Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range

T Battelino, T Danne, RM Bergenstal, SA Amiel… - Diabetes …, 2019 - Am Diabetes Assoc
Improvements in sensor accuracy, greater convenience and ease of use, and expanding
reimbursement have led to growing adoption of continuous glucose monitoring (CGM) …

[HTML][HTML] Glucose variability: how does it work?

VV Klimontov, OV Saik, AI Korbut - International journal of molecular …, 2021 - mdpi.com
A growing body of evidence points to the role of glucose variability (GV) in the development
of the microvascular and macrovascular complications of diabetes. In this review, we …

Artificial intelligence and machine learning for improving glycemic control in diabetes: best practices, pitfalls and opportunities

PG Jacobs, P Herrero, A Facchinetti… - IEEE reviews in …, 2023 - ieeexplore.ieee.org
Objective: Artificial intelligence and machine learning are transforming many fields including
medicine. In diabetes, robust biosensing technologies and automated insulin delivery …

Utilizing the ambulatory glucose profile to standardize and implement continuous glucose monitoring in clinical practice

ML Johnson, TW Martens, AB Criego… - Diabetes technology …, 2019 - liebertpub.com
Use of continuous glucose monitoring (CGM) is recognized as a valuable component of
diabetes self-management and is increasingly considered a standard of care for individuals …

Glucose variability and diabetes complications: Risk factor or biomarker? Can we disentangle the “Gordian Knot”?

L Monnier, C Colette, D Owens - Diabetes & metabolism, 2021 - Elsevier
Abstract «Variability in glucose homoeostasis» is a better description than «glycaemic
variability» as it encompasses two categories of dysglycaemic disorders: i) the short-term …

Glucose time in range, time above range, and time below range depend on mean or median glucose or HbA1c, glucose coefficient of variation, and shape of the …

D Rodbard - Diabetes technology & therapeutics, 2020 - liebertpub.com
Background: Examine the expected relationships between time in range (% TIR), time above
range (% TAR), and time below range (% TBR) with median glucose (or% HbA1c) and …

[HTML][HTML] Ever-increasing insulin-requiring patients globally

SK Garg, AH Rewers, HK Akturk - Diabetes technology & …, 2018 - liebertpub.com
Prevalence of diabetes continues to increase world-wide and now involves about half a
billion people globally. 1–3 The majority of this increase involves patients diagnosed with …

[HTML][HTML] Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches

B Bent, PJ Cho, M Henriquez, A Wittmann… - npj Digital …, 2021 - nature.com
Prediabetes affects one in three people and has a 10% annual conversion rate to type 2
diabetes without lifestyle or medical interventions. Management of glycemic health is …

A consensus statement for continuous glucose monitoring metrics for inpatient clinical trials

EK Spanakis, CB Cook, K Kulasa… - Journal of diabetes …, 2023 - journals.sagepub.com
Diabetes Technology Society organized an expert consensus panel to develop metrics for
research in the use of continuous glucose monitors (CGMs) in a hospital setting. The experts …

Review of methods for detecting glycemic disorders

M Bergman, M Abdul-Ghani, RA DeFronzo… - Diabetes research and …, 2020 - Elsevier
Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting
glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram …