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Data Set with Clinical Breakpoints for SIR Interpretation

Source: R/data.R
clinical_breakpoints.Rd

Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. Currently implemented guidelines are EUCAST (2011-2023) and CLSI (2011-2023). Use as.sir() to transform MICs or disks measurements to SIR values.

Usage

clinical_breakpoints

Format

A tibble with 42 599 observations and 12 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"

  • ecoff
    Epidemiological cut-off (ECOFF) value, used in antimicrobial susceptibility testing to differentiate between wild-type and non-wild-type strains of bacteria or fungi (use as.sir(..., ecoff = TRUE) to interpret raw data using ECOFF values)

  • uti
    A logical value (TRUE/FALSE) to indicate whether the rule applies to a urinary tract infection (UTI)

Details

Clinical breakpoints are validated through WHONET, a free desktop Windows application developed and supported by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance. More can be read on their website.

Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit our website for the download links. The actual files are of course available on our GitHub repository.

They allow for machine reading EUCAST and CLSI guidelines, which is almost impossible with the MS Excel and PDF files distributed by EUCAST and CLSI.

See also

intrinsic_resistant

Examples

clinical_breakpoints
#> # A tibble: 42,599 × 12
#>    guideline   method site  mo           rank_index ab   ref_tbl       disk_dose
#>    <chr>       <chr>  <chr> <mo>              <dbl> <ab> <chr>         <chr>    
#>  1 EUCAST 2023 MIC    NA    F_ASPRG_MGTS          2 AMB  Aspergillus   NA       
#>  2 EUCAST 2023 MIC    NA    F_ASPRG_NIGR          2 AMB  Aspergillus   NA       
#>  3 EUCAST 2023 MIC    NA    F_CANDD_ALBC          2 AMB  Candida       NA       
#>  4 EUCAST 2023 MIC    NA    F_CANDD_DBLN          2 AMB  Candida       NA       
#>  5 EUCAST 2023 MIC    NA    F_CANDD_GLBR          2 AMB  Candida       NA       
#>  6 EUCAST 2023 MIC    NA    F_CANDD_KRUS          2 AMB  Candida       NA       
#>  7 EUCAST 2023 MIC    NA    F_CANDD_PRPS          2 AMB  Candida       NA       
#>  8 EUCAST 2023 MIC    NA    F_CANDD_TRPC          2 AMB  Candida       NA       
#>  9 EUCAST 2023 MIC    NA    F_CRYPT_NFRM          2 AMB  Candida       NA       
#> 10 EUCAST 2023 MIC    NA    B_ANAER-NEG           6 AMC  Gram-negativ… NA       
#> # ℹ 42,589 more rows
#> # ℹ 4 more variables: breakpoint_S <dbl>, breakpoint_R <dbl>, ecoff <dbl>,
#> #   uti <lgl>