The function hypo_index produces Hypoglycemia index 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.
- b
Exponent, generally in the range from 1.0 to 2.0, default value is 2.
- 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.
Value
If a data.frame object is passed, then a tibble object with two columns: subject id and corresponding Hypoglycemia Index value is returned. If a vector of glucose values is passed, then a tibble object with just the Hypoglycemia 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 Hypoglycemia Index values is returned. NA glucose values are omitted from the calculation of the Hypoglycemia Index values.
Hypoglycemia Index is calculated by \(n/d * \sum [(LLTR-hypoBG_j)^{b}]\) Here n is the total number of Glucose measurements (excluding NA values), and \(hypoBG_j\) is the jth Glucose measurement below the LLTR cutoff, b is an exponent, and d 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)
hypo_index(example_data_1_subject, LLTR = 60)
#> # A tibble: 1 × 2
#> id hypo_index
#> <fct> <dbl>
#> 1 Subject 1 0
data(example_data_5_subject)
hypo_index(example_data_5_subject)
#> # A tibble: 5 × 2
#> id hypo_index
#> <fct> <dbl>
#> 1 Subject 1 0.0103
#> 2 Subject 2 0
#> 3 Subject 3 0.0378
#> 4 Subject 4 0.0437
#> 5 Subject 5 0.0120
hypo_index(example_data_5_subject, LLTR = 70)
#> # A tibble: 5 × 2
#> id hypo_index
#> <fct> <dbl>
#> 1 Subject 1 0.000480
#> 2 Subject 2 0
#> 3 Subject 3 0.00626
#> 4 Subject 4 0.00978
#> 5 Subject 5 0.000387