    #>   <chr>                 <sir>
    #> 1 Klebsiella pneumoniae   S
    #> 2 Escherichia coli        S

    eucast_rules(oops, info = FALSE, overwrite = TRUE)
    #> # A tibble: 2 × 2
    #>   mo                    ampicillin
    #>   <chr>                 <sir>
    #> 1 Klebsiella pneumoniae   R
    #> 2 Escherichia coli        S

A more convenient function is `mo_is_intrinsic_resistant()` that uses the same guideline, but allows to check for one or more specific microorganisms or antimicrobials:

    mo_is_intrinsic_resistant(
      c("Klebsiella pneumoniae", "Escherichia coli"),
      "ampicillin"
    )
    #> [1]  TRUE FALSE

    mo_is_intrinsic_resistant(
      "Klebsiella pneumoniae",
      c("ampicillin", "kanamycin")
    )
    #> [1]  TRUE FALSE

EUCAST rules can not only be used for correction, they can also be used for filling in known resistance and susceptibility based on results of other antimicrobials drugs. This process is called interpretive reading, and is basically a form of imputation:

    data <- tibble::tibble(
      mo = c(
        "Staphylococcus aureus",
        "Enterococcus faecalis",
        "Escherichia coli",
        "Klebsiella pneumoniae",
        "Pseudomonas aeruginosa"
      ),
      VAN = "-", # Vancomycin
      AMX = "-", # Amoxicillin
      COL = "-", # Colistin
      CAZ = "-", # Ceftazidime
      CXM = "-", # Cefuroxime
      PEN = "S", # Benzylenicillin
      FOX = "S" # Cefoxitin
    )

    data

mo | VAN | AMX | COL | CAZ | CXM | PEN | FOX
--- | --- | --- | --- | --- | --- | --- | ---
Staphylococcus aureus | - | - | - | - | - | S | S
Enterococcus faecalis | - | - | - | - | - | S | S
Escherichia coli | - | - | - | - | - | S | S
Klebsiella pneumoniae | - | - | - | - | - | S | S
Pseudomonas aeruginosa | - | - | - | - | - | S | S

    eucast_rules(data, overwrite = TRUE)

mo | VAN | AMX | COL | CAZ | CXM | PEN | FOX
--- | --- | --- | --- | --- | --- | --- | ---
Staphylococcus aureus | - | S | R | R | S | S | S
Enterococcus faecalis | - | - | R | R | R | S | R
Escherichia coli | R | - | - | - | - | R | S
Klebsiella pneumoniae | R | R | - | - | - | R | S
Pseudomonas aeruginosa | R | R | - | - | R | R | R