Quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long-term glucose regulation
Introduction The integration of continuous glucose monitoring (CGM) into clinical practice has rapidly emerged in the last decade, changing the evaluation of long-term glucose regulation in patients with diabetes. When using CGM-derived metrics to evaluate long-term glucose regulation, it is essenti...
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BMJ Publishing Group
2025-02-01
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| Series: | BMJ Open Diabetes Research & Care |
| Online Access: | https://drc.bmj.com/content/13/1/e004768.full |
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| author | Gozewijn D Laverman Stennie Zoet Thomas Urgert Anouk Veldhuis Bert-Jan van Beijnum |
| author_facet | Gozewijn D Laverman Stennie Zoet Thomas Urgert Anouk Veldhuis Bert-Jan van Beijnum |
| author_sort | Gozewijn D Laverman |
| collection | DOAJ |
| description | Introduction The integration of continuous glucose monitoring (CGM) into clinical practice has rapidly emerged in the last decade, changing the evaluation of long-term glucose regulation in patients with diabetes. When using CGM-derived metrics to evaluate long-term glucose regulation, it is essential to determine the minimal observation period necessary for a reliable estimate. The approach of this study was to calculate mean absolute errors (MAEs) for varying window lengths, with the goal of demonstrating how the CGM observation period influences the accuracy of the estimation of 90-day glycemic control.Research design and methods CGM data were collected from the DIABASE cohort (ZGT hospital, The Netherlands). Trailing aggregates (TAs) were calculated for four CGM-derived metrics: time in range (TIR), time below range (TBR), glucose management indicator (GMI) and glycemic variability (GV). Arbitrary MAEs for each patient were compared between the TAs of window lengths from 1 to 89 days and a reference TA of 90 days, which is assumed to reflect long-term glycemic regulation.Results Using 14 days of CGM data resulted in 65% of subjects having their TIR estimation being below a MAE threshold of 5%. In order to have 90% of the subjects below a TIR MAE threshold of 5%, the observation period needs to be 29 days.Conclusions Although there is currently no consensus on what is an acceptable MAE, this study provides insight into how MAEs of CGM-derived metrics change according to the used observation period within a population and may thus be helpful for clinical decision-making. |
| format | Article |
| id | doaj-art-9e68bf788f1741edb7a23e58ea9364c9 |
| institution | OA Journals |
| issn | 2052-4897 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMJ Publishing Group |
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| series | BMJ Open Diabetes Research & Care |
| spelling | doaj-art-9e68bf788f1741edb7a23e58ea9364c92025-08-20T02:03:57ZengBMJ Publishing GroupBMJ Open Diabetes Research & Care2052-48972025-02-0113110.1136/bmjdrc-2024-004768Quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long-term glucose regulationGozewijn D Laverman0Stennie Zoet1Thomas Urgert2Anouk Veldhuis3Bert-Jan van Beijnum41 Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands1 Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands1 Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands3 Department of Health and Information Technology, Ziekenhuisgroep Twente, Almelo, Overijssel, The Netherlands1 Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The NetherlandsIntroduction The integration of continuous glucose monitoring (CGM) into clinical practice has rapidly emerged in the last decade, changing the evaluation of long-term glucose regulation in patients with diabetes. When using CGM-derived metrics to evaluate long-term glucose regulation, it is essential to determine the minimal observation period necessary for a reliable estimate. The approach of this study was to calculate mean absolute errors (MAEs) for varying window lengths, with the goal of demonstrating how the CGM observation period influences the accuracy of the estimation of 90-day glycemic control.Research design and methods CGM data were collected from the DIABASE cohort (ZGT hospital, The Netherlands). Trailing aggregates (TAs) were calculated for four CGM-derived metrics: time in range (TIR), time below range (TBR), glucose management indicator (GMI) and glycemic variability (GV). Arbitrary MAEs for each patient were compared between the TAs of window lengths from 1 to 89 days and a reference TA of 90 days, which is assumed to reflect long-term glycemic regulation.Results Using 14 days of CGM data resulted in 65% of subjects having their TIR estimation being below a MAE threshold of 5%. In order to have 90% of the subjects below a TIR MAE threshold of 5%, the observation period needs to be 29 days.Conclusions Although there is currently no consensus on what is an acceptable MAE, this study provides insight into how MAEs of CGM-derived metrics change according to the used observation period within a population and may thus be helpful for clinical decision-making.https://drc.bmj.com/content/13/1/e004768.full |
| spellingShingle | Gozewijn D Laverman Stennie Zoet Thomas Urgert Anouk Veldhuis Bert-Jan van Beijnum Quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long-term glucose regulation BMJ Open Diabetes Research & Care |
| title | Quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long-term glucose regulation |
| title_full | Quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long-term glucose regulation |
| title_fullStr | Quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long-term glucose regulation |
| title_full_unstemmed | Quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long-term glucose regulation |
| title_short | Quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long-term glucose regulation |
| title_sort | quantification of the relation between continuous glucose monitoring observation period and the estimation error in assessing long term glucose regulation |
| url | https://drc.bmj.com/content/13/1/e004768.full |
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