Continuous Glucose Monitoring–Derived Data Report—Simply a Better Management Tool

Battelino, Tadej; Bergenstal, Richard M.

doi:10.2337/dci20-0032

Cited by 18 publications

(21 citation statements)

References 26 publications

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“…7 years, and the mean HbA1c of 8.9% (74.0 mmol/mol) additionally support the value of CGM-derived TIR as the primary outcome in clinical trials. The relation of TIR with all-cause mortality and CVD mortality remained significant after multiple adjustments for numerous other main risk factors, and when analyzed as a discrete (in groups) or continuous variable.…”

supporting

confidence: 52%

“…The intuitive intelligibility of the TIR and TBR concept with its ''more green-less red'' mantra that can be followed prospectively throughout the days, weeks, months, and years with diabetes seems to more acceptable to individuals with diabetes than the retrospective A1c. Toschi and coauthors propose CGM-derived metrics to be used as an adjunct to the HbA1c; we believe CGM-derived metrics simply are a better management tool (7). Reducing glucose variability of course remains an important therapeutic target ( 23): as now suggested by several independent analyses, by reaching the TIR and TBR targets the CV goes below the current target of 36.…”

Section: Commentmentioning

confidence: 98%

“…Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, UK; 2 Diabetes Unit, Endocrinology and Nutrition, Institut d'Investigacions Biomèdiques August Pi i Sunyer, CIBERDEM, Hospital Clínic, Barcelona, Spain; 3 Jaeb Center for Health Research, Tampa, FL; 4 Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, Valencia, Spain; 5 Research Institute of the Diabetes Academy Mergentheim, Bad Mergentheim, Germany; 6 Department of Clinical Psychology and Psychotherapy, University of Bamberg, Bamberg, Germany; 7 Institut für Diabetes-Technologie, Forschungsund Entwicklungsgesellschaft GmbH an der Universität Ulm, Ulm, Germany; 8…”

mentioning

confidence: 99%

“…Moser O 1,2 , Riddell MC 3 , Eckstein ML 1 , Adolfsson A 4,5 , Rabasa-Lhoret R [6][7][8][9] , van den Boom L 10 , Gillard P 11 , Nørgaard K 12 , Oliver NS 13 , Zaharieva DP 14 , Battelino T 15,16 , de Beaufort C 17,18 , Bergenstal RM 19 , Buckingham B 14 , Cengiz E 20,21…”

mentioning

confidence: 99%

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Continuous and Intermittent Glucose Monitoring in 2020

Bode

Battelino

Dovč

2021

Diabetes Technology & Therapeutics

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IntroductionO ld and sage people say every terrible thing also brings something positive.And as wretched as this may sound, the SARS-CoV-2 pandemic with all its terrible consequences boosted the adoption and use of continuous and intermittent glucose monitoring (CGM) with the possibility of remote data access to an unimaginable extent: the CGM was recommended for the management of glycemia in the hospitals and intensive care units (1) and was successfully used at homes in most societies during the lockdown of cities, regions, and entire countries (2-4). The international digital/virtual clinic consensus endorsed during the Madrid 2020 ATTD congress (5), which intended to modestly start this important informatization process, became the roadmap overnight for many centers all over the world with routine digital/virtual diabetes clinics, serving as the predominant way of delivering diabetes care. This silver lining brings some consolation to diabetes teams faced with increased morbidity and mortality of people with diabetes related to .Meanwhile, additional evidence for CGM use and particularly for the CGM-derived glycemic metrics such as time in range (TIR), time below range (TBR), and time above range (TAR) accumulated and demonstrated its superior usability in everyday diabetes care (7-9). There are some indications that advanced technology could incrementally increase TIR (Fig. 1) (10).This year, our article focuses on clinical trials that extend existing knowledge particularly related to incremental benefits of diabetes technology and open new questions and challenges in the routine use of CGM. Importantly, evidence supporting CGM-derived metrics as the primary outcome in clinical trials is discussed.

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supporting

confidence: 52%

Section: Commentmentioning

confidence: 98%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Continuous and Intermittent Glucose Monitoring in 2020

Bode

Battelino

Dovč

2021

Diabetes Technology & Therapeutics

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“…Continuous glucose monitoring (CGM) systems have been available to support diabetes self-management for nearly two decades [1] . Based on evidence from clinical trials and real-world experiences, clinical guidelines have been established to assess CGM data and set glycemic targets for clinicians and people with diabetes [2] and guide therapeutic decision making, e.g., designing interventions to improve time in range (TIR) [3] . Furthermore, there is growing evidence that CGM-based measures, like TIR, correlate with long-term complications, and therefore data from CGM may be used to supplement HbA 1c as a measure of glycemic status for people living with diabetes [4] .…”

Section: Introductionmentioning

confidence: 99%

Dysglycemia in adults at risk for or living with non-insulin treated type 2 diabetes: Insights from continuous glucose monitoring

et al. 2021

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Background Continuous glucose monitoring (CGM) has demonstrable benefits for people living with diabetes, but the supporting evidence is almost exclusively from White individuals with type 1 diabetes. Here, we have quantified CGM profiles in Hispanic/Latino adults with or at-risk of non-insulin treated type 2 diabetes (T2D). Methods 100 participants (79 female, 86% Hispanic/Latino [predominantly Mexican], age 54·6 [±12·0] years) stratified into (i) at risk of T2D, (ii) with pre-diabetes (pre-T2D), and (iii) with non-insulin treated T2D, wore blinded CGMs for 2 weeks. Beyond standardized CGM measures (average glucose, glucose variability, time in 70–140 mg/dL and 70–180 mg/dL ranges), we also examined additional CGM measures based on the time of day. Findings Standardized CGM measures were significantly different for participants with T2D compared to at-risk and pre-T2D participants ( p <0·0001). In addition, pre-T2D participants spent more time between 140 and 180 mg/dL during the day than at-risk participants ( p <0·01). T2D participants spent more time between 140 and 180 mg/dL both during the day and overnight compared to at-risk and pre-T2D participants (both p <0·0001). Time in 70–140 mg/dL range during the day was significantly correlated with HbA 1c ( r =-0·72, p <0·0001), after adjusting for age, sex, BMI, and waist circumference ( p <0·0001). Interpretation Standardized CGM measures show a progression of dysglycemia from at-risk of T2D, to pre-T2D, and to T2D. Stratifying CGM readings by time of day and the range 140–180 mg/dL provides additional metrics to differentiate between the groups. Funding US Department of Agriculture (Grant #2018-33800-28404) and NSF PATHS-UP ERC (Award #1648451).

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