Calculate Creatinine Clearance Using Cockcroft-Gault Equation

Calculate Creatinine Clearance Using Cockcroft-Gault Equation

Usage

crcl(sexf, age, creat, weight)

Arguments

sexf

bool of sex of subject. Female: True, Male: False

age

age of subject (years)

creat

serum creatinine levels (mg/dL)

weight

weight of subject (kg)

Value

CrCl (mL/min)

Details

The Cockcroft-Gault equation: $$CrCl = F \cdot \frac{(140 - A) \cdot W}{72 \cdot S_{cr}}$$

where:

• \(A\) = age (years)

• \(W\) = weight (kg)

• \(S_{cr}\) = serum creatinine (mg/dL)

• \(F\) = 0.85 (female) or 1 (male)

See also

Other renal_function: aegfr(), ckdepi_2009_egfr(), ckdepi_2021_egfr(), ckdepi_2021_egfr_cystatin(), egfr(), mdrd_egfr(), rfc(), schwartz_egfr()

Examples

crcl(FALSE, 20, 10, 70)
#> [1] 11.66667
#> attr(,"units")
#> [1] "mL/min"

df <- data.frame(
  "ID" = c(1, 1, 1, 1, 2, 2, 2, 2),
  "SEX" = c("F", "F", "F", "F", "M", "M", "M", "M"),
  "RACE" = c("WHITE", "WHITE", "WHITE", "WHITE", "BLACK", "BLACK", "BLACK", "BLACK"),
  "AGE" = c(24, 24, 24, 24, 22, 22, 22, 22),
  "CREAT" = c(1, 1, 1, 1, 4, 4, 4, 4),
  "WEIGHT" = c(70, 70, 70, 70, 65, 65, 65, 65)
)

df <- df %>%
  dplyr::group_by(ID) %>%
  dplyr::mutate(CRCL = crcl(is_female(SEX), AGE, CREAT, WEIGHT))
df
#> # A tibble: 8 × 7
#> # Groups:   ID [2]
#>      ID SEX   RACE    AGE CREAT WEIGHT  CRCL
#>   <dbl> <chr> <chr> <dbl> <dbl>  <dbl> <dbl>
#> 1     1 F     WHITE    24     1     70  95.9
#> 2     1 F     WHITE    24     1     70  95.9
#> 3     1 F     WHITE    24     1     70  95.9
#> 4     1 F     WHITE    24     1     70  95.9
#> 5     2 M     BLACK    22     4     65  26.6
#> 6     2 M     BLACK    22     4     65  26.6
#> 7     2 M     BLACK    22     4     65  26.6
#> 8     2 M     BLACK    22     4     65  26.6