The function grade_hyper produces %GRADE hyperglycemia values in a tibble object.
Arguments
- data
DataFrame object with column names "id", "time", and "gl", or numeric vector of glucose values.
- upper
Upper bound used for hyperglycemia cutoff, in mg/dL. Default is 140.
Value
If a data.frame object is passed, then a tibble object with two columns: subject id and corresponding %GRADE hyperglycemia value is returned. If a vector of glucose values is passed, then a tibble object with just the %GRADE hyperglycemia value is returned. as.numeric() can be wrapped around the latter to output just a numeric value.
Details
A tibble object with 1 row for each subject, a column for subject id and a column for %GRADE hyperglycemia values is returned. NA glucose values are omitted from the calculation of the %GRADE hyperglycemia values.
%GRADE hyperglycemia is determined by calculating the percentage of GRADE score (see grade function) attributed to hyperglycemic glucose values.
References
Hill et al. (2007): A method for assessing quality of control from glucose profiles Diabetic Medicine 24 .753-758, doi:10.1111/j.1464-5491.2007.02119.x .
Examples
data(example_data_1_subject)
grade_hyper(example_data_1_subject)
#> # A tibble: 1 × 2
#> id GRADE_hyper
#> <fct> <dbl>
#> 1 Subject 1 71.7
grade_hyper(example_data_1_subject, upper = 180)
#> # A tibble: 1 × 2
#> id GRADE_hyper
#> <fct> <dbl>
#> 1 Subject 1 33.1
data(example_data_5_subject)
grade_hyper(example_data_5_subject)
#> # A tibble: 5 × 2
#> id GRADE_hyper
#> <fct> <dbl>
#> 1 Subject 1 71.7
#> 2 Subject 2 99.4
#> 3 Subject 3 79.6
#> 4 Subject 4 65.5
#> 5 Subject 5 93.3
grade_hyper(example_data_5_subject, upper = 160)
#> # A tibble: 5 × 2
#> id GRADE_hyper
#> <fct> <dbl>
#> 1 Subject 1 48.5
#> 2 Subject 2 96.3
#> 3 Subject 3 65.7
#> 4 Subject 4 39.3
#> 5 Subject 5 82.0