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CKD staging (GFR and albuminuria) and KDIGO risk

Source: R/ckd_stage.R
ckd_stage.Rd

Categorizes eGFR into G1-G5, albuminuria into A1-A3 (by UACR mg/g), and maps KDIGO risk.

Usage

ckd_stage(
  data,
  col_map,
  na_action = c("keep", "omit", "error"),
  check_extreme = FALSE,
  extreme_action = c("cap", "NA", "error"),
  verbose = FALSE
)

Arguments

data

Data frame with renal measures.

col_map

Named list with required key: eGFR; optional key: UACR.

na_action

One of:

  • "keep" (retain rows; stages become NA where inputs missing)

  • "omit" (drop rows with any missing eGFR/UACR that are mapped)

  • "error" (abort if any mapped input missing)

check_extreme

Logical; if TRUE, screen eGFR/UACR for extreme values.

extreme_action

One of:

  • "cap" - winsorize to bounds (eGFR: (0, 200); UACR: (0, 5000) mg/g)

  • "NA" - replace out-of-range with NA

  • "error" - abort on any out-of-range value

verbose

Logical; if TRUE, emits progress messages via hm_inform().

Value

Tibble with CKD_stage, Albuminuria_stage, KDIGO_risk.

References

Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group (2013). “KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease.” Kidney International Supplements, 3(1), 1–150. Guideline without reliable DOI metadata in Crossref; related synopsis PMID: 23732715, https://kdigo.org/guidelines/ckd-evaluation-and-management/.

Examples

df <- data.frame(eGFR = c(95, 50), UACR = c(10, 200))
ckd_stage(df, list(eGFR = "eGFR", UACR = "UACR"))
#> # A tibble: 2 × 3
#>   CKD_stage Albuminuria_stage KDIGO_risk
#>   <fct>     <fct>             <fct>     
#> 1 G1        A1                Low       
#> 2 G3a       A2                High