iglu (version 4.2.2)

hypo_index: Calculate Hypoglycemia Index

Description

The function hypo_index produces Hypoglycemia index values in a tibble object.

Usage

hypo_index(data, LLTR = 80, b = 2, d = 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.

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.

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 \(\frac{1}{n \cdot d} \sum \left(ULTR - hyperBG_j \right)^b\). 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, tools:::Rd_expr_doi("10.1089/dia.2008.0132").

Examples

data(example_data_1_subject)
hypo_index(example_data_1_subject, LLTR = 60)

data(example_data_5_subject)
hypo_index(example_data_5_subject)
hypo_index(example_data_5_subject, LLTR = 70)