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.
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.
Value
A tibble object with columns for subject id and GRI value. Rows correspond to individual subjects.
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.
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 doi:10.1177/19322968221085273 .
Examples
data(example_data_1_subject)
gri(example_data_1_subject)
#> # A tibble: 1 × 2
#> id GRI
#> <fct> <dbl>
#> 1 Subject 1 7.19
data(example_data_5_subject)
gri(example_data_5_subject, tz = 'GMT')
#> # A tibble: 5 × 2
#> id GRI
#> <fct> <dbl>
#> 1 Subject 1 7.19
#> 2 Subject 2 79.7
#> 3 Subject 3 20.0
#> 4 Subject 4 4.38
#> 5 Subject 5 39.5