The function hyper_index produces Hyperglycemia Index values in a tibble object.
Arguments
- data
DataFrame object with column names "id", "time", and "gl", or numeric vector of glucose values.
- ULTR
Upper Limit of Target Range, default value is 140 mg/dL.
- a
Exponent, generally in the range from 1.0 to 2.0, default value is 1.1.
- c
Scaling factor, to display Hyperglycemia Index, Hypoglycemia Index, and IGC on approximately the same numerical range as measurements of HBGI, LBGI and GRADE, default value is 30.
Value
If a data.frame object is passed, then a tibble object with two columns: subject id and corresponding Hyperglycemia Index value is returned. If a vector of glucose values is passed, then a tibble object with just the Hyperglycemia Index 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 the Hyperglycemia Index values is returned. NA glucose values are omitted from the calculation of the Hyperglycemia Index values.
Hyperglycemia Index is calculated by \(n/c * \sum [(hyperBG_j-ULTR) ^{a}]\) Here n is the total number of Glucose measurements (excluding NA values), \(hyperBG_j\) is the jth Glucose measurement above the ULTR cutoff, a is an exponent, and c is a scaling factor.
References
Rodbard (2009) Interpretation of continuous glucose monitoring data: glycemic variability and quality of glycemic control, Diabetes Technology and Therapeutics 11 .55-67, doi:10.1089/dia.2008.0132 .
Examples
data(example_data_1_subject)
hyper_index(example_data_1_subject)
#> # A tibble: 1 × 2
#> id hyper_index
#> <fct> <dbl>
#> 1 Subject 1 0.391
hyper_index(example_data_1_subject, ULTR = 160)
#> # A tibble: 1 × 2
#> id hyper_index
#> <fct> <dbl>
#> 1 Subject 1 0.192
data(example_data_5_subject)
hyper_index(example_data_5_subject)
#> # A tibble: 5 × 2
#> id hyper_index
#> <fct> <dbl>
#> 1 Subject 1 0.391
#> 2 Subject 2 4.17
#> 3 Subject 3 1.18
#> 4 Subject 4 0.358
#> 5 Subject 5 2.21
hyper_index(example_data_5_subject, ULTR = 150)
#> # A tibble: 5 × 2
#> id hyper_index
#> <fct> <dbl>
#> 1 Subject 1 0.275
#> 2 Subject 2 3.64
#> 3 Subject 3 0.947
#> 4 Subject 4 0.222
#> 5 Subject 5 1.86