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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)

Arguments

data

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

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 .

Author

Elizabeth Chun

Examples


data(example_data_1_subject)
gri(example_data_1_subject)
#> # A tibble: 1 × 2
#>   id          GRI
#>   <fct>     <dbl>
#> 1 Subject 1  7.49

data(example_data_5_subject)
gri(example_data_5_subject)
#> # A tibble: 5 × 2
#>   id           GRI
#>   <fct>      <dbl>
#> 1 Subject 1   7.49
#> 2 Subject 2 100   
#> 3 Subject 3  24.5 
#> 4 Subject 4   4.51
#> 5 Subject 5  48.5