hbgi: Calculate High Blood Glucose Index (HBGI)

In iglu: Interpreting Glucose Data from Continuous Glucose Monitors

Calculate High Blood Glucose Index (HBGI)

Description

The function hbgi produces HBGI values in a tibble object.

Usage

hbgi(data)

Arguments

data	DataFrame object with column names "id", "time", and "gl", or numeric vector of glucose values.

Details

A tibble object with 1 row for each subject, a column for subject id and a column for HBGI values is returned. NA glucose values are omitted from the calculation of the HBGI.

HBGI is calculated by 1/n * \sum (10 * fg_i ^2), where fg_i = max(0, 1.509 * (log(G_i)^{1.084} - 5.381), G_i is the ith Glucose measurement for a subject, and n is the total number of measurements for that subject.

Value

If a data.frame object is passed, then a tibble object with two columns: subject id and corresponding HBGI value is returned. If a vector of glucose values is passed, then a tibble object with just the HBGI value is returned. as.numeric() can be wrapped around the latter to output just a numeric value.

References

Kovatchev et al. (2006) Evaluation of a New Measure of Blood Glucose Variability in, Diabetes Diabetes care 29 .2433-2438, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2337/dc06-1085")}.

Examples

data(example_data_1_subject)
hbgi(example_data_1_subject)

data(example_data_5_subject)
hbgi(example_data_5_subject)

iglu documentation built on April 4, 2025, 12:16 a.m.