How to apply EUCAST rules

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