admiral (version 1.1.1)

compute_egfr: Compute Estimated Glomerular Filtration Rate (eGFR) for Kidney Function

Description

Compute Kidney Function Tests:

• Estimated Creatinine Clearance (CRCL) by Cockcroft-Gault equation

• Estimated Glomerular Filtration Rate (eGFR) by CKD-EPI or MDRD equations

Usage

compute_egfr(creat, creatu = "SI", age, weight, sex, race = NULL, method)

Value

A numeric vector of egfr values

Arguments

creat

Creatinine

A numeric vector is expected.

creatu

Creatinine Units

A character vector is expected.

Default: "SI"

Expected Values: "SI", "CV", "umol/L", "mg/dL"

age

Age (years)

A numeric vector is expected.

weight

Weight (kg)

A numeric vector is expected if method = "CRCL"

sex

Gender

A character vector is expected.

Expected Values: "M", "F"

race

Race

A character vector is expected if method = "MDRD"

Expected Values: "BLACK OR AFRICAN AMERICAN" and others

method

Method

A character vector is expected.

Expected Values: "CRCL", "CKD-EPI", "MDRD"

Details

Calculates an estimate of Glomerular Filtration Rate (eGFR)

CRCL Creatinine Clearance (Cockcroft-Gault)

For Creatinine in umol/L:

$$\frac{(140 - age) \times weight(kg) \times constant}{Serum\:Creatinine(\mu mol/L)}$$

$$Constant = 1.04\:for\:females, 1.23\:for\:males$$

For Creatinine in mg/dL:

$$\frac{(140 - age) \times weight(kg) \times (0.85\:if\:female)}{72 \times Serum\:Creatinine(mg/dL)}$$

units = mL/min

CKD-EPI Chronic Kidney Disease Epidemiology Collaboration formula

$$eGFR = 142 \times min(SCr/{\kappa}, 1)^{\alpha} \times max(SCr/{\kappa}, 1)^{-1.200} \times 0.9938^{Age} \times 1.012 [if\:female]$$

SCr = standardized serum creatinine in mg/dL (Note SCr(mg/dL) = Creat(umol/L) / 88.42)

$$\kappa$$ = 0.7 (females) or 0.9 (males) $$\alpha$$ = -0.241 (female) or -0.302 (male) units = mL/min/1.73 m2

MDRD Modification of Diet in Renal Disease formula

$$eGFR = 175 \times (SCr)^{-1.154} \times (age)^{-0.203} \times 0.742 [if\:female] \times 1.212 [if\:Black]$$

SCr = standardized serum creatinine in mg/dL (Note SCr(mg/dL) = Creat(umol/L) / 88.42)

units = mL/min/1.73 m2

See Also

BDS-Findings Functions that returns a vector: compute_bmi(), compute_bsa(), compute_framingham(), compute_map(), compute_qtc(), compute_qual_imputation(), compute_qual_imputation_dec(), compute_rr(), compute_scale()

Examples

compute_egfr(
  creat = 90, creatu = "umol/L", age = 53, weight = 85, sex = "M", method = "CRCL"
)

compute_egfr(
  creat = 90, creatu = "umol/L", age = 53, sex = "M", race = "ASIAN", method = "MDRD"
)

compute_egfr(
  creat = 70, creatu = "umol/L", age = 52, sex = "F", race = "BLACK OR AFRICAN AMERICAN",
  method = "MDRD"
)

compute_egfr(
  creat = 90, creatu = "umol/L", age = 53, sex = "M", method = "CKD-EPI"
)


base <- tibble::tribble(
  ~STUDYID, ~USUBJID, ~AGE, ~SEX, ~RACE, ~WTBL, ~CREATBL, ~CREATBLU,
  "P01", "P01-1001", 55, "M", "WHITE", 90.7, 96.3, "umol/L",
  "P01", "P01-1002", 52, "F", "BLACK OR AFRICAN AMERICAN", 68.5, 70, "umol/L",
  "P01", "P01-1003", 67, "M", "BLACK OR AFRICAN AMERICAN", 85.0, 77, "umol/L",
  "P01", "P01-1004", 76, "F", "ASIAN", 60.7, 65, "umol/L",
)

base %>%
  dplyr::mutate(
    CRCL_CG = compute_egfr(
      creat = CREATBL, creatu = CREATBLU, age = AGE, weight = WTBL, sex = SEX,
      method = "CRCL"
    ),
    EGFR_EPI = compute_egfr(
      creat = CREATBL, creatu = CREATBLU, age = AGE, weight = WTBL, sex = SEX,
      method = "CKD-EPI"
    ),
    EGFR_MDRD = compute_egfr(
      creat = CREATBL, creatu = CREATBLU, age = AGE, weight = WTBL, sex = SEX,
      race = RACE, method = "MDRD"
    ),
  )