An Interactive Web Application for the Statistical Analysis of Continuous Glucose Monitoring Data in Epidemiological Studies. (March 2022)

• Record Type: Journal Article
• Authors: De Livera, Alysha M.; Shaw, Jonathan E.; Cohen, Neale; Reutens, Anne; Salim, Agus
• Is Part Of: Journal of diabetes science and technology. Volume 16:Number 2(2022)
• Page Start: 397
• Page End: 400
• Publication Date: 2022-03
• Subjects: continuous glucose monitoring -- statistical analysis -- visualization -- software; Diabetes -- Periodicals; Medical technology -- Periodicals; Diabetes Mellitus -- Periodicals; 616.462005
• DOI: 10.1177/1932296820985570
• Languages: English
• ISSNs: 1932-2968

Abstract

Motivation: Continuous glucose monitoring (CGM) systems are an essential part of novel technology in diabetes management and care. CGM studies have become increasingly popular among researchers, healthcare professionals, and people with diabetes due to the large amount of useful information that can be collected using CGM systems. The analysis of the data from these studies for research purposes, however, remains a challenge due to the characteristics and large volume of the data. Results: Currently, there are no publicly available interactive software applications that can perform statistical analyses and visualization of data from CGM studies. With the rapidly increasing popularity of CGM studies, such an application is becoming necessary for anyone who works with these large CGM datasets, in particular for those with little background in programming or statistics. CGMStatsAnalyser is a publicly available, user-friendly, web-based application, which can be used to interactively visualize, summarize, and statistically analyze voluminous and complex CGM datasets together with the subject characteristics with ease.