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Calculate a Suite of Renal Function, Injury, and Excretion Markers

Source: R/renal_markers.R
renal_markers.Rd

Given routine blood and urine assays, renal_markers() computes:

  • eGFR_cr: CKD-EPI creatinine equation (2009 variant; race factor retained to preserve prior behavior)

  • eGFR_cys: CKD-EPI cystatin C equation (if cystatin_C provided)

  • eGFR_combined: CKD-EPI combined creatinine+cystatin C (if both provided)

  • BUN_Cr_ratio: Blood urea nitrogen / serum creatinine

  • FE_Urea: Fractional excretion of urea (%)

  • NGAL, KIM1, NAG, Beta2Micro, IL18, L_FABP: pass-through urinary injury markers (if mapped)

Usage

renal_markers(
  data,
  col_map,
  na_action = c("keep", "omit", "error"),
  na_warn_prop = 0.2,
  check_extreme = FALSE,
  extreme_action = c("warn", "cap", "error", "ignore"),
  extreme_rules = NULL,
  verbose = FALSE
)

Arguments

data

A data.frame or tibble with renal lab data.

col_map

Named list mapping:

  • creatinine -> serum creatinine (mg/dL)

  • age -> age (years)

  • sex -> sex indicator (1 = male, 0 = female). Also accepts "male"/"female".

  • race -> race ("white", "black", or "other"). Also accepts common aliases.

  • BUN -> blood urea nitrogen (mg/dL)

  • optional cystatin_C -> serum cystatin C (mg/L)

  • optional urea_serum -> serum urea (mg/dL)

  • optional creatinine_urine -> urine creatinine (mg/dL)

  • optional urea_urine -> urine urea (mg/dL)

  • optional NGAL, KIM1, NAG, beta2_micro, IL18, L_FABP -> urine injury markers

na_action

One of c("keep","omit","error") for handling missing values in required inputs. Default "keep".

na_warn_prop

Proportion \([0,1]\) to trigger high-missingness warnings for required inputs. Default 0.2.

check_extreme

Logical; if TRUE, scans selected inputs for out-of-range values using simple heuristics. Default FALSE.

extreme_action

One of c("warn","cap","error","ignore") when extremes are detected. Default "warn".

extreme_rules

Optional named list of c(min,max) bounds keyed by input names (e.g., "creatinine","BUN","cystatin_C","urea_serum","creatinine_urine","urea_urine"). If NULL, built-in defaults are used.

verbose

Logical; if TRUE, prints progress messages and a completion summary.

Value

A tibble with columns: eGFR_cr, eGFR_cys, eGFR_combined, BUN_Cr_ratio, FE_Urea, NGAL, KIM1, NAG, Beta2Micro, IL18, L_FABP

Details

Robust validation is applied, including NA handling (na_action), high-missingness diagnostics, safe divisions with a consolidated zero-denominator warning, and an optional input extremes scan/cap. New arguments are appended for backward compatibility.

Expected units (no automatic conversion performed):

  • creatinine (serum): mg/dL

  • cystatin C (serum): mg/L

  • BUN (serum): mg/dL

  • urea_serum, urea_urine: mg/dL

  • creatinine_urine: mg/dL

References

Levey AS, Stevens LA, Schmid CH, others (2009). “A new equation to estimate glomerular filtration rate.” Annals of Internal Medicine, 150(9), 604–612. doi:10.7326/0003-4819-150-9-200905050-00006 . Inker LA, Schmid CH, Tighiouart H, others (2012). “Estimating glomerular filtration rate from serum cystatin C.” New England Journal of Medicine, 367(1), 20–29. doi:10.1056/NEJMoa1114248 . Inker LA, Eneanya ND, Coresh J, others (2021). “New creatinine- and cystatin C-based equations for estimating GFR without race.” New England Journal of Medicine, 385(19), 1737–1749. doi:10.1056/NEJMoa2102953 . Kaplan AA, Kohn OF (1992). “Fractional Excretion of Urea as a Guide to Renal Dysfunction.” American Journal of Nephrology, 12(1–2), 49–54. doi:10.1159/000168417 . Parikh CR, Coca SG, Thiessen-Philbrook H, others (2011). “Postoperative Biomarkers Predict Acute Kidney Injury and Poor Outcomes after Adult Cardiac Surgery.” Journal of the American Society of Nephrology, 22(12), 1737–1747. doi:10.1681/ASN.2010121302 . Vaidya VS, Ramirez V, Ichimura T, others (2010). “Kidney injury molecule-1 outperforms traditional biomarkers of kidney injury in preclinical biomarker qualification studies.” Nature Biotechnology, 28(5), 478–485. doi:10.1038/nbt.1623 . Portilla D, Dent C, Sugaya T, others (2008). “Urinary liver-type fatty acid-binding protein as a biomarker of acute kidney injury.” Kidney International, 73(4), 465–472. doi:10.1038/sj.ki.5002721 .

Examples

df <- tibble::tibble(Cr = 1.0, Age = 40, Sex = 1, Race = "white", BUN = 14)
cm <- list(creatinine = "Cr", age = "Age", sex = "Sex", race = "Race", BUN = "BUN")
renal_markers(df, cm)
#> # A tibble: 1 × 11
#>   eGFR_cr eGFR_cys eGFR_combined BUN_Cr_ratio FE_Urea  NGAL  KIM1   NAG
#>     <dbl>    <dbl>         <dbl>        <dbl>   <dbl> <dbl> <dbl> <dbl>
#> 1    93.7       NA            NA           14      NA    NA    NA    NA
#> # ℹ 3 more variables: Beta2Micro <dbl>, IL18 <dbl>, L_FABP <dbl>