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Calculates renal impairment categories based on Renal Function Estimator

rfc.Rd

This function categorizes renal function based on estimated glomerular filtration rate (eGFR), creatinine clearance, or other renal function estimators. It supports both clinical and regulatory categorization standards and can convert between absolute (mL/min) and relative (mL/min/1.73m²) units using body surface area.

Usage

rfc(
  estimator = NULL,
  absolute_units = NULL,
  bsa = NULL,
  category_standard = c("regulatory", "clinical")
)

Arguments

estimator

Numeric vector of renal function estimator values (eGFR, CrCL, etc.)

absolute_units

Logical indicating if estimator units are mL/min (TRUE) or mL/min/1.73m² (FALSE)

bsa

Numeric vector of body surface area in m² for unit conversion. Required when converting between absolute and relative units

category_standard

Character string specifying categorization standard: "regulatory" (default) or "clinical"

Value

Integer vector of renal impairment categories (1-4 for regulatory, 1-5 for clinical). Returns -999 for missing values.

Details

The function applies different categorization schemes based on the category_standard:

Regulatory categories (uses mL/min):

  • 1: Normal: ≥90 mL/min

  • 2: Mild impairment: 60-89 mL/min

  • 3: Moderate impairment: 30-59 mL/min

  • 4: Severe impairment: <30 mL/min

Clinical categories (uses mL/min/1.73m²):

  • 1: Normal: ≥90 mL/min/1.73m²

  • 2: Mild impairment: 60-89 mL/min/1.73m²

  • 3: Moderate impairment: 30-59 mL/min/1.73m²

  • 4: Severe impairment: 15-29 mL/min/1.73m²

  • 5: End-stage: <15 mL/min/1.73m²

When unit conversion is required, the function uses:

  • Absolute to relative: relative = 1.73 (absolute / bsa)

  • Relative to absolute: absolute = relative (bsa / 1.73)

See also

egfr for calculating eGFR, crcl for creatinine clearance, bsa for body surface area calculation

Examples

# Regulatory categories with absolute units (creatinine clearance)
rfc(estimator = c(95, 75, 45, 25), absolute_units = TRUE)
#> [1] 1 2 3 4

# Clinical categories with relative units (eGFR)
rfc(
  estimator = c(95, 75, 45, 25, 10),
  absolute_units = FALSE,
  category_standard = "clinical"
)
#> [1] 1 2 3 4 5

# Convert relative eGFR to regulatory categories
rfc(
  estimator = 65,
  absolute_units = FALSE,
  bsa = 1.8
)
#> [1] 2

# Pipeline example with realistic data
df <- data.frame(
  ID = 1:4,
  SEX = c("F", "M", "F", "M"),
  AGE = c(65, 45, 70, 50),
  CREAT = c(1.2, 0.9, 1.5, 1.1),
  WEIGHT = c(70, 80, 60, 85),
  HEIGHT = c(165, 175, 160, 180),
  RACE = c("WHITE", "BLACK", "OTHER", "ASIAN")
)

library(dplyr)
df %>%
  mutate(
    EGFR = egfr(is_female(SEX), is_black(RACE), AGE, CREAT),
    BSA = bsa(WEIGHT, HEIGHT, method = "Dubois"),
    # Clinical categories using eGFR directly
    BRFC_CLINICAL = rfc(EGFR, FALSE, category_standard = "clinical"),
    # Regulatory categories converting eGFR to absolute
    BRFC_REGULATORY = rfc(EGFR, FALSE, BSA)
  )
#>   ID SEX AGE CREAT WEIGHT HEIGHT  RACE      EGFR      BSA BRFC_CLINICAL
#> 1  1   F  65   1.2     70    165 WHITE  47.38724 1.770960             3
#> 2  2   M  45   0.9     80    175 BLACK 119.12934 1.956060             1
#> 3  3   F  70   1.5     60    160 OTHER  34.93361 1.622063             3
#> 4  4   M  50   1.1     85    180 ASIAN  77.86046 2.048528             2
#>   BRFC_REGULATORY
#> 1               3
#> 2               1
#> 3               3
#> 4               1
df
#>   ID SEX AGE CREAT WEIGHT HEIGHT  RACE
#> 1  1   F  65   1.2     70    165 WHITE
#> 2  2   M  45   0.9     80    175 BLACK
#> 3  3   F  70   1.5     60    160 OTHER
#> 4  4   M  50   1.1     85    180 ASIAN