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Freckmann G, Waldenmaier D, Heinemann L. Head-to-Head Evaluation of Continuous Glucose Monitoring and Automated Insulin Delivery Systems: Why are They not Used More Systematically? J Diabetes Sci Technol 2024; 18:535-540. [PMID: 38293951 PMCID: PMC11089857 DOI: 10.1177/19322968241227976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Affiliation(s)
- Guido Freckmann
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Delia Waldenmaier
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Lutz Heinemann
- Science Consulting in Diabetes GmbH, Düsseldorf, Germany
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2
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Freckmann G, Eichenlaub M, Waldenmaier D, Pleus S, Wehrstedt S, Haug C, Witthauer L, Jendle J, Hinzmann R, Thomas A, Eriksson Boija E, Makris K, Diem P, Tran N, Klonoff DC, Nichols JH, Slingerland RJ. Clinical Performance Evaluation of Continuous Glucose Monitoring Systems: A Scoping Review and Recommendations for Reporting. J Diabetes Sci Technol 2023; 17:1506-1526. [PMID: 37599389 PMCID: PMC10658695 DOI: 10.1177/19322968231190941] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/22/2023]
Abstract
The use of different approaches for design and results presentation of studies for the clinical performance evaluation of continuous glucose monitoring (CGM) systems has long been recognized as a major challenge in comparing their results. However, a comprehensive characterization of the variability in study designs is currently unavailable. This article presents a scoping review of clinical CGM performance evaluations published between 2002 and 2022. Specifically, this review quantifies the prevalence of numerous options associated with various aspects of study design, including subject population, comparator (reference) method selection, testing procedures, and statistical accuracy evaluation. We found that there is a large variability in nearly all of those aspects and, in particular, in the characteristics of the comparator measurements. Furthermore, these characteristics as well as other crucial aspects of study design are often not reported in sufficient detail to allow an informed interpretation of study results. We therefore provide recommendations for reporting the general study design, CGM system use, comparator measurement approach, testing procedures, and data analysis/statistical performance evaluation. Additionally, this review aims to serve as a foundation for the development of a standardized CGM performance evaluation procedure, thereby supporting the goals and objectives of the Working Group on CGM established by the Scientific Division of the International Federation of Clinical Chemistry and Laboratory Medicine.
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Affiliation(s)
- Guido Freckmann
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Manuel Eichenlaub
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Delia Waldenmaier
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Stefan Pleus
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Stephanie Wehrstedt
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Cornelia Haug
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Lilian Witthauer
- Diabetes Center Berne, Bern, Switzerland
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital Bern, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Johan Jendle
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Rolf Hinzmann
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Roche Diabetes Care GmbH, Mannheim, Germany
| | - Andreas Thomas
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Pirna, Germany
| | - Elisabet Eriksson Boija
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Equalis AB, Uppsala, Sweden
| | - Konstantinos Makris
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Clinical Biochemistry Department, KAT General Hospital, Athens, Greece
| | - Peter Diem
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Endokrinologie Diabetologie Bern, Bern, Switzerland
| | - Nam Tran
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Department of Pathology and Laboratory Medicine, University of California Davis Health, Sacramento, CA, USA
| | - David C. Klonoff
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA, USA
| | - James H. Nichols
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Vanderbilt University Medical Center, Nashville, TN, USA
| | - Robbert J. Slingerland
- IFCC Scientific Division - Working Group on Continuous Glucose Monitoring
- Department of Clinical Chemistry, Isala Clinics, Zwolle, the Netherlands
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Chmayssem A, Nadolska M, Tubbs E, Sadowska K, Vadgma P, Shitanda I, Tsujimura S, Lattach Y, Peacock M, Tingry S, Marinesco S, Mailley P, Lablanche S, Benhamou PY, Zebda A. Insight into continuous glucose monitoring: from medical basics to commercialized devices. Mikrochim Acta 2023; 190:177. [PMID: 37022500 DOI: 10.1007/s00604-023-05743-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 03/08/2023] [Indexed: 04/07/2023]
Abstract
According to the latest statistics, more than 537 million people around the world struggle with diabetes and its adverse consequences. As well as acute risks of hypo- or hyper- glycemia, long-term vascular complications may occur, including coronary heart disease or stroke, as well as diabetic nephropathy leading to end-stage disease, neuropathy or retinopathy. Therefore, there is an urgent need to improve diabetes management to reduce the risk of complications but also to improve patient's quality life. The impact of continuous glucose monitoring (CGM) is well recognized, in this regard. The current review aims at introducing the basic principles of glucose sensing, including electrochemical and optical detection, summarizing CGM technology, its requirements, advantages, and disadvantages. The role of CGM systems in the clinical diagnostics/personal testing, difficulties in their utilization, and recommendations are also discussed. In the end, challenges and prospects in future CGM systems are discussed and non-invasive, wearable glucose biosensors are introduced. Though the scope of this review is CGMs and provides information about medical issues and analytical principles, consideration of broader use will be critical in future if the right systems are to be selected for effective diabetes management.
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Affiliation(s)
- Ayman Chmayssem
- UMR 5525, Univ. Grenoble Alpes, CNRS, Grenoble INP, INSERM, TIMC, VetAgro Sup, 38000, Grenoble, France
| | - Małgorzata Nadolska
- Institute of Nanotechnology and Materials Engineering, Faculty of Applied Physics and Mathematics, Gdansk University of Technology, 80-233, Gdansk, Poland
| | - Emily Tubbs
- Univ. Grenoble Alpes, CEA, INSERM, IRIG, 38000, Grenoble, Biomics, France
- Univ. Grenoble Alpes, LBFA and BEeSy, INSERM, U1055, F-38000, Grenoble, France
| | - Kamila Sadowska
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109, Warsaw, Poland
| | - Pankaj Vadgma
- School of Engineering and Materials Science, Queen Mary University of London, Mile End, London, E1 4NS, UK
| | - Isao Shitanda
- Department of Pure and Applied Chemistry, Faculty of Science and Technology, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba, 278-8510, Japan
- Research Institute for Science and Technology, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba, 278-8510, Japan
| | - Seiya Tsujimura
- Japanese-French lAaboratory for Semiconductor physics and Technology (J-F AST)-CNRS-Université Grenoble Alpes-Grenoble, INP-University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8573, Japan
- Division of Material Science, Faculty of Pure and Applied Science, University of Tsukuba, 1-1-1, Tennodai, Ibaraki, Tsukuba, 305-5358, Japan
| | | | - Martin Peacock
- Zimmer and Peacock, Nedre Vei 8, Bldg 24, 3187, Horten, Norway
| | - Sophie Tingry
- Institut Européen Des Membranes, UMR 5635, IEM, Université Montpellier, ENSCM, CNRS, Montpellier, France
| | - Stéphane Marinesco
- Plate-Forme Technologique BELIV, Lyon Neuroscience Research Center, UMR5292, Inserm U1028, CNRS, Univ. Claude-Bernard-Lyon I, 69675, Lyon 08, France
| | - Pascal Mailley
- Univ. Grenoble Alpes, CEA, LETI, 38000, Grenoble, DTBS, France
| | - Sandrine Lablanche
- Univ. Grenoble Alpes, LBFA and BEeSy, INSERM, U1055, F-38000, Grenoble, France
- Department of Endocrinology, Grenoble University Hospital, Univ. Grenoble Alpes, Pôle DigiDune, Grenoble, France
| | - Pierre Yves Benhamou
- Department of Endocrinology, Grenoble University Hospital, Univ. Grenoble Alpes, Pôle DigiDune, Grenoble, France
| | - Abdelkader Zebda
- UMR 5525, Univ. Grenoble Alpes, CNRS, Grenoble INP, INSERM, TIMC, VetAgro Sup, 38000, Grenoble, France.
- Japanese-French lAaboratory for Semiconductor physics and Technology (J-F AST)-CNRS-Université Grenoble Alpes-Grenoble, INP-University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8573, Japan.
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Kalogeropoulou MS, Iglesias-Platas I, Beardsall K. Should continuous glucose monitoring be used to manage neonates at risk of hypoglycaemia? Front Pediatr 2023; 11:1115228. [PMID: 37025284 PMCID: PMC10070986 DOI: 10.3389/fped.2023.1115228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 02/28/2023] [Indexed: 04/08/2023] Open
Abstract
The National Institute for Clinical Excellence (NICE) now recommends that continuous glucose monitoring (CGM) be offered to adults and children with diabetes who are at risk from hypoglycaemia. Hypoglycaemia is common in the neonatal period, and is a preventable cause of poor neurodevelopmental outcome, but is CGM helpful in the management of neonates at risk of hypoglycaemia? Neonatal studies have shown that CGM can detect clinically silent hypoglycaemia, which has been associated with reduced executive and visual function in early childhood. Intervention trials have further shown CGM can support the targeting of glucose levels in high-risk extremely preterm neonates. In spite of significant advances in technology, including smaller sensors, better accuracy and factory calibration, further progress and adoption into clinical practice has been limited as current devices are not designed nor have regulatory approval for the specific needs of the newborn. The use of CGM has the potential to support clinical management, and prevention of hypoglycaemia but must be set within its current limitations. The data CGM provides however also provides an important opportunity to improve our understanding of potential risks of hypoglycaemia and the impact of clinical interventions to prevent it.
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Affiliation(s)
| | - Isabel Iglesias-Platas
- Department of Paediatrics, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Kathryn Beardsall
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
- Department of Paediatrics, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
- Neonatal Intensive Care Unit, Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Correspondence: Kathryn Beardsall
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Yeoh E, Png D, Khoo J, Chee YJ, Sharda P, Low S, Lim SC, Subramaniam T. A head-to-head comparison between Guardian Connect and FreeStyle Libre systems and an evaluation of user acceptability of sensors in patients with type 1 diabetes. Diabetes Metab Res Rev 2022; 38:e3560. [PMID: 35728796 DOI: 10.1002/dmrr.3560] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 04/03/2022] [Accepted: 05/03/2022] [Indexed: 11/11/2022]
Abstract
AIMS A user-calibrated real-time continuous glucose monitoring (rt-CGM) system is compared to a factory-calibrated flash glucose monitoring (FGM) system and assessed in terms of accuracy and acceptability in patients with type 1 diabetes (T1D). METHODS Ten participants with T1D were enroled from a specialist diabetes centre in Singapore and provided with the Guardian Connect with Enlite Sensor (Medtronic, Northridge, CA, USA) and first-generation Freestyle Libre System (Abbott Diabetes Care, Witney, UK), worn simultaneously. Participants had to check capillary blood glucose four times per day. At the end of week 1 and week 2, participants returned for data download and were given a user evaluation survey. RESULTS Accuracy evaluation between Guardian Connect and Freestyle Libre includes the overall mean absolute relative difference value (9.7 ± 11.0% vs. 17.5 ± 10.9%), Clarke Error Grid zones A + B (98.6% vs. 98.1%), sensitivity (78.9% vs. 63.4%), and specificity (93.4% vs. 81.0%). Notably, time below range (<3.9 mmol/L) was 10.5% for FGM versus 2% for rt-CGM. From the evaluation survey, 90% of participants perceived rt-CGM to be accurate versus 40% for FGM, although the majority found both devices to be easy to use, educational, and useful in improving glycaemic control. However, due to the cost of sensors, only 30% were keen to use either device for continuous monitoring. CONCLUSIONS Although rt-CGM was superior to FGM in terms of accuracy, the value of glucose trends in both devices is still useful in diabetes self-management. Patients and clinicians may consider either technology depending on their requirements.
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Affiliation(s)
- Ester Yeoh
- Diabetes Centre, Admiralty Medical Centre, Singapore, Singapore
- Department of Medicine, Division of Endocrinology, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Doanna Png
- Diabetes Centre, Admiralty Medical Centre, Singapore, Singapore
| | - Jonathon Khoo
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Ying Jie Chee
- Department of Medicine, Division of Endocrinology, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Puja Sharda
- Diabetes Centre, Admiralty Medical Centre, Singapore, Singapore
| | - Serena Low
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Su Chi Lim
- Diabetes Centre, Admiralty Medical Centre, Singapore, Singapore
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore
| | - Tavintharan Subramaniam
- Diabetes Centre, Admiralty Medical Centre, Singapore, Singapore
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, Singapore
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Garg SK, Kipnes M, Castorino K, Bailey TS, Akturk HK, Welsh JB, Christiansen MP, Balo AK, Brown SA, Reid JL, Beck SE. Accuracy and Safety of Dexcom G7 Continuous Glucose Monitoring in Adults with Diabetes. Diabetes Technol Ther 2022; 24:373-380. [PMID: 35157505 PMCID: PMC9208857 DOI: 10.1089/dia.2022.0011] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background: We evaluated the accuracy and safety of a seventh generation (G7) Dexcom continuous glucose monitor (CGM) during 10.5 days of use in adults with diabetes. Methods: Adults with either type 1 or type 2 diabetes (on intensive insulin therapy or not) participated at 12 investigational sites in the United States. In-clinic visits were conducted on days 1 or 2, 4 or 7, and on the second half of day 10 or the first half of day 11 for frequent comparisons with comparator blood glucose measurements obtained with the YSI 2300 Stat Plus glucose analyzer. Participants wore sensors concurrently on the upper arm and abdomen. Accuracy evaluation included the proportion of CGM values within 15% of comparator glucose levels >100 mg/dL or within 15 mg/dL of comparator levels ≤100 mg/dL (%15/15), along with the %20/20 and %30/30 agreement rates. The mean absolute relative difference (MARD) between temporally matched CGM and comparator values was also calculated. Results: Data from 316 participants (619 sensors, 77,774 matched pairs) were analyzed. For arm- and abdomen-placed sensors, overall MARDs were 8.2% and 9.1%, respectively. Overall %15/15, %20/20, and %30/30 agreement rates were 89.6%, 95.3%, and 98.8% for arm-placed sensors and were 85.5%, 93.2%, and 98.1% for abdomen-placed sensors. Across days of wear, glucose concentration ranges, and rates of change, %20/20 agreement rates varied by no more than 9% from the overall %20/20. No serious adverse events were reported. Conclusions: The G7 CGM provides accurate glucose readings with single-digit MARD with arm or abdomen placement in adults with diabetes. Clinicaltrials.gov: NCT04794478.
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Affiliation(s)
- Satish K. Garg
- Department of Medicine and Pediatrics, Barbara Davis Center for Diabetes, University of Colorado, Aurora, Colorado, USA
- Address correspondence to: Satish K. Garg, MD, Department of Medicine and Pediatrics, Barbara Davis Center for Diabetes, University of Colorado Denver, 1775 Aurora Court, Aurora, CO 80045, USA
| | | | | | | | - Halis Kaan Akturk
- Department of Medicine and Pediatrics, Barbara Davis Center for Diabetes, University of Colorado, Aurora, Colorado, USA
| | | | | | | | - Sue A. Brown
- University of Virginia, Charlottesville, Virginia, USA
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Schierbauer JR, Günther S, Haupt S, Zimmer RT, Zunner BEM, Zimmermann P, Wachsmuth NB, Eckstein ML, Aberer F, Sourij H, Moser O. Accuracy of Real Time Continuous Glucose Monitoring during Different Liquid Solution Challenges in Healthy Adults: A Randomized Controlled Cross-Over Trial. SENSORS 2022; 22:s22093104. [PMID: 35590794 PMCID: PMC9105614 DOI: 10.3390/s22093104] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 04/12/2022] [Accepted: 04/13/2022] [Indexed: 01/02/2023]
Abstract
Continuous glucose monitoring (CGM) represents an integral of modern diabetes management, however, there is still a lack of sensor performance data when rapidly consuming different liquids and thus changing total body water. 18 healthy adults (ten females, age: 23.1 ± 1.8 years, BMI 22.2 ± 2.1 kg·m−2) performed four trial visits consisting of oral ingestion (12 mL per kg body mass) of either a 0.9% sodium chloride, 5% glucose or Ringer’s solution and a control visit, in which no liquid was administered (control). Sensor glucose levels (Dexcom G6, Dexcom Inc., San Diego, CA, USA) were obtained at rest and in 10-min intervals for a period of 120 min after solution consumption and compared against reference capillary blood glucose measurements. The overall MedARD [IQR] was 7.1% [3.3−10.8]; during control 5.9% [2.7−10.8], sodium chloride 5.0% [2.7−10.2], 5% glucose 11.0% [5.3−21.6] and Ringer’s 7.5% [3.1−13.2] (p < 0.0001). The overall bias [95% LoA] was 4.3 mg·dL−1 [−19 to 28]; during control 3.9 mg·dL−1 [−11 to 18], sodium chloride 4.8 mg·dL−1 [−9 to 19], 5% glucose 3.6 mg·dL−1 [−33 to 41] and Ringer’s solution 4.9 mg·dL−1 [−13 to 23]. The Dexcom G6 CGM system detects glucose with very good accuracy during liquid solution challenges in normoglycemic individuals, however, our data suggest that in people without diabetes, sensor performance is influenced by different solutions.
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Affiliation(s)
- Janis R. Schierbauer
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
| | - Svenja Günther
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
| | - Sandra Haupt
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
| | - Rebecca T. Zimmer
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
| | - Beate E. M. Zunner
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
| | - Paul Zimmermann
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
| | - Nadine B. Wachsmuth
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
| | - Max L. Eckstein
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
| | - Felix Aberer
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
- Interdisciplinary Metabolic Medicine Trials Unit, Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, 8036 Graz, Austria;
| | - Harald Sourij
- Interdisciplinary Metabolic Medicine Trials Unit, Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, 8036 Graz, Austria;
| | - Othmar Moser
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, 95440 Bayreuth, Germany; (J.R.S.); (S.G.); (S.H.); (R.T.Z.); (B.E.M.Z.); (P.Z.); (N.B.W.); (M.L.E.); (F.A.)
- Interdisciplinary Metabolic Medicine Trials Unit, Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, 8036 Graz, Austria;
- Correspondence: ; Tel.: +49-(0)921-55-3465
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Accuracy Assessment of the GlucoMen® Day CGM System in Individuals with Type 1 Diabetes: A Pilot Study. BIOSENSORS 2022; 12:bios12020106. [PMID: 35200366 PMCID: PMC8869704 DOI: 10.3390/bios12020106] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 02/03/2022] [Accepted: 02/08/2022] [Indexed: 11/16/2022]
Abstract
The aim of this study was to evaluate the accuracy and usability of a novel continuous glucose monitoring (CGM) system designed for needle-free insertion and reduced environmental impact. We assessed the sensor performance of two GlucoMen® Day CGM systems worn simultaneously by eight participants with type 1 diabetes. Self-monitoring of blood glucose (SMBG) was performed regularly over 14 days at home. Participants underwent two standardized, 5-h meal challenges at the research center with frequent plasma glucose (PG) measurements using a laboratory reference (YSI) instrument. When comparing CGM to PG, the overall mean absolute relative difference (MARD) was 9.7 [2.6–14.6]%. The overall MARD for CGM vs. SMBG was 13.1 [3.5–18.6]%. The consensus error grid (CEG) analysis showed 98% of both CGM/PG and CGM/SMBG pairs in the clinically acceptable zones A and B. The analysis confirmed that GlucoMen® Day CGM meets the clinical requirements for state-of-the-art CGM. In addition, the needle-free insertion technology is well tolerated by users and reduces medical waste compared to conventional CGM systems.
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9
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Selvin E, Wang D, Tang O, Minotti M, Echouffo-Tcheugui JB, Coresh J. Glucose Patterns in Very Old Adults: A Pilot Study in a Community-Based Population. Diabetes Technol Ther 2021; 23:737-744. [PMID: 34191599 PMCID: PMC8819510 DOI: 10.1089/dia.2021.0156] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Context: Continuous glucose monitoring (CGM) provides nuanced information on glucose patterns, but data in very old adults are scarce. Objective: To evaluate CGM patterns in very old adults. Design: Pilot study. Setting: Participants recruited from one center during visit 7 (2019) of the community-based Atherosclerosis Risk in Communities (ARIC) Study. Participants: We enrolled 27 adults (8 with type 2 diabetes and 19 without diabetes) who wore a CGM sensor (Abbott Libre Pro) for up to 14 days. Clinical and laboratory measures, including hemoglobin A1c (HbA1c), were obtained. Main Outcomes: Mean CGM glucose, standard deviation (SD), coefficient of variation (CV), time-in-range (TIR) 70-180 mg/dL, and hypoglycemia. Results: Mean age was 81 (range 77-91 years) and mean CGM wear time was 13.2 days. In persons without diabetes, there was a wide range of CGM parameters: range of mean glucose, 83.7-124.5 mg/dL, SD 12.2-27.3 mg/dL, CV 14.0%-26.7%, and TIR 71.1%-99.5%. In persons with diabetes, the range of mean CGM glucose was 105.5-223.0 mg/dL, SD, 22.3-86.6 mg/dL, CV 18.2%-38.8%, TIR 38.7%-98.3%. The Pearson's correlation of mean glucose with HbA1c was high overall (0.90); but, for some participants with similar HbA1c, glucose patterns differed substantially. There was a high prevalence of hypoglycemia (glucose <70 or <54 mg/dL) in both persons with and without diabetes. Conclusions: There was high feasibility and acceptability of CGM in very old adults. Low readings on CGM are common, even in nondiabetic older adults; the clinical relevance of these low values is unclear. CGM may provide complementary information to HbA1c in some older adults.
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Affiliation(s)
- Elizabeth Selvin
- Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Address correspondence to: Elizabeth Selvin, PhD, MPH, Department of Epidemiology, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, 2024 E Monument Street, Suite 2-600, Baltimore, MD 21287, USA.
| | - Dan Wang
- Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Olive Tang
- Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Melissa Minotti
- Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Justin B. Echouffo-Tcheugui
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Josef Coresh
- Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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10
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Nagl K, Berger G, Aberer F, Ziko H, Weimann K, Bozic I, Rami‐Merhar B, Mader JK. Performance of three different continuous glucose monitoring systems in children with type 1 diabetes during a diabetes summer camp. Pediatr Diabetes 2021; 22:271-278. [PMID: 33219728 PMCID: PMC7984061 DOI: 10.1111/pedi.13160] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 09/25/2020] [Accepted: 11/16/2020] [Indexed: 12/19/2022] Open
Abstract
The aim of this study was to assess accuracy of the three most commonly used continuous glucose monitoring (CGM) systems in almost real-life situation during a diabetes camp in children with type 1 diabetes (T1D) aged 9-14 years. Data was gathered during a 2-week summer camp under physicians' supervision. Out of 38 participating children with T1D (aged: 11.0 [9.9; 12.1] years; 57% girls, mean HbA1c 7.2 [6.9; 7.7] %,) 37 wore a CGM system (either Abbott FreeStyle Libre (FSL), Dexcom G6 (DEX) or Medtronic Enlite (ENL)) throughout the camp. All concomitantly available data pairs of capillary glucose measurements and sensor values were used for the analysis. Mean absolute relative difference (MARD) was calculated and Parkes Error Grid analyses were done for all three systems used. In total 2079 data pairs were available for analysis. The overall MARDs of CGM systems used at the camp was FSL: 13.3% (6.7;21.6). DEX: 10.3% (5.8; 16.7) and ENL 8.5% (3.6; 15.6). During eu-, hypo- and hyperglycemia MARDs were lowest in ENL. Highest MARDs were seen in hypoglycemia, where all three systems exhibited MARDs above 15%. Overnight MARDs of all systems was higher than during daytime. All sensors performed worst in hypoglycemia. Performance of the adequately calibrated Medtronic system outperformed the factory-calibrated sensors. For clinical practice, it is important to adequately train children with T1D and families in the correct procedures for sensors that require calibrations.
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Affiliation(s)
- Katrin Nagl
- Department of Pediatrics and Adolescent MedicineMedical University ViennaAustria
| | - Gabriele Berger
- Department of Pediatrics and Adolescent MedicineMedical University ViennaAustria
| | - Felix Aberer
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazAustria
| | - Haris Ziko
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazAustria
| | - Katharina Weimann
- Department of Pediatrics and Adolescent MedicineMedical University ViennaAustria
| | - Ina Bozic
- Department of Pediatrics and Adolescent MedicineMedical University ViennaAustria
| | - Birgit Rami‐Merhar
- Department of Pediatrics and Adolescent MedicineMedical University ViennaAustria
| | - Julia K Mader
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazAustria
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11
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Boeder S, Kulasa K. Hospital care: improving outcomes in type 1 diabetes. Curr Opin Endocrinol Diabetes Obes 2021; 28:14-20. [PMID: 33315629 DOI: 10.1097/med.0000000000000601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
PURPOSE OF REVIEW Caring for patients with type 1 diabetes (T1D) in the hospital presents unique challenges. This review provides an update on significant issues relevant to the inpatient management of T1D. Topics include trends in diabetic ketoacidosis (DKA), hypoglycemia, and adapting ambulatory technologies for inpatient use. RECENT FINDINGS Rates of DKA in the United States are rising. Although socioeconomic status, health insurance coverage, and hemoglobin A1c are persistently associated with DKA in individuals with T1D, newer risk factors have also emerged. These include the off-label use of sodium-glucose cotransporter inhibitor medications, immune checkpoint inhibitor-induced diabetes, and infection with severe acute respiratory syndrome coronavirus 2. Hypoglycemia is common among hospitalized patients with T1D. Use of validated hypoglycemia risk prediction models and multidisciplinary care initiatives can reduce the risk of inpatient hypoglycemia. Finally, continuous glucose monitoring is being adapted for use in the hospital setting and has shown promise during the coronavirus disease 2019 (COVID-19) pandemic. SUMMARY Evidence-based treatment algorithms, risk prediction calculators, multidisciplinary interventions, and wearable technology hold promise for improved outcomes in hospitalized patients with T1D.
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Affiliation(s)
- Schafer Boeder
- Department of Medicine, Division of Endocrinology and Metabolism, University of California, San Diego, La Jolla, California, USA
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12
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Performance of the Intermittently Scanned Continuous Glucose Monitoring (isCGM) System during a High Oral Glucose Challenge in Adults with Type 1 Diabetes-A Prospective Secondary Outcome Analysis. BIOSENSORS-BASEL 2021; 11:bios11010022. [PMID: 33467765 PMCID: PMC7830732 DOI: 10.3390/bios11010022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 01/05/2021] [Accepted: 01/14/2021] [Indexed: 11/17/2022]
Abstract
To assess intermittently scanned continuous glucose monitoring (isCGM) performance for different rates of change in plasma glucose (RCPG) during glycemic challenges in type 1 diabetes (T1D). Nineteen people with T1D (7 females; age 35 ± 11 years; HbA1c 7.3 ± 0.6% (56 ± 7 mmol/mol)) performing two glycemic challenges (OGTT) were included. During OGTTs, plasma glucose was compared against sensor glucose for timepoints 0 min (pre-OGTT), +15 min, +30 min, +60 min, +120 min, +180 min, and +240 min by means of median absolute (relative) difference (MARD and MAD) and Clarke Error Grid (CEG), then was stratified for RCPG and glycemic ranges. Overall, MARD was 8.3% (4.0–14.8) during hypoglycemia level 1 18.8% (15.8–22.0), euglycemia 9.5% (4.3–15.1), hyperglycemia level 1 9.4% (4.0–17.2), and hyperglycemia level 2 7.1% (3.3–11.9). The MARD was associated with the RCPG (p < 0.0001), detailing significant differences in comparison of low, moderate, high, and very high RCPG (p = 0.014). Overall, CEG resulted in 88% (212 values) of comparison points in zone A, 12% (29 values) in zone B, and 0.4% (1 value) in zone D. The isCGM system was accurate during OGTTs. Its performance was dependent on the RCPG and showed an overestimation of the actual reference glucose during hypoglycemia.
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13
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A Comprehensive Review of Continuous Glucose Monitoring Accuracy during Exercise Periods. SENSORS 2021; 21:s21020479. [PMID: 33445438 PMCID: PMC7828017 DOI: 10.3390/s21020479] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/29/2020] [Accepted: 01/05/2021] [Indexed: 12/15/2022]
Abstract
Continuous Glucose Monitoring (CGM) has been a springboard of new diabetes management technologies such as integrated sensor-pump systems, the artificial pancreas, and more recently, smart pens. It also allows patients to make better informed decisions compared to a few measurements per day from a glucometer. However, CGM accuracy is reportedly affected during exercise periods, which can impact the effectiveness of CGM-based treatments. In this review, several studies that used CGM during exercise periods are scrutinized. An extensive literature review of clinical trials including exercise and CGM in type 1 diabetes was conducted. The gathered data were critically analysed, especially the Mean Absolute Relative Difference (MARD), as the main metric of glucose accuracy. Most papers did not provide accuracy metrics that differentiated between exercise and rest (non-exercise) periods, which hindered comparative data analysis. Nevertheless, the statistic results confirmed that CGM during exercise periods is less accurate.
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14
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Moser O, Riddell MC, Eckstein ML, Adolfsson P, Rabasa-Lhoret R, van den Boom L, Gillard P, Nørgaard K, Oliver NS, Zaharieva DP, Battelino T, de Beaufort C, Bergenstal RM, Buckingham B, Cengiz E, Deeb A, Heise T, Heller S, Kowalski AJ, Leelarathna L, Mathieu C, Stettler C, Tauschmann M, Thabit H, Wilmot EG, Sourij H, Smart CE, Jacobs PG, Bracken RM, Mader JK. Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA). Diabetologia 2020; 63:2501-2520. [PMID: 33047169 DOI: 10.1007/s00125-020-05263-9] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (i.e. before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes. Graphical abstract.
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Affiliation(s)
- Othmar Moser
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Auenbruggerplatz 2, 8036, Graz, Austria.
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, Bayreuth, Germany.
| | - Michael C Riddell
- School of Kinesiology and Health Science, York University, Toronto, ON, Canada
| | - Max L Eckstein
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Auenbruggerplatz 2, 8036, Graz, Austria
| | - Peter Adolfsson
- Department of Pediatrics, The Hospital of Halland, Kungsbacka, Sweden
- Sahlgrenska Academy at University of Gothenburg, Institution of Clinical Sciences, Gothenburg, Sweden
| | - Rémi Rabasa-Lhoret
- Institut de Recherches Cliniques de Montréal, Montréal, QC, Canada
- Endocrinology Division Centre Hospitalier Universitaire de Montréal, Montréal, QC, Canada
- Nutrition Department, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
- Montreal Diabetes Research Centre, Montréal, QC, Canada
| | | | - Pieter Gillard
- Department of Endocrinology, University Hospitals Leuven, KU Leuven, Leuven, Belgium
| | - Kirsten Nørgaard
- Steno Diabetes Center Copenhagen, University of Copenhagen, Copenhagen, Denmark
| | - Nick S Oliver
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College, London, London, UK
| | - Dessi P Zaharieva
- Department of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA, USA
| | - Tadej Battelino
- Department of Paediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Carine de Beaufort
- Department of Pediatric Diabetes and Endocrinology, Centre Hospitalier Luxembourg, Luxembourg, Luxembourg
- Department of Pediatrics, Free University Brussels (VUB), Brussels, Belgium
| | | | - Bruce Buckingham
- Department of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA, USA
| | - Eda Cengiz
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, USA
- Bahçeşehir Üniversitesi, Istanbul, Turkey
| | - Asma Deeb
- Paediatric Endocrinology Division, Shaikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates
| | | | - Simon Heller
- Department of Oncology & Metabolism, The Medical School, University of Sheffield, Sheffield, UK
- Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | | | - Lalantha Leelarathna
- Manchester Diabetes Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Chantal Mathieu
- Department of Endocrinology, University Hospitals Leuven, KU Leuven, Leuven, Belgium
| | - Christoph Stettler
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Martin Tauschmann
- Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Hood Thabit
- Manchester Diabetes Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Emma G Wilmot
- Diabetes Department, Royal Derby Hospital, University Hospitals of Derby and Burton NHSFT, Derby, UK
- Faculty of Medicine & Health Sciences, University of Nottingham, Nottingham, UK
| | - Harald Sourij
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Auenbruggerplatz 2, 8036, Graz, Austria
| | - Carmel E Smart
- School of Health Sciences, University of Newcastle, Callaghan, NSW, Australia
- Department of Paediatric Diabetes and Endocrinology, John Hunter Children's Hospital, Newcastle, NSW, Australia
| | - Peter G Jacobs
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Richard M Bracken
- Applied Sport, Technology, Exercise and Medicine Research Centre (A-STEM), College of Engineering, Swansea University, Swansea, UK
| | - Julia K Mader
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Auenbruggerplatz 2, 8036, Graz, Austria
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15
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Moser O, Riddell MC, Eckstein ML, Adolfsson P, Rabasa‐Lhoret R, van den Boom L, Gillard P, Nørgaard K, Oliver NS, Zaharieva DP, Battelino T, de Beaufort C, Bergenstal RM, Buckingham B, Cengiz E, Deeb A, Heise T, Heller S, Kowalski AJ, Leelarathna L, Mathieu C, Stettler C, Tauschmann M, Thabit H, Wilmot EG, Sourij H, Smart CE, Jacobs PG, Bracken RM, Mader JK. Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA). Pediatr Diabetes 2020; 21:1375-1393. [PMID: 33047481 PMCID: PMC7702152 DOI: 10.1111/pedi.13105] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (ie, before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes.
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Affiliation(s)
- Othmar Moser
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazAustria
- Division of Exercise Physiology and Metabolism, Department of Sport Science, University of BayreuthBayreuthGermany
| | - Michael C. Riddell
- School of Kinesiology and Health ScienceYork UniversityTorontoOntarioCanada
| | - Max L. Eckstein
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazAustria
| | - Peter Adolfsson
- Department of PediatricsThe Hospital of HallandKungsbackaSweden
- Sahlgrenska Academy at University of GothenburgInstitution of Clinical SciencesGothenburgSweden
| | - Rémi Rabasa‐Lhoret
- Institut de recherches Cliniques de MontréalMontréalQCCanada
- Endocrinology division Centre Hospitalier Universitaire de MontréalMontréalQCCanada
- Nutrition Department, Faculty of MedicineUniversité de MontréalMontréalQCCanada
- Montreal Diabetes Research CentreMontréalQCCanada
| | | | - Pieter Gillard
- Department of EndocrinologyUniversity Hospitals Leuven, KU LeuvenLeuvenBelgium
| | - Kirsten Nørgaard
- Steno Diabetes Center CopenhagenUniversity of CopenhagenCopenhagenDenmark
| | - Nick S. Oliver
- Department of Metabolism, Digestion and Reproduction, Faculty of MedicineImperial CollegeLondonLondonUK
| | - Dessi P. Zaharieva
- Department of Pediatric Endocrinology and DiabetesStanford University School of MedicineStanfordCaliforniaUSA
| | - Tadej Battelino
- Department of Paediatric Endocrinology, Diabetes and Metabolic Diseases, UMC ‐ University Children’s HospitalUniversity Medical Centre LjubljanaLjubljanaSlovenia
- Faculty of MedicineUniversity of LjubljanaLjubljanaSlovenia
| | - Carine de Beaufort
- Department of Pediatric Diabetes and EndocrinologyCentre Hospitalier LuxembourgLuxembourgLuxembourg
- Department of Pediatrics, Free University Brussels (VUB)BrusselsBelgium
| | | | - Bruce Buckingham
- Department of Pediatric Endocrinology and DiabetesStanford University School of MedicineStanfordCaliforniaUSA
| | - Eda Cengiz
- Department of Pediatrics, Yale School of MedicineNew HavenConnecticutUSA
- Bahçeşehir Üniversitesi, IstanbulTurkey
| | - Asma Deeb
- Paediatric Endocrinology DivisionShaikh Shakhbout Medical CityAbu DhabiUnited Arab Emirates
| | | | - Simon Heller
- Department of Oncology & Metabolism, The Medical SchoolUniversity of SheffieldSheffieldUK
- Sheffield Teaching Hospitals NHS Foundation Trust, SheffieldUK
| | | | - Lalantha Leelarathna
- Manchester Diabetes Centre, Manchester University NHS Foundation TrustManchester Academic Health Science CentreManchesterUK
- Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
| | - Chantal Mathieu
- Department of EndocrinologyUniversity Hospitals Leuven, KU LeuvenLeuvenBelgium
| | - Christoph Stettler
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, InselspitalBern University Hospital and University of BernBernSwitzerland
| | - Martin Tauschmann
- Department of Pediatrics and Adolescent MedicineMedical University of ViennaViennaAustria
| | - Hood Thabit
- Manchester Diabetes Centre, Manchester University NHS Foundation TrustManchester Academic Health Science CentreManchesterUK
| | - Emma G. Wilmot
- Diabetes Department, Royal Derby Hospital, University Hospitals of Derby and Burton NHSFTDerbyUK
- Faculty of Medicine & Health SciencesUniversity of NottinghamNottinghamUK
| | - Harald Sourij
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazAustria
| | - Carmel E. Smart
- School of Health Sciences, University of NewcastleCallaghanNew South WalesAustralia
- Department of Paediatric Diabetes and EndocrinologyJohn Hunter Children’s HospitalNewcastleNew South WalesAustralia
| | - Peter G. Jacobs
- Department of Biomedical EngineeringOregon Health & Science UniversityPortlandOregonUSA
| | - Richard M. Bracken
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
| | - Julia K. Mader
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazAustria
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16
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Moser O, Eckstein ML, McCarthy O, Deere R, Pitt J, Williams DM, Hayes J, Sourij H, Bain SC, Bracken RM. Performance of the Freestyle Libre flash glucose monitoring (flash GM) system in individuals with type 1 diabetes: A secondary outcome analysis of a randomized crossover trial. Diabetes Obes Metab 2019; 21:2505-2512. [PMID: 31332929 PMCID: PMC6852439 DOI: 10.1111/dom.13835] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 07/03/2019] [Accepted: 07/12/2019] [Indexed: 01/08/2023]
Abstract
AIMS The efficacy of flash glucose monitoring (flash GM) systems has been demonstrated by improvements in glycaemia; however, during high rates of glucose flux, the performance of continuous glucose monitoring systems was impaired, as detailed in previous studies. This study aimed to determine the performance of the flash GM system during daily-life glycaemic challenges such as carbohydrate-rich meals, bolus insulin-induced glycaemic disturbances and acute physical exercise in individuals with type 1 diabetes. MATERIALS AND METHODS This study comprised four randomized trial visits with alternating pre- and post-exercise bolus insulin doses. Throughout the four 14-hour inpatient phases, 19 participants received three carbohydrate-rich meals and performed moderate-intensity exercise. Venous blood glucose and capillary blood glucose during exercise was compared to interstitial glucose concentrations. Flash GM accuracy was assessed by median absolute relative difference (MARD) (interquartile range [IQR]) using the Bland-Altman method and Clark error grid, as well as according to guidelines for integrated CGM approvals (Class II-510(K)). RESULTS The overall MARD (IQR) during inpatient phases was 14.3% (6.9%-22.8%), during hypoglycaemia (≤3.9 mmol/L) was 31.6% (16.2%-46.8%), during euglycaemia (4.0 mmol/L - 9.9 mmol/L) was 16.0% (8.5%-24.0%) and during hyperglycaemia (≥10 mmol/L) was 9.4% (5.1%-15.7%). Overall Bland-Altman analysis showed a bias (95% LoA) of 1.26 mmol/L (-1.67 to 4.19 mmol/L). The overall MARD during acute exercise was 29.8% (17.5%-39.8%), during hypoglycaemia was 45.1% (35.2%-51.1%), during euglycaemia was 30.7% (18.7%-39.2%) and during hyperglycaemia was 16.3% (10.0%-22.8%). CONCLUSION Flash GM interstitial glucose readings were not sufficiently accurate within the hypoglycaemic range and during acute exercise and require confirmatory blood glucose measurements.
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Affiliation(s)
- Othmar Moser
- Diabetes Research Group, Medical SchoolSwansea UniversitySwanseaUK
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
- Division of Endocrinology and DiabetologyMedical University of GrazGrazAustria
| | - Max L. Eckstein
- Diabetes Research Group, Medical SchoolSwansea UniversitySwanseaUK
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
- Division of Endocrinology and DiabetologyMedical University of GrazGrazAustria
| | - Olivia McCarthy
- Diabetes Research Group, Medical SchoolSwansea UniversitySwanseaUK
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
| | - Rachel Deere
- Diabetes Research Group, Medical SchoolSwansea UniversitySwanseaUK
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
- Department for HealthUniversity of BathBathUK
| | - Jason Pitt
- Diabetes Research Group, Medical SchoolSwansea UniversitySwanseaUK
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
| | - David M. Williams
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
| | - Jennifer Hayes
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
| | - Harald Sourij
- Division of Endocrinology and DiabetologyMedical University of GrazGrazAustria
| | - Stephen C. Bain
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
| | - Richard M. Bracken
- Diabetes Research Group, Medical SchoolSwansea UniversitySwanseaUK
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
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17
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Zaharieva DP, Turksoy K, McGaugh SM, Pooni R, Vienneau T, Ly T, Riddell MC. Lag Time Remains with Newer Real-Time Continuous Glucose Monitoring Technology During Aerobic Exercise in Adults Living with Type 1 Diabetes. Diabetes Technol Ther 2019; 21:313-321. [PMID: 31059282 PMCID: PMC6551983 DOI: 10.1089/dia.2018.0364] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Background: Real-time continuous glucose monitoring (CGM) devices help detect glycemic excursions associated with exercise, meals, and insulin dosing in patients with type 1 diabetes (T1D). However, the delay between interstitial and blood glucose may result in CGM underestimating the true change in glycemia during activity. The purpose of this study was to examine CGM discrepancies during exercise and the meal postexercise versus self-monitoring of blood glucose (SMBG). Methods: Seventeen adults with T1D using insulin pump therapy and CGM completed 60 min of aerobic exercise on three occasions. A standardized meal was given 30 min postexercise. SMBG was measured during exercise and in recovery using OmniPod® Personal Diabetes Manager (PDM; Insulet, Billerica, MA) with built-in glucose meter (FreeStyle; Abbott Laboratories, Abbott Park, IL), while CGM was measured with Dexcom G4® with 505 algorithm (n = 4) or G5® (n = 13), which were calibrated with subjects' own PDM. Results: SMBG showed a large drop in glycemia during exercise, while CGM showed a lag of 12 ± 11 (mean ± standard deviation) minutes and bias of -7 ± 19 mg/dL/min during activity. Mean absolute relative difference (MARD) for CGM versus SMBG was 13 (6-22)% [median (interquartile range)] during exercise and 8 (5-14)% during mealtime. Clarke error grids showed CGM values were in zones A and B 94%-99% of the time for SMBG. Conclusion: In summary, the drop in CGM lags behind the drop in blood glucose during prolonged aerobic exercise by 12 ± 11 min, and MARD increases to 13 (6-22)% during exercise as well. Therefore, if hypoglycemia is suspected during exercise, individuals should confirm glucose levels with a capillary glucose measurement.
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Affiliation(s)
- Dessi P. Zaharieva
- Kinesiology and Health Science, Faculty of Health, Muscle Health Research Centre, York University, Toronto, Canada
| | - Kamuran Turksoy
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois
| | - Sarah M. McGaugh
- Kinesiology and Health Science, Faculty of Health, Muscle Health Research Centre, York University, Toronto, Canada
| | - Rubin Pooni
- Kinesiology and Health Science, Faculty of Health, Muscle Health Research Centre, York University, Toronto, Canada
| | | | - Trang Ly
- Insulet Corporation, Billerica, Massachusetts
| | - Michael C. Riddell
- Kinesiology and Health Science, Faculty of Health, Muscle Health Research Centre, York University, Toronto, Canada
- LMC Diabetes and Endocrinology, Toronto, Canada
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18
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Moser O, Pandis M, Aberer F, Kojzar H, Hochfellner D, Elsayed H, Motschnig M, Augustin T, Kreuzer P, Pieber TR, Sourij H, Mader JK. A head-to-head comparison of personal and professional continuous glucose monitoring systems in people with type 1 diabetes: Hypoglycaemia remains the weak spot. Diabetes Obes Metab 2019; 21:1043-1048. [PMID: 30484947 PMCID: PMC6590188 DOI: 10.1111/dom.13598] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 11/23/2018] [Accepted: 11/23/2018] [Indexed: 01/08/2023]
Abstract
To compare the performance of a professional continuous glucose monitoring (proCGM) and a personal continuous glucose monitoring (persCGM) system worn in parallel under standardized conditions in individuals with type 1 diabetes (T1D), two CGM systems (iPro2 - proCGM; Minimed 640G - persCGM) worn in parallel using the same sensor (Enlite 2) were compared. Ten people with T1D were included in this single-centre, open-label study in which CGM performance was evaluated. The study consisted of a 24-hours inpatient phase (meals, exercise, glycaemic challenges) and a 4-day home phase. Analyses included fulfilment of ISO 15197:2013 criteria, mean absolute relative difference (MARD), Parkes Error Grid and Bland-Altman plots. During the inpatient stay, ISO 15197:2013 criteria fulfilment was 58.4% (proCGM) and 57.8% (persCGM). At home, the systems met ISO 15197:2013 criteria by 66.5% (proCGM) and 65.3% (persCGM). No difference of MARD in inpatient phase (19.1 ± 16.7% vs. 19.0 ± 19.6; P = 0.83) and home phase (18.6 ± 26.8% vs. 17.4 ± 21.3%, P = 0.87) was observed. All sensors performed less accurately during hypoglycaemia. ProCGM and persCGM showed similar performance during daytime and night-time for the inpatient and the home phase. However, sensor performance was reduced during hypoglycaemia for both systems.
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Affiliation(s)
- Othmar Moser
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
- Diabetes Research Group, Medical SchoolSwansea UniversitySwanseaUK
- Applied Sport, Technology, Exercise and Medicine Research Centre (A‐STEM), College of EngineeringSwansea UniversitySwanseaUK
| | - Marlene Pandis
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
| | - Felix Aberer
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
| | - Harald Kojzar
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
| | - Daniel Hochfellner
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
| | - Hesham Elsayed
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
| | - Melanie Motschnig
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
| | - Thomas Augustin
- Joanneum Research GmbH, HEALTH – Institute for Biomedicine and Health SciencesGrazAustria
| | - Philipp Kreuzer
- Division of Emergency Medicine Department of Internal MedicineMedical University of GrazGrazAustria
| | - Thomas R. Pieber
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
- Joanneum Research GmbH, HEALTH – Institute for Biomedicine and Health SciencesGrazAustria
- Center for Biomarker Research in Medicine, CBmedGrazAustria
| | - Harald Sourij
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
- Center for Biomarker Research in Medicine, CBmedGrazAustria
| | - Julia K. Mader
- Division of Endocrinology and Diabetology, Department of Internal MedicineMedical University of GrazGrazAustria
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