ArticleDiabetes technology & therapeutics2011
Translating glucose variability metrics into the clinic via Continuous Glucose Monitoring: a Graphical User Interface for Diabetes Evaluation (CGM-GUIDE©).
Article in Diabetes technology & therapeutics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Efficacy and safety of evogliptin treatment in patients with type 2 diabetes: A multicentre, active-controlled, randomized, double-blind study with open-label extension (the EVERGREEN study).Diabetes, obesity & metabolism · 2020Trial
- Female Mice Are Not More Variable Than Males: Evidence From Continuous Glucose Monitoring in Normoglycaemic C57BL/6 Mice.Diabetes, obesity & metabolism · 2026Article
- Lack of Association Between Hemoglobin A1c and Continuous Glucose Monitor Metrics Among Individuals with Prediabetes and Normoglycemia.Diabetes technology & therapeutics · 2026Article
- Article
- Glucostats: an efficient Python library for glucose time series feature extraction and visual analysis.BMC bioinformatics · 2025Article
- Evaluation of Asymptomatic Fasting Hypoglycemia in Outpatients Without Diabetes.Journal of the American Board of Family Medicine : JABFM · 2025Article
- Glucose variability measured by continuous glucose monitoring is associated with skin autofluorescence: the Maastricht Study.Diabetologia · 2025Article
- Association Between Hypnotics and Glycemic Variability Assessed by Continuous Glucose Monitoring Under Real-Life Conditions in Patients With Type 2 Diabetes: A Cross-Sectional Study.Journal of diabetes research · 2025Article
- AGATA: A Toolbox for Automated Glucose Data Analysis.Journal of diabetes science and technology · 2024Article
- Explainable hypoglycemia prediction models through dynamic structured grammatical evolution.Scientific reports · 2024Article
- Enhancement of Ambulatory Glucose Profile for Decision Assistance and Treatment Adjustments.Diagnostics (Basel, Switzerland) · 2024Article
- Long-Term Glucose Forecasting for Open-Source Automated Insulin Delivery Systems: A Machine Learning Study with Real-World Variability Analysis.Healthcare (Basel, Switzerland) · 2023Article
- CGM Metrics Identify Dysglycemic States in Participants From the TrialNet Pathway to Prevention Study.Diabetes care · 2023Article
- Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems.Nutrients · 2022Article
- An Interactive Web Application for the Statistical Analysis of Continuous Glucose Monitoring Data in Epidemiological Studies.Journal of diabetes science and technology · 2022Article
- Glucose Patterns in Very Old Adults: A Pilot Study in a Community-Based Population.Diabetes technology & therapeutics · 2021Article
- Non-invasive wearables for remote monitoring of HbA1c and glucose variability: proof of concept.BMJ open diabetes research & care · 2021Article
- New Innovation: Use of Flash Glucose Monitoring for Evaluating Glycaemic Variability, Patient Satisfaction and Clinical Utility in Pregnant Women with Diabetes.Journal of obstetrics and gynaecology of India · 2021Article
- Continuous glucose monitoring during pregnancy in healthy mice.Scientific reports · 2021Article
- Cgmquantify: Python and R Software Packages for Comprehensive Analysis of Interstitial Glucose and Glycemic Variability from Continuous Glucose Monitor Data.IEEE open journal of engineering in medicine and biology · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundSeveral metrics of glucose variability have been proposed to date, but an integrated approach that provides a complete and consistent assessment of glycemic variation is missing. As a consequence, and because of the tedious coding necessary during quantification, most investigators and clinicians have not yet adopted the use of multiple glucose variability metrics to evaluate glycemic variation.
methodsWe compiled the most extensively used statistical techniques and glucose variability metrics, with adjustable hyper- and hypoglycemic limits and metric parameters, to create a user-friendly Continuous Glucose Monitoring Graphical User Interface for Diabetes Evaluation (CGM-GUIDE©). In addition, we introduce and demonstrate a novel transition density profile that emphasizes the dynamics of transitions between defined glucose states.
resultsOur combined dashboard of numerical statistics and graphical plots support the task of providing an integrated approach to describing glycemic variability. We integrated existing metrics, such as SD, area under the curve, and mean amplitude of glycemic excursion, with novel metrics such as the slopes across critical transitions and the transition density profile to assess the severity and frequency of glucose transitions per day as they move between critical glycemic zones.
conclusionsBy presenting the above-mentioned metrics and graphics in a concise aggregate format, CGM-GUIDE provides an easy to use tool to compare quantitative measures of glucose variability. This tool can be used by researchers and clinicians to develop new algorithms of insulin delivery for patients with diabetes and to better explore the link between glucose variability and chronic diabetes complications.
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