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These functions can be used to determine first weighted isolates by considering the phenotype for isolate selection (see first_isolate()). Using a phenotype-based method to determine first isolates is more reliable than methods that disregard phenotypes.

Usage

key_antimicrobials(
  x = NULL,
  col_mo = NULL,
  universal = c("ampicillin", "amoxicillin/clavulanic acid", "cefuroxime",
    "piperacillin/tazobactam", "ciprofloxacin", "trimethoprim/sulfamethoxazole"),
  gram_negative = c("gentamicin", "tobramycin", "colistin", "cefotaxime", "ceftazidime",
    "meropenem"),
  gram_positive = c("vancomycin", "teicoplanin", "tetracycline", "erythromycin",
    "oxacillin", "rifampin"),
  antifungal = c("anidulafungin", "caspofungin", "fluconazole", "miconazole", "nystatin",
    "voriconazole"),
  only_rsi_columns = FALSE,
  ...
)

all_antimicrobials(x = NULL, only_rsi_columns = FALSE, ...)

antimicrobials_equal(
  y,
  z,
  type = c("points", "keyantimicrobials"),
  ignore_I = TRUE,
  points_threshold = 2,
  ...
)

Arguments

x

a data.frame with antibiotics columns, like AMX or amox. Can be left blank to determine automatically

col_mo

column name of the IDs of the microorganisms (see as.mo()), defaults to the first column of class mo. Values will be coerced using as.mo().

universal

names of broad-spectrum antimicrobial agents, case-insensitive. Set to NULL to ignore. See Details for the default agents.

gram_negative

names of antibiotic agents for Gram-positives, case-insensitive. Set to NULL to ignore. See Details for the default agents.

gram_positive

names of antibiotic agents for Gram-negatives, case-insensitive. Set to NULL to ignore. See Details for the default agents.

antifungal

names of antifungal agents for fungi, case-insensitive. Set to NULL to ignore. See Details for the default agents.

only_rsi_columns

a logical to indicate whether only columns must be included that were transformed to class <rsi> (see as.rsi()) on beforehand (defaults to FALSE)

...

ignored, only in place to allow future extensions

y, z

character vectors to compare

type

type to determine weighed isolates; can be "keyantimicrobials" or "points", see Details

ignore_I

logical to indicate whether antibiotic interpretations with "I" will be ignored when type = "keyantimicrobials", see Details

points_threshold

minimum number of points to require before differences in the antibiogram will lead to inclusion of an isolate when type = "points", see Details

Details

The key_antimicrobials() and all_antimicrobials() functions are context-aware. This means that the x argument can be left blank if used inside a data.frame call, see Examples.

The function key_antimicrobials() returns a character vector with 12 antimicrobial results for every isolate. The function all_antimicrobials() returns a character vector with all antimicrobial results for every isolate. These vectors can then be compared using antimicrobials_equal(), to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (".") by key_antimicrobials() and ignored by antimicrobials_equal().

Please see the first_isolate() function how these important functions enable the 'phenotype-based' method for determination of first isolates.

The default antimicrobial agents used for all rows (set in universal) are:

  • Ampicillin

  • Amoxicillin/clavulanic acid

  • Cefuroxime

  • Ciprofloxacin

  • Piperacillin/tazobactam

  • Trimethoprim/sulfamethoxazole

The default antimicrobial agents used for Gram-negative bacteria (set in gram_negative) are:

  • Cefotaxime

  • Ceftazidime

  • Colistin

  • Gentamicin

  • Meropenem

  • Tobramycin

The default antimicrobial agents used for Gram-positive bacteria (set in gram_positive) are:

  • Erythromycin

  • Oxacillin

  • Rifampin

  • Teicoplanin

  • Tetracycline

  • Vancomycin

The default antimicrobial agents used for fungi (set in antifungal) are:

  • Anidulafungin

  • Caspofungin

  • Fluconazole

  • Miconazole

  • Nystatin

  • Voriconazole

See also

Examples

# `example_isolates` is a data set available in the AMR package.
# See ?example_isolates.

# output of the `key_antimicrobials()` function could be like this:
strainA <- "SSSRR.S.R..S"
strainB <- "SSSIRSSSRSSS"

# those strings can be compared with:
antimicrobials_equal(strainA, strainB, type = "keyantimicrobials")
#> [1] TRUE
# TRUE, because I is ignored (as well as missing values)

antimicrobials_equal(strainA, strainB, type = "keyantimicrobials", ignore_I = FALSE)
#> [1] FALSE
# FALSE, because I is not ignored and so the 4th [character] differs

# \donttest{
if (require("dplyr")) {
  # set key antibiotics to a new variable
  my_patients <- example_isolates %>%
    mutate(keyab = key_antimicrobials(antifungal = NULL)) %>% # no need to define `x`
    mutate(
      # now calculate first isolates
      first_regular = first_isolate(col_keyantimicrobials = FALSE),
      # and first WEIGHTED isolates
      first_weighted = first_isolate(col_keyantimicrobials = "keyab")
    )

  # Check the difference in this data set, 'weighted' results in more isolates:
  sum(my_patients$first_regular, na.rm = TRUE)
  sum(my_patients$first_weighted, na.rm = TRUE)
}
#> Including isolates from ICU.
#> Including isolates from ICU.
#> [1] 1395
# }