gri: Calculate Glycemia Risk Index (GRI)

In iglu: Interpreting Glucose Data from Continuous Glucose Monitors

Calculate Glycemia Risk Index (GRI)

Description

The function gri produces a tibble object with values equal to the glycemia risk index (GRI) metric. The output columns are subject id and GRI value. ' The output rows correspond to subjects.

Usage

gri(data, tz = "")

Arguments

data	DataFrame object with column names "id", "time", and "gl", or numeric vector of glucose values.
tz	Default: "". A character string specifying the time zone to be used. System-specific (see as.POSIXct), but " " is the current time zone, and "GMT" is UTC (Universal Time, Coordinated). Invalid values are most commonly treated as UTC, on some platforms with a warning.

Details

A tibble object with 1 row for each subject, a column for subject id and column for GRI is returned. The formula for GRI is as follows:

(3.0 × VLow) + (2.4 × Low) + (1.6 × VHigh) + (0.8 × High)

where VLow, Low, VHigh, and High correspond to the percent of glucose values in the ranges <54 mg/dL, 54-70 mg/dL, >250 mg/dL, and 180-250 mg/dL respectively. The maximum allowed value for GRI is 100%, any calculated values higher than 100 are capped.

Value

A tibble object with columns for subject id and GRI value. Rows correspond to individual subjects.

Author(s)

Elizabeth Chun

References

Klonoff et al. (2022) A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings. J Diabetes Sci Technol \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/19322968221085273")}.

Examples

data(example_data_1_subject)
gri(example_data_1_subject)

data(example_data_5_subject)
gri(example_data_5_subject, tz = 'GMT')

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