Codify AKI from Serum Creatinine and/or Urine Output

Using KDIGO Clinical Practice Guideline for Acute Kidney Injury Volume 2 | Issue 1 | March 2012

aki_staging(...)

# S3 method for data.frame
aki_staging(
  .data,
  SCr = NULL,
  bCr = NULL,
  UO = NULL,
  dttm = NULL,
  pt_id = NULL,
  ...
)

# S3 method for units
aki_staging(SCr = NULL, bCr = NULL, UO = NULL, dttm = NULL, pt_id = NULL, ...)

# S3 method for numeric
aki_staging(SCr = NULL, bCr = NULL, UO = NULL, dttm = NULL, pt_id = NULL, ...)

Arguments

...: Further optional arguments
.data: (data.frame) A data.frame, optional
SCr: Serum creatinine column name, or vector of units or numeric if .data is not provided
bCr: Baseline creatinine column name, or vector of units or numeric if .data is not provided
UO: Urine output column name, or vector of units or numeric if .data is not provided
dttm: DateTime column name, or vector of POSIXct if .data is not provided
pt_id: Patient ID column name, or vector of characters or factors if .data is not provided

Value

(ordered factor) AKI stages

Details

Provided a baseline creatinine, series of Serum Creatinine readings and/or Urine Output, aki_staging() calculates whether or not a patient has AKI. The staging (1, 2, 3) of AKI is returned.

When multiple columns are provided, aki_staging() will automatically calculate whether or not AKI has occurred using each KDIGO definition.

aki_bCr(): Staging of AKI based on baseline serum creatinine
aki_SCr(): Staging of AKI based on changes in serum creatinine
aki_UO(): Staging of AKI based on urine output

The most severe AKI stage is then returned.

See https://kdigo.org/guidelines/acute-kidney-injury/ for more details.

Examples

aki_staging(aki_pt_data, SCr = "SCr_", bCr = "bCr_", UO = "UO_", dttm = "dttm_", pt_id = "pt_id_")
#>  [1] No AKI      AKI Stage 1 AKI Stage 2 AKI Stage 2 AKI Stage 3 AKI Stage 3
#>  [7] No AKI      No AKI      AKI Stage 1 No AKI      No AKI      AKI Stage 1
#> [13] No AKI      No AKI      No AKI      AKI Stage 1 No AKI      AKI Stage 2
#> [19] AKI Stage 3 AKI Stage 1 AKI Stage 3 AKI Stage 2 No AKI      AKI Stage 1
#> [25] AKI Stage 3 AKI Stage 3 No AKI     
#> Levels: No AKI < AKI Stage 1 < AKI Stage 2 < AKI Stage 3

aki_pt_data %>%
  dplyr::mutate(aki = aki_staging(SCr = SCr_, bCr = bCr_, UO = UO_, dttm = dttm_, pt_id = pt_id_))
#> # A tibble: 27 × 8
#>       SCr_    bCr_ pt_id_ dttm_                 UO_ aki_staging_type aki_  aki  
#>    [mg/dl] [mg/dl] <chr>  <dttm>              [ml/… <chr>            <ord> <ord>
#>  1     2       1.5 NA     NA                     NA aki_bCr          No A… No A…
#>  2     2.5     1.5 NA     NA                     NA aki_bCr          AKI … AKI …
#>  3     3       1.5 NA     NA                     NA aki_bCr          AKI … AKI …
#>  4     3.5     1.5 NA     NA                     NA aki_bCr          AKI … AKI …
#>  5     4       1.5 NA     NA                     NA aki_bCr          AKI … AKI …
#>  6     4.5     1.5 NA     NA                     NA aki_bCr          AKI … AKI …
#>  7     3.4    NA   pt1    2020-10-23 09:00:00    NA aki_SCr          No A… No A…
#>  8     3.9    NA   pt1    2020-10-25 21:00:00    NA aki_SCr          No A… No A…
#>  9     3      NA   pt1    2020-10-20 09:00:00    NA aki_SCr          AKI … AKI …
#> 10     3.4    NA   pt2    2020-10-18 22:00:00    NA aki_SCr          No A… No A…
#> # ℹ 17 more rows