Using KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease Volume 3 | Issue 1 | January 2013
Usage
eGFR(...)
# S3 method for class 'data.frame'
eGFR(
.data,
SCr = NULL,
SCysC = NULL,
Age = NULL,
height = NULL,
BUN = NULL,
male = NULL,
black = NULL,
pediatric = NULL,
...
)
# S3 method for class 'units'
eGFR(
SCr = NULL,
SCysC = NULL,
Age = NULL,
height = NULL,
BUN = NULL,
male = NULL,
black = NULL,
pediatric = NULL,
...
)
# S3 method for class 'numeric'
eGFR(
SCr = NULL,
SCysC = NULL,
Age = NULL,
height = NULL,
BUN = NULL,
male = NULL,
black = NULL,
pediatric = NULL,
...
)Arguments
- ...
Further optional arguments
- .data
(data.frame) A data.frame, optional
- SCr
Serum creatinine column name, or vector of units or numeric if
.datais not provided- SCysC
Serum Cystatin C column name, or vector of units or numeric if
.datais not provided- Age
Age of patient column name, or vector of units or numeric if
.datais not provided- height
Height of patient column name, or vector of units or numeric if
.datais not provided- BUN
Blood urea nitrogen column name, or vector of units or numeric if
.datais not provided- male
Male or not column name, or vector of logical (TRUE/FALSE) if
.datais not provided- black
Black race or not column name, or vector of logical (TRUE/FALSE) if
.datais not provided- pediatric
(logical) Pediatric or not column name, or vector of logical (TRUE/FALSE) if
.datais not provided
Value
(units) Estimated glomerular filtration rate (eGFR) of the same type provided (numeric or units in ml/min/1.73m2)
Details
Automatic selection of equation to estimation the Glomerular Filtration Rate (eGFR), based on input data
eGFR_adult_SCr(): 2009 CKD-EPI creatinine equationeGFR_adult_SCysC(): 2012 CKD-EPI cystatin C equationeGFR_adult_SCr_SCysC(): 2012 CKD-EPI creatinine-cystatin C equationeGFR_child_SCr(): Pediatric creatinine-based equationeGFR_child_SCr_BUN(): Pediatric creatinine-BUN equationeGFR_child_SCysC(): Pediatric cystatin C-based equation
See https://kdigo.org/guidelines/ckd-evaluation-and-management/ for more details
Examples
eGFR(eGFR_pt_data,
SCr = "SCr_", SCysC = "SCysC_",
Age = "Age_", height = "height_", BUN = "BUN_",
male = "male_", black = "black_", pediatric = "pediatric_"
)
#> Units: [mL/(min*1.73m^2)]
#> [1] 139.32466 161.68446 166.81886 150.52336 155.33226 171.35616 139.32466
#> [8] 66.77365 96.41798 150.52336 64.15027 99.04045 49.63420 161.68446
#> [15] 97.06854 53.62373 155.33226 99.70870 49.63420 66.77365 56.10368
#> [22] 53.62373 64.15027 57.62964 155.99874 173.48118 178.86404 168.53768
#> [29] 166.66552 183.72895 155.99874 71.64555 103.37985 168.53768 68.83077
#> [36] 106.19167 66.06766 173.48118 116.50660 71.37808 166.66552 119.67546
#> [43] 66.06766 71.64555 67.33849 71.37808 68.83077 69.17003 99.12000
#> [50] 148.21219 165.89761
eGFR_pt_data %>%
dplyr::mutate(eGFR = eGFR(
SCr = SCr_, SCysC = SCysC_,
Age = Age_, height = height_, BUN = BUN_,
male = male_, black = black_, pediatric = pediatric_
))
#> # A tibble: 51 × 11
#> SCr_ SCysC_ Age_ male_ black_ height_ BUN_ eGFR_calc_type_ eGFR_
#> [mg/dl] [mg/L] [years] <lgl> <lgl> [m] [mg/dl] <chr> [mL/…
#> 1 0.5 NA 20 FALSE FALSE NA NA eGFR_adult_SCr 139.
#> 2 NA 0.4 20 FALSE FALSE NA NA eGFR_adult_SCysC 162.
#> 3 0.5 0.4 20 FALSE FALSE NA NA eGFR_adult_SCr_SCy… 167.
#> 4 0.5 NA 30 FALSE TRUE NA NA eGFR_adult_SCr 150.
#> 5 NA 0.4 30 FALSE TRUE NA NA eGFR_adult_SCysC 155.
#> 6 0.5 0.4 30 FALSE TRUE NA NA eGFR_adult_SCr_SCy… 171.
#> 7 0.5 NA 20 FALSE FALSE NA NA eGFR_adult_SCr 139.
#> 8 NA 1.2 20 FALSE FALSE NA NA eGFR_adult_SCysC 66.8
#> 9 0.5 1.2 20 FALSE FALSE NA NA eGFR_adult_SCr_SCy… 96.4
#> 10 0.5 NA 30 FALSE TRUE NA NA eGFR_adult_SCr 150.
#> # ℹ 41 more rows
#> # ℹ 2 more variables: pediatric_ <lgl>, eGFR [mL/(min*1.73m^2)]