as.rsi.RdInterpret MIC values according to EUCAST or CLSI, or clean up existing RSI values. This transforms the input to a new class rsi, which is an ordered factor with levels S < I < R. Invalid antimicrobial interpretations will be translated as NA with a warning.
as.rsi(x, ...) # S3 method for mic as.rsi(x, mo, ab, guideline = "EUCAST", ...) # S3 method for disk as.rsi(x, mo, ab, guideline = "EUCAST", ...) # S3 method for data.frame as.rsi(x, col_mo = NULL, guideline = "EUCAST", ...) is.rsi(x) is.rsi.eligible(x, threshold = 0.05)
| x | vector of values (for class |
|---|---|
| ... | parameters passed on to methods |
| mo | a microorganism code, generated with |
| ab | an antimicrobial code, generated with |
| guideline | defaults to the latest included EUCAST guideline, run |
| col_mo | column name of the IDs of the microorganisms (see |
| threshold | maximum fraction of invalid antimicrobial interpretations of |
Ordered factor with new class rsi
Run unique(AMR::rsi_translation$guideline) for a list of all supported guidelines.
After using as.rsi, you can use eucast_rules to (1) apply inferred susceptibility and resistance based on results of other antimicrobials and (2) apply intrinsic resistance based on taxonomic properties of a microorganism.
The function is.rsi.eligible returns TRUE when a columns contains at most 5% invalid antimicrobial interpretations (not S and/or I and/or R), and FALSE otherwise. The threshold of 5% can be set with the threshold parameter.
In 2019, EUCAST has decided to change the definitions of susceptibility testing categories S, I and R as shown below (http://www.eucast.org/newsiandr/). Results of several consultations on the new definitions are available on the EUCAST website under "Consultations".
S - Susceptible, standard dosing regimen: A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
I - Susceptible, increased exposure: A microorganism is categorised as "Susceptible, Increased exposure" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
R - Resistant: A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.
Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
This AMR package honours this new insight. Use portion_SI to determine antimicrobial susceptibility and count_SI to count susceptible isolates.
On our website https://msberends.gitlab.io/AMR you can find a tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.
# NOT RUN { rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370))) rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370), "A", "B", "C")) is.rsi(rsi_data) # this can also coerce combined MIC/RSI values: as.rsi("<= 0.002; S") # will return S # interpret MIC values as.rsi(x = as.mic(2), mo = as.mo("S. pneumoniae"), ab = "AMX", guideline = "EUCAST") as.rsi(x = as.mic(4), mo = as.mo("S. pneumoniae"), ab = "AMX", guideline = "EUCAST") plot(rsi_data) # for percentages barplot(rsi_data) # for frequencies library(clean) freq(rsi_data) # frequency table with informative header # using dplyr's mutate library(dplyr) example_isolates %>% mutate_at(vars(PEN:RIF), as.rsi) # fastest way to transform all columns with already valid AB results to class `rsi`: example_isolates %>% mutate_if(is.rsi.eligible, as.rsi) # default threshold of `is.rsi.eligible` is 5%. is.rsi.eligible(WHONET$`First name`) # fails, >80% is invalid is.rsi.eligible(WHONET$`First name`, threshold = 0.99) # succeeds # }