cogi: Calculate Continuous Glucose Monitoring Index (COGI) values

In irinagain/iglu: Interpreting Glucose Data from Continuous Glucose Monitors

Calculate Continuous Glucose Monitoring Index (COGI) values

Description

The function COGI produces cogi values in a tibble object.

Usage

cogi(data, targets = c(70, 180), weights = c(.5,.35,.15))

Arguments

data	DataFrame with column names ("id", "time", and "gl"), or numeric vector of glucose values.
targets	Numeric vector of two glucose values for threshold. Glucose values from data argument will be compared to each value in the targets vector to determine the time in range and time below range for COGI. The lower value will be used for determining time below range. Default list is (70, 180).
weights	Numeric vector of three weights to be applied to time in range, time below range and glucose variability, respectively. The default list is (.5,.35,.15)

Details

A tibble object with 1 row for each subject, a column for subject id and column for each target value is returned. NA's will be omitted from the glucose values in calculation of cogi.

Value

If a data.frame object is passed, then a tibble object with a column for subject id and then a column for each target value is returned. If a vector of glucose values is passed, then a tibble object without the subject id is returned. as.numeric() can be wrapped around the latter to output a numeric vector.

References

Leelarathna (2020) Evaluating Glucose Control With a Novel Composite Continuous Glucose Monitoring Index, Diabetes Technology and Therapeutics 14(2) 277-284, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/1932296819838525")}.

Examples

data(example_data_1_subject)

cogi(example_data_1_subject)
cogi(example_data_1_subject, targets = c(50, 140), weights = c(.3,.6,.1))

data(example_data_5_subject)

cogi(example_data_5_subject)
cogi(example_data_5_subject, targets = c(80, 180), weights = c(.2,.4,.4))

irinagain/iglu documentation built on April 15, 2024, 4:20 p.m.