Data set containing reference data to interpret MIC and disk diffusion to R/SI values, according to international guidelines. Currently implemented guidelines are EUCAST (2011-2022) and CLSI (2011-2022). Use as.rsi()
to transform MICs or disks measurements to R/SI values.
rsi_translation
A data.frame with 20,369 observations and 11 variables:
guideline
Name of the guideline
method
Either "DISK" or "MIC"
site
Body site, e.g. "Oral" or "Respiratory"
mo
Microbial ID, see as.mo()
rank_index
Taxonomic rank index of mo
from 1 (subspecies/infraspecies) to 5 (unknown microorganism)
ab
Antibiotic ID, see as.ab()
ref_tbl
Info about where the guideline rule can be found
disk_dose
Dose of the used disk diffusion method
breakpoint_S
Lowest MIC value or highest number of millimetres that leads to "S"
breakpoint_R
Highest MIC value or lowest number of millimetres that leads to "R"
uti
A logical value (TRUE
/FALSE
) to indicate whether the rule applies to a urinary tract infection (UTI)
Overview of the data set:
head(rsi_translation)
## guideline method site mo rank_index ab ref_tbl disk_dose
## 1 EUCAST 2022 MIC <NA> F_ASPRG_MGTS 2 AMB Aspergillus <NA>
## 2 EUCAST 2022 MIC <NA> F_ASPRG_NIGR 2 AMB Aspergillus <NA>
## 3 EUCAST 2022 MIC <NA> F_CANDD 3 AMB Candida <NA>
## 4 EUCAST 2022 MIC <NA> F_CANDD_ALBC 2 AMB Candida <NA>
## 5 EUCAST 2022 MIC <NA> F_CANDD_DBLN 2 AMB Candida <NA>
## 6 EUCAST 2022 MIC <NA> F_CANDD_KRUS 2 AMB Candida <NA>
## breakpoint_S breakpoint_R uti
## 1 1 1 FALSE
## 2 1 1 FALSE
## 3 1 1 FALSE
## 4 1 1 FALSE
## 5 1 1 FALSE
## 6 1 1 FALSE
The repository of this AMR
package contains a file comprising this exact data set: https://github.com/msberends/AMR/blob/main/data-raw/rsi_translation.txt. This file allows for machine reading EUCAST and CLSI guidelines, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically and the mo
and ab
columns have been transformed to contain the full official names instead of codes.
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR
package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.
On our website https://msberends.github.io/AMR/ you can find a comprehensive tutorial about how to conduct AMR data analysis, the complete documentation of all functions and an example analysis using WHONET data.