as.mic: Transform Input to Minimum Inhibitory Concentrations (MIC)

In AMR: Antimicrobial Resistance Data Analysis

Transform Input to Minimum Inhibitory Concentrations (MIC)

Description

This transforms vectors to a new class mic, which treats the input as decimal numbers, while maintaining operators (such as ">=") and only allowing valid MIC values known to the field of (medical) microbiology.

Usage

as.mic(x, na.rm = FALSE)

NA_mic_

is.mic(x)

## S3 method for class 'mic'
droplevels(x, as.mic = FALSE, ...)

Arguments

x	a character or numeric vector
na.rm	a logical indicating whether missing values should be removed
as.mic	a logical to indicate whether the mic class should be kept - the default is FALSE
...	arguments passed on to methods

Details

To interpret MIC values as SIR values, use as.sir() on MIC values. It supports guidelines from EUCAST (2011-2023) and CLSI (2011-2023).

This class for MIC values is a quite a special data type: formally it is an ordered factor with valid MIC values as factor levels (to make sure only valid MIC values are retained), but for any mathematical operation it acts as decimal numbers:

x <- random_mic(10)
x
#> Class 'mic'
#>  [1] 16     1      8      8      64     >=128  0.0625 32     32     16

is.factor(x)
#> [1] TRUE

x[1] * 2
#> [1] 32

median(x)
#> [1] 26

This makes it possible to maintain operators that often come with MIC values, such ">=" and "<=", even when filtering using numeric values in data analysis, e.g.:

x[x > 4]
#> Class 'mic'
#> [1] 16    8     8     64    >=128 32    32    16

df <- data.frame(x, hospital = "A")
subset(df, x > 4) # or with dplyr: df %>% filter(x > 4)
#>        x hospital
#> 1     16        A
#> 5     64        A
#> 6  >=128        A
#> 8     32        A
#> 9     32        A
#> 10    16        A

The following generic functions are implemented for the MIC class: !, !=, %%, %/%, &, *, +, -, /, <, <=, ==, >, >=, ^, |, abs(), acos(), acosh(), all(), any(), asin(), asinh(), atan(), atanh(), ceiling(), cos(), cosh(), cospi(), cummax(), cummin(), cumprod(), cumsum(), digamma(), exp(), expm1(), floor(), gamma(), lgamma(), log(), log1p(), log2(), log10(), max(), mean(), min(), prod(), range(), round(), sign(), signif(), sin(), sinh(), sinpi(), sqrt(), sum(), tan(), tanh(), tanpi(), trigamma() and trunc(). Some functions of the stats package are also implemented: median(), quantile(), mad(), IQR(), fivenum(). Also, boxplot.stats() is supported. Since sd() and var() are non-generic functions, these could not be extended. Use mad() as an alternative, or use e.g. sd(as.numeric(x)) where x is your vector of MIC values.

Using as.double() or as.numeric() on MIC values will remove the operators and return a numeric vector. Do not use as.integer() on MIC values as by the R convention on factors, it will return the index of the factor levels (which is often useless for regular users).

Use droplevels() to drop unused levels. At default, it will return a plain factor. Use droplevels(..., as.mic = TRUE) to maintain the mic class.

NA_mic_ is a missing value of the new mic class, analogous to e.g. base R's NA_character_.

Value

Ordered factor with additional class mic, that in mathematical operations acts as decimal numbers. Bare in mind that the outcome of any mathematical operation on MICs will return a numeric value.

See Also

as.sir()

Examples

mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
mic_data
is.mic(mic_data)

# this can also coerce combined MIC/SIR values:
as.mic("<=0.002; S")

# mathematical processing treats MICs as numeric values
fivenum(mic_data)
quantile(mic_data)
all(mic_data < 512)

# interpret MIC values
as.sir(
  x = as.mic(2),
  mo = as.mo("Streptococcus pneumoniae"),
  ab = "AMX",
  guideline = "EUCAST"
)
as.sir(
  x = as.mic(c(0.01, 2, 4, 8)),
  mo = as.mo("Streptococcus pneumoniae"),
  ab = "AMX",
  guideline = "EUCAST"
)

# plot MIC values, see ?plot
plot(mic_data)
plot(mic_data, mo = "E. coli", ab = "cipro")

if (require("ggplot2")) {
  autoplot(mic_data, mo = "E. coli", ab = "cipro")
}
if (require("ggplot2")) {
  autoplot(mic_data, mo = "E. coli", ab = "cipro", language = "nl") # Dutch
}

AMR documentation built on Oct. 22, 2023, 1:08 a.m.