iglu (version 4.2.2)

igc: Calculate Index of Glycemic Control

Description

The function igc produces IGC values in a tibble object.

Usage

igc(data, LLTR = 80, ULTR = 140, a = 1.1, b = 2, c = 30, d = 30)

Value

A tibble object with two columns: subject id and corresponding IGC 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.

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, tools:::Rd_expr_doi("10.1089/dia.2008.0132").

Examples

data(example_data_1_subject)
igc(example_data_1_subject)
igc(example_data_1_subject, ULTR = 160)

data(example_data_5_subject)
igc(example_data_5_subject)
igc(example_data_5_subject, LLTR = 75, ULTR = 150)