CRAN/E | cgmquantify

cgmquantify

Analyzing Glucose and Glucose Variability

Installation

About

Continuous glucose monitoring (CGM) systems provide real-time, dynamic glucose information by tracking interstitial glucose values throughout the day. Glycemic variability, also known as glucose variability, is an established risk factor for hypoglycemia (Kovatchev) and has been shown to be a risk factor in diabetes complications. Over 20 metrics of glycemic variability have been identified. Here, we provide functions to calculate glucose summary metrics, glucose variability metrics (as defined in clinical publications), and visualizations to visualize trends in CGM data. Cho P, Bent B, Wittmann A, et al. (2020) American Diabetes Association (2020) Kovatchev B (2019) doi:10.1177/1932296819826111 Kovdeatchev BP (2017) doi:10.1038/nrendo.2017.3 Tamborlane W V., Beck RW, Bode BW, et al. (2008) doi:10.1056/NEJMoa0805017 Umpierrez GE, P. Kovatchev B (2018) doi:10.1016/j.amjms.2018.09.010.

Key Metrics

Version 0.1.0
R ≥ 2.10
Published 2021-02-05 1178 days ago
Needs compilation? no
License MIT License
License File
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Maintainer

Maintainer

Maria Henriquez

marhenriq@gmail.com

Authors

Maria Henriquez

aut / com / cph / cre / trl

Brinnae Bent

aut / cph / dtc

Material

README
Reference manual
Package source

Vignettes

User Guide

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 2.10

Imports

dplyr
tidyverse
ggplot2
hms
stats
magrittr

Suggests

testthat ≥ 2.0.0
knitr
rmarkdown