Journal article · Conference paper
Early Glycemic Control Assessment Based on Consensus CGM Metrics
Department of Health Technology, Technical University of Denmark1
Department of Applied Mathematics and Computer Science, Technical University of Denmark2
Cognitive Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark3
Brain Computer Interface, Digital Health, Department of Health Technology, Technical University of Denmark4
University of Hamburg5
Novo Nordisk Foundation6
Continuous glucose monitoring (CGM) has revolutionized the world of diabetes and transformed the approach to diabetes care. In this context, an expert panel has reached consensus on clinical targets for CGM data interpretation based on eight CGM metrics. At least 70% of 14 consecutive CGM days (referred to as a period) are recommended to assess glycemic control based on the metrics.
In clinical practice less CGM data may be available. Therefore, the primary aim of this study is to explore the ability to recover the consensus metrics utilizing less than 14 days of CGM data (intra-period). As a secondary aim, we investigate the recovery considering two consecutive periods (inter-period).
The analyses are based on real-world CGM data from 484 diabetes users (4726 periods) acquired from the Cornerstones4Care® Powered by Glooko app. Using up to 14 accumulated days, the consensus metrics are calculated for each user and period, and compared to the fully 14 accumulated intra- and inter-period days.
Relatively low deviations were observed for time in range (TIR) and average based metrics when using less than 14 days, however, we observed large deviations in metrics characterizing infrequent events such as time below range (TBR). Furthermore, the consensus metrics obtained in two consecutive 14 day periods have clear discrepancies (inter-period).
Recovering consensus metrics using less than 14 days might still be valuable in terms of interpreting CGM data in certain clinical contexts. However, caution should be taken if treatment decisions would be made with less than 14 days of data on critical metrics such as TBR, since the metrics characterizing infrequent events deviate substantially when less data are available.
Substantial deviation is also seen when comparing across two consecutive periods, which means that care should be taken not to over-generalize consensus metric based glycemic control conclusions from one period to subsequent periods.
Language: | English |
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Publisher: | IEEE |
Year: | 2021 |
Pages: | 1269-1275 |
Proceedings: | 43<sup>rd</sup> Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
ISBN: | 172811179x , 1728111803 , 9781728111797 , 9781728111803 , 1728111781 , 172811179X and 9781728111780 |
ISSN: | 26940604 |
Types: | Journal article and Conference paper |
DOI: | 10.1109/EMBC46164.2021.9631015 |
ORCIDs: | Mohebbi, Ali and Morup, Morten |
Benchmarking Biology Blood Glucose Blood Glucose Self-Monitoring CGM data interpretation Consensus Diabetes Diabetes Mellitus, Type 1 Glooko app Glucose Glycemic Control Humans Measurement Monitoring biochemistry biomedical measurement blood consecutive periods consensus CGM metrics consensus metric-based glycemic control continuous glucose monitoring critical metrics diabetes care diseases glycemic control assessment interpreting CGM data intra-period patient care patient monitoring patient treatment real-world CGM data subsequent periods sugar