Determine Bug-Drug Combinations — bug_drug

Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use format() on the result to prettify it to a publishable/printable format, see Examples.

Usage

bug_drug_combinations(x, col_mo = NULL, FUN = mo_shortname, ...)

# S3 method for bug_drug_combinations
format(
  x,
  translate_ab = "name (ab, atc)",
  language = get_AMR_locale(),
  minimum = 30,
  combine_SI = TRUE,
  add_ab_group = TRUE,
  remove_intrinsic_resistant = FALSE,
  decimal.mark = getOption("OutDec"),
  big.mark = ifelse(decimal.mark == ",", " ", ","),
  ...
)

Arguments

x: a data set with antibiotic columns, such as amox, AMX and AMC
col_mo: column name of the names or codes of the microorganisms (see as.mo()), defaults to the first column of class mo. Values will be coerced using as.mo().
FUN: the function to call on the mo column to transform the microorganism codes, defaults to mo_shortname()
...: arguments passed on to FUN
translate_ab: a character of length 1 containing column names of the antibiotics data set
language: language of the returned text, defaults to system language (see get_AMR_locale()) and can also be set with the option AMR_locale. Use language = NULL or language = "" to prevent translation.
minimum: the minimum allowed number of available (tested) isolates. Any isolate count lower than minimum will return NA with a warning. The default number of 30 isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.
combine_SI: a logical to indicate whether values S and I should be summed, so resistance will be based on only R, defaults to TRUE
add_ab_group: a logical to indicate where the group of the antimicrobials must be included as a first column
remove_intrinsic_resistant: logical to indicate that rows and columns with 100% resistance for all tested antimicrobials must be removed from the table
decimal.mark: the character to be used to indicate the numeric decimal point.
big.mark: character; if not empty used as mark between every big.interval decimals before (hence big) the decimal point.

Value

The function bug_drug_combinations() returns a data.frame with columns "mo", "ab", "S", "I", "R" and "total".

Details

The function format() calculates the resistance per bug-drug combination. Use combine_SI = TRUE (default) to test R vs. S+I and combine_SI = FALSE to test R+I vs. S.

Examples

# \donttest{
#' # example_isolates is a data set available in the AMR package.
# run ?example_isolates for more info.
example_isolates
#> # A tibble: 2,000 × 46
#>    date       patient   age gender ward     mo           PEN   OXA   FLC   AMX  
#>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir> <sir> <sir> <sir>
#>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA   
#>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R     NA    NA    NA   
#>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA   
#>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA   
#>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA   
#>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA   
#>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R    
#>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R     NA    S     R    
#>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R     NA    R     NA   
#> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R     NA    S     NA   
#> # … with 1,990 more rows, and 36 more variables: AMC <sir>, AMP <sir>,
#> #   TZP <sir>, CZO <sir>, FEP <sir>, CXM <sir>, FOX <sir>, CTX <sir>,
#> #   CAZ <sir>, CRO <sir>, GEN <sir>, TOB <sir>, AMK <sir>, KAN <sir>,
#> #   TMP <sir>, SXT <sir>, NIT <sir>, FOS <sir>, LNZ <sir>, CIP <sir>,
#> #   MFX <sir>, VAN <sir>, TEC <sir>, TCY <sir>, TGC <sir>, DOX <sir>,
#> #   ERY <sir>, CLI <sir>, AZM <sir>, IPM <sir>, MEM <sir>, MTR <sir>,
#> #   CHL <sir>, COL <sir>, MUP <sir>, RIF <sir>

x <- bug_drug_combinations(example_isolates)
format(x, translate_ab = "name (atc)")
#> # A tibble: 39 × 12
#>    Group     Drug  CoNS  E. co…¹ E. fa…² K. pn…³ P. ae…⁴ P. mi…⁵ S. au…⁶ S. ep…⁷
#>    <chr>     <chr> <chr> <chr>   <chr>   <chr>   <chr>   <chr>   <chr>   <chr>  
#>  1 "Aminogl… Amik… "100… "  0.0… "100.0… ""      ""      ""      ""      "100.0…
#>  2 ""        Gent… " 13… "  2.0… "100.0… " 10.3… "  0.0… "  5.9… "  0.9… " 21.5…
#>  3 ""        Kana… "100… ""      "100.0… ""      "100.0… ""      ""      "100.0…
#>  4 ""        Tobr… " 78… "  2.6… "100.0… " 10.3… "  0.0… "  5.9… "  2.3… " 49.4…
#>  5 "Ampheni… Chlo… ""    ""      ""      ""      "100.0… ""      "  0.0… "  3.1…
#>  6 "Antimyc… Rifa… ""    "100.0… ""      "100.0… "100.0… "100.0… "  0.0… "  2.7…
#>  7 "Beta-la… Amox… " 93… " 50.0… ""      "100.0… "100.0… ""      " 93.9… " 98.9…
#>  8 ""        Amox… " 42… " 13.1… ""      " 10.3… "100.0… "  2.8… "  0.4… " 54.5…
#>  9 ""        Ampi… " 93… " 50.0… ""      "100.0… "100.0… ""      " 93.9… " 98.9…
#> 10 ""        Benz… " 77… "100.0… ""      "100.0… "100.0… "100.0… " 80.9… " 89.4…
#> # … with 29 more rows, 2 more variables: `S. hominis` <chr>,
#> #   `S. pneumoniae` <chr>, and abbreviated variable names ¹`E. coli`,
#> #   ²`E. faecalis`, ³`K. pneumoniae`, ⁴`P. aeruginosa`, ⁵`P. mirabilis`,
#> #   ⁶`S. aureus`, ⁷`S. epidermidis`

# Use FUN to change to transformation of microorganism codes
bug_drug_combinations(example_isolates,
  FUN = mo_gramstain
)
#> # A tibble: 120 × 6
#>    mo            ab        S     I     R total
#>  * <chr>         <chr> <int> <int> <int> <int>
#>  1 Gram-negative AMC     463    89   174   726
#>  2 Gram-negative AMK     251     0     5   256
#>  3 Gram-negative AMP     226     0   405   631
#>  4 Gram-negative AMX     226     0   405   631
#>  5 Gram-negative AZM       1     2   696   699
#>  6 Gram-negative CAZ     607     0    27   634
#>  7 Gram-negative CHL       1     0    30    31
#>  8 Gram-negative CIP     610    11    63   684
#>  9 Gram-negative CLI      18     1   709   728
#> 10 Gram-negative COL     309     0    78   387
#> # … with 110 more rows
#> Use 'format()' on this result to get a publishable/printable format.

bug_drug_combinations(example_isolates,
  FUN = function(x) {
    ifelse(x == as.mo("Escherichia coli"),
      "E. coli",
      "Others"
    )
  }
)
#> # A tibble: 80 × 6
#>    mo      ab        S     I     R total
#>  * <chr>   <chr> <int> <int> <int> <int>
#>  1 E. coli AMC     332    74    61   467
#>  2 E. coli AMK     171     0     0   171
#>  3 E. coli AMP     196     0   196   392
#>  4 E. coli AMX     196     0   196   392
#>  5 E. coli AZM       0     0   467   467
#>  6 E. coli CAZ     449     0    11   460
#>  7 E. coli CHL       0     0     0     0
#>  8 E. coli CIP     398     1    57   456
#>  9 E. coli CLI       0     0   467   467
#> 10 E. coli COL     240     0     0   240
#> # … with 70 more rows
#> Use 'format()' on this result to get a publishable/printable format.
# }