GLU: A tool for analysing continuously measured glucose in epidemiology

Abstract

MotivationContinuous glucose monitors (CGM) record interstitial glucose continuously, producing a sequence of measurements for each participant (e.g. the average glucose every 5 minutes over several days, both day and night). To analyze these data, researchers tend to derive summary variables such as the Area Under the Curve (AUC), to then use in subsequent analyses. To date, a lack of consistency and transparency of precise definitions used for these summary variables has hindered interpretation, replication and comparison of results across studies. We present GLU, an open-source software package for deriving a consistent set of summary variables from CGM data.\n\nGeneral featuresGLU performs quality control of each CGM sample (e.g. addressing missing data), derives a diverse set of summary variables (e.g. AUC, and proportion of time spent in hypo-, normo- and hyper-glycaemic levels) covering six broad domains, and outputs these (with quality control information) to the user.\n\nImplementationGLU is implemented in R.\n\nAVAILABILITYGLU is available on GitHub at [https://github.com/MRCIEU/GLU]. Git tag v0.1 corresponds to the version presented here.