What are EUCAST rules? The European Committee on Antimicrobial Susceptibility Testing (EUCAST) states on their website:
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.
In Europe, a lot of medical microbiological laboratories already apply these rules (Brown et al., 2015). Our package features their latest insights on intrinsic resistance and exceptional phenotypes (version 10.0, 2020). Moreover, the
eucast_rules() function we use for this purpose can also apply additional rules, like forcing
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, practically every strain of Klebsiella is resistant to ampicillin.
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 solve this, that can be applied using
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 part of the
eucast_rules() function as well:
data <- data.frame(mo = c("Staphylococcus aureus", "Enterococcus faecalis", "Escherichia coli", "Klebsiella pneumoniae", "Pseudomonas aeruginosa"), VAN = "-", # Vancomycin AMX = "-", # Amoxicillin COL = "-", # Colistin CAZ = "-", # Ceftazidime CXM = "-", # Cefuroxime PEN = "S", # Penicillin G FOX = "S", # Cefoxitin stringsAsFactors = FALSE)
# Warning: Not all columns with antimicrobial results are of class <rsi>. # Transform eligible columns to class <rsi> on beforehand: your_data %>% mutate_if(is.rsi.eligible, as.rsi)