The function igc produces IGC values in a tibble object.
Arguments
- data
DataFrame object with column names "id", "time", and "gl", or numeric vector of glucose values.
- LLTR
Lower Limit of Target Range, default value is 80 mg/dL.
- 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.
- b
Exponent, generally in the range from 1.0 to 2.0, default value is 2.
- 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.
- d
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.
Details
A tibble object with 1 row for each subject, a column for subject id and a column for the IGC values is returned.
IGC is calculated by taking the sum of the Hyperglycemia
Index and the Hypoglycemia index. See hypo_index and
hyper_index.
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)
igc(example_data_1_subject)
#> # A tibble: 1 × 2
#> id IGC
#> <fct> <dbl>
#> 1 Subject 1 0.401
igc(example_data_1_subject, ULTR = 160)
#> # A tibble: 1 × 2
#> id IGC
#> <fct> <dbl>
#> 1 Subject 1 0.203
data(example_data_5_subject)
igc(example_data_5_subject)
#> # A tibble: 5 × 2
#> id IGC
#> <fct> <dbl>
#> 1 Subject 1 0.401
#> 2 Subject 2 4.17
#> 3 Subject 3 1.22
#> 4 Subject 4 0.401
#> 5 Subject 5 2.22
igc(example_data_5_subject, LLTR = 75, ULTR = 150)
#> # A tibble: 5 × 2
#> id IGC
#> <fct> <dbl>
#> 1 Subject 1 0.278
#> 2 Subject 2 3.64
#> 3 Subject 3 0.965
#> 4 Subject 4 0.242
#> 5 Subject 5 1.86