The function `agp_metrics` runs the following functions and combines them into a tibble object: `active_percent`, `mean_glu`, `gmi`, `cv_glu`, `below_percent`, `in_range_percent`, `above_percent`.
agp_metrics(data, shinyformat = FALSE, tz = '')
By default, a tibble object with 1 row for each subject, and 13 columns is returned: a column for subject id, a column for start date, a column for end date, a column for number of days, a column for active_percent, a column for Mean value, a column for gmi value, a column for cv value, a column for below_54 value, a column for below_70 value, a column for in_range_70_180 value, a column for above_180 value, a column for above_250 value,
DataFrame object with column names "id", "time", and "gl".
Default: FALSE. Boolean indicating whether the output should be formatted for the single subject AGP page in shiny.
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.
The function uses recommended cutoffs of 54, 70, 180, and 250 mg/dL for calculation.
If `shinyformat == FALSE` (default), returns a tibble object with 1 row for each subject, and 12 columns: a column for subject id (`id`), a column for start date (`start_date`), a column for end date (`end_date`), a column for number of days (`ndays`), a column for active percent (`active_percent`), a column for mean value (`mean`), a column for GMI value (`GMI`), a column for CV value (`CV`), a column for a column for a column for a column for a column for
If `shinyformat == TRUE`, a tibble with 2 columns: metric and value, is returned. This output is used when generating the single subject AGP shiny page.
Johnson et al. (2019) Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice, Diabetes Technology and Therapeutics 21:S2 S2-17-S2-25, tools:::Rd_expr_doi("10.1089/dia.2019.0034").
data(example_data_1_subject)
agp_metrics(example_data_1_subject)
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