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Hirsch IB, Tirosh A, Navon A. Noninvasive Real-Time Glucose Monitoring Is in the Near Future. Diabetes Technol Ther 2024; 26:661-666. [PMID: 38417015 DOI: 10.1089/dia.2024.0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/01/2024]
Abstract
Objective: Since the introduction of continuous glucose monitoring (CGM) technology, developers have rigorously researched the feasibility of creating a noninvasive glucose monitoring device. In a recent pilot study, investigators reported a strong correlation between glucose values obtained from novel noninvasive monitoring device (GWave) values to venous and capillary glucose measurements. Research Design and Methods: We investigated whether the level of accuracy observed in the pilot study could be reproduced in a larger cohort, using a smaller third-generation manufacturable device (Gen III GWave) containing a standardized sensor chip that can be mass produced for commercial use. The evaluation assessed concordance with capillary blood glucose, reproducibility between two Gen III devices, and accuracy during insulin-induced hypoglycemia. Results: Assessment of samples from 75 subjects (type 2 diabetes, n = 6; type 1 diabetes, n = 28; nondiabetic pregnant subjects, n = 10; and nondiabetic, n = 31) showed that 97% of values were in Zone A with 3% in Zone B of the Clarke Error Grid, with a mean absolute relative difference of 6.7% from reference blood glucose. Comparison between two independent Gen III GWave devices demonstrated reproducibility between the sensors (R2 = 0.95), with 100% of values within Zone A. In the hypoglycemia assessment, measurements from the Gen III sensor tightly followed the capillary glucose measurements down to 42 mg/dL (2.3 mmol/L), whereas the CGM measurements from two different CGM only converged with the GWave and capillary glucose readings after 90 min of decreasing glucose levels. Conclusion: Our results show promise as potentially the first noninvasive technology. Future studies will focus on larger number of people in all glucose ranges. Real-time noninvasive blood glucose monitoring is possible using GWave technology.
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Affiliation(s)
- Irl B Hirsch
- UW Medicine Diabetes Institute, School of Medicine, University of Washington, Seattle, Washington, USA
| | - Amir Tirosh
- Division of Endocrinology, Diabetes, and Metabolism, Sheba Medical Center, Ramat Gan, Israel
| | - Ami Navon
- Department of Immunology and Regenerative Biology, The Weizmann Institute of Science, Rehovot, Israel
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WANG YY, YING HM, TIAN F, QIAN XL, Zhou ZF. Three months use of Hybrid Closed Loop Systems improves glycated hemoglobin levels in adolescents and children with type 1 diabetes: A meta-analysis. PLoS One 2024; 19:e0308202. [PMID: 39133688 PMCID: PMC11318905 DOI: 10.1371/journal.pone.0308202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 07/19/2024] [Indexed: 08/15/2024] Open
Abstract
BACKGROUND Longer outpatient studies have demonstrated that hybrid closed loop (HCL) use has led to a concomitant reduction in glycated hemoglobin(HbA1c) by 0.3%-0.7%. However, reports have also indicated that HbA1c levels are not declined in the long-term use of HCL. Therefore, we wonder that 3 months use of HCL could improve glycated hemoglobin levels in adolescents and children with T1D. METHODS Relevant studies were searched electronically in the Cochrane Library, PubMed, and Embase utilizing the key words "Pediatrics or Child or Adolescent", "Insulin Infusion Systems" and "Diabetes Mellitus" from inception to 17th March 2024 to evaluate the performance of HCL on HbA1c in adolescents, and children with T1D. RESULTS Nine studies involving 927 patients were identified. Three months use of HCL show a beneficial effect on HbA1c management (p <0.001) as compared to standard of care in adolescents and children with T1D, without evidence of heterogeneity between articles (I2 = 40%, p = 0.10). HCL did significantly increase the overall average percentage of hypoglycemic time between 70 and 180 mg/dL (TIR) (p <0.001; I2 = 51%). HCL did not show a beneficial effect on hypoglycemic time <70 mg/dL and <54 mg/dL (p >0.05). The overall percentage of hyperglycemic time was significantly decreased in HCL group compared to the control group when it was defined as >180 mg/dL (p <0.001; I2 = 83%), >250 mg/dL (p = 0.007, I2 = 86%) and >300 mg/dL (p = 0.005; I2 = 76%). The mean glucose level was significantly decreased by HCL (p <0.001; I2 = 58%), however, no significant difference was found in coefficient of variation of sensor glucose (p = 0.82; I2 = 71%) and daily insulin dose (p = 0.94; I2 <0.001) between the HCL group and the control group. CONCLUSIONS HCL had a beneficial effect on HbA1c management and TIR without increased hypoglycemic time as compared to standard of care in adolescents and children with T1D when therapy duration of HCL was not less than three months. TRIAL NUMBER AND REGISTRY URL CRD42022367493; https://www.crd.york.ac.uk/PROSPERO, Principal investigator: Zhen-feng Zhou, Date of registration: October 30, 2022.
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Affiliation(s)
- Yuan-yuan WANG
- Department of Endocrinology, Xixi Hospital of Hangzhou (Affiliated Hangzhou Xixi Hospital of Zhejiang Chinese Medical University), Hangzhou, Zhejiang Province, Hangzhou, China
| | - Hui-min YING
- Department of Endocrinology, Xixi Hospital of Hangzhou (Affiliated Hangzhou Xixi Hospital of Zhejiang Chinese Medical University), Hangzhou, Zhejiang Province, Hangzhou, China
| | - Fang TIAN
- Department of Endocrinology, Xixi Hospital of Hangzhou (Affiliated Hangzhou Xixi Hospital of Zhejiang Chinese Medical University), Hangzhou, Zhejiang Province, Hangzhou, China
| | - Xiao-lu QIAN
- Department of Endocrinology, Xixi Hospital of Hangzhou (Affiliated Hangzhou Xixi Hospital of Zhejiang Chinese Medical University), Hangzhou, Zhejiang Province, Hangzhou, China
| | - Zhen-feng Zhou
- Department of Anesthesiology, Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital, Hangzhou First People’s Hospital Qianjiang New City Campus, Zhejiang Chinese Medical University), Hangzhou, China
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Elghobashy ME, Richards AJ, Malekzadeh R, Patel D, Turner LV, Burr JF, Power GA, Laham R, Riddell MC, Cheng AJ. Carbohydrate Ingestion Increases Interstitial Glucose and Mitigates Neuromuscular Fatigue during Single-Leg Knee Extensions. Med Sci Sports Exerc 2024; 56:1495-1504. [PMID: 38595179 DOI: 10.1249/mss.0000000000003440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
Abstract
INTRODUCTION We aimed to investigate the neuromuscular contributions to enhanced fatigue resistance with carbohydrate (CHO) ingestion and to identify whether fatigue is associated with changes in interstitial glucose levels assessed using a continuous glucose monitor (CGM). METHODS Twelve healthy participants (six males, six females) performed isokinetic single-leg knee extensions (90°·s -1 ) at 20% of the maximal voluntary contraction (MVC) torque until MVC torque reached 60% of its initial value (i.e., task failure). Central and peripheral fatigue were evaluated every 15 min during the fatigue task using the interpolated twitch technique and electrically evoked torque. Using a single-blinded crossover design, participants ingested CHO (85 g sucrose per hour), or a placebo (PLA), at regular intervals during the fatigue task. Minute-by-minute interstitial glucose levels measured via CGM and whole blood glucose readings were obtained intermittently during the fatiguing task. RESULTS CHO ingestion increased time to task failure over PLA (113 ± 69 vs 81 ± 49 min, mean ± SD; P < 0.001) and was associated with higher glycemia as measured by CGM (106 ± 18 vs 88 ± 10 mg·dL -1 , P < 0.001) and whole blood glucose sampling (104 ± 17 vs 89 ± 10 mg·dL -1 , P < 0.001). When assessing the values in the CHO condition at a similar time point to those at task failure in the PLA condition (i.e., ~81 min), MVC torque, percentage voluntary activation, and 10 Hz torque were all better preserved in the CHO versus PLA condition ( P < 0.05). CONCLUSIONS Exogenous CHO intake mitigates neuromuscular fatigue at both the central and peripheral levels by raising glucose concentrations rather than by preventing hypoglycemia.
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Affiliation(s)
- Mohamed E Elghobashy
- Muscle Health Research Centre, School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Ontario, CANADA
| | - Andrew J Richards
- Muscle Health Research Centre, School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Ontario, CANADA
| | - Rohin Malekzadeh
- Muscle Health Research Centre, School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Ontario, CANADA
| | - Disha Patel
- Muscle Health Research Centre, School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Ontario, CANADA
| | - Lauren V Turner
- Muscle Health Research Centre, School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Ontario, CANADA
| | - Jamie F Burr
- Department of Human Health and Nutritional Sciences, College of Biological Sciences, University of Guelph, Guelph, Ontario, CANADA
| | - Geoffrey A Power
- Department of Human Health and Nutritional Sciences, College of Biological Sciences, University of Guelph, Guelph, Ontario, CANADA
| | - Robert Laham
- Muscle Health Research Centre, School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Ontario, CANADA
| | - Michael C Riddell
- Muscle Health Research Centre, School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Ontario, CANADA
| | - Arthur J Cheng
- Muscle Health Research Centre, School of Kinesiology and Health Science, Faculty of Health, York University, Toronto, Ontario, CANADA
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den Braber N, Braem CIR, Vollenbroek-Hutten MMR, Hermens HJ, Urgert T, Yavuz US, Veltink PH, Laverman GD. Consequences of Data Loss on Clinical Decision-Making in Continuous Glucose Monitoring: Retrospective Cohort Study. Interact J Med Res 2024; 13:e50849. [PMID: 39083801 PMCID: PMC11325125 DOI: 10.2196/50849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 02/21/2024] [Accepted: 04/10/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND The impact of missing data on individual continuous glucose monitoring (CGM) data is unknown but can influence clinical decision-making for patients. OBJECTIVE We aimed to investigate the consequences of data loss on glucose metrics in individual patient recordings from continuous glucose monitors and assess its implications on clinical decision-making. METHODS The CGM data were collected from patients with type 1 and 2 diabetes using the FreeStyle Libre sensor (Abbott Diabetes Care). We selected 7-28 days of 24 hours of continuous data without any missing values from each individual patient. To mimic real-world data loss, missing data ranging from 5% to 50% were introduced into the data set. From this modified data set, clinical metrics including time below range (TBR), TBR level 2 (TBR2), and other common glucose metrics were calculated in the data sets with and that without data loss. Recordings in which glucose metrics deviated relevantly due to data loss, as determined by clinical experts, were defined as expert panel boundary error (εEPB). These errors were expressed as a percentage of the total number of recordings. The errors for the recordings with glucose management indicator <53 mmol/mol were investigated. RESULTS A total of 84 patients contributed to 798 recordings over 28 days. With 5%-50% data loss for 7-28 days recordings, the εEPB varied from 0 out of 798 (0.0%) to 147 out of 736 (20.0%) for TBR and 0 out of 612 (0.0%) to 22 out of 408 (5.4%) recordings for TBR2. In the case of 14-day recordings, TBR and TBR2 episodes completely disappeared due to 30% data loss in 2 out of 786 (0.3%) and 32 out of 522 (6.1%) of the cases, respectively. However, the initial values of the disappeared TBR and TBR2 were relatively small (<0.1%). In the recordings with glucose management indicator <53 mmol/mol the εEPB was 9.6% for 14 days with 30% data loss. CONCLUSIONS With a maximum of 30% data loss in 14-day CGM recordings, there is minimal impact of missing data on the clinical interpretation of various glucose metrics. TRIAL REGISTRATION ClinicalTrials.gov NCT05584293; https://clinicaltrials.gov/study/NCT05584293.
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Affiliation(s)
- Niala den Braber
- Biomedical Signal and Systems, Faculty of Electrical Engineering, Mathematics And Computer Science, University of Twente, Enschede, Netherlands
- Internal Medicine, Ziekenhuisgroep Twente, Almelo, Netherlands
| | - Carlijn I R Braem
- Biomedical Signal and Systems, Faculty of Electrical Engineering, Mathematics And Computer Science, University of Twente, Enschede, Netherlands
- Internal Medicine, Ziekenhuisgroep Twente, Almelo, Netherlands
| | - Miriam M R Vollenbroek-Hutten
- Biomedical Signal and Systems, Faculty of Electrical Engineering, Mathematics And Computer Science, University of Twente, Enschede, Netherlands
| | - Hermie J Hermens
- Biomedical Signal and Systems, Faculty of Electrical Engineering, Mathematics And Computer Science, University of Twente, Enschede, Netherlands
| | - Thomas Urgert
- Biomedical Signal and Systems, Faculty of Electrical Engineering, Mathematics And Computer Science, University of Twente, Enschede, Netherlands
- Internal Medicine, Ziekenhuisgroep Twente, Almelo, Netherlands
| | - Utku S Yavuz
- Biomedical Signal and Systems, Faculty of Electrical Engineering, Mathematics And Computer Science, University of Twente, Enschede, Netherlands
| | - Peter H Veltink
- Biomedical Signal and Systems, Faculty of Electrical Engineering, Mathematics And Computer Science, University of Twente, Enschede, Netherlands
| | - Gozewijn D Laverman
- Biomedical Signal and Systems, Faculty of Electrical Engineering, Mathematics And Computer Science, University of Twente, Enschede, Netherlands
- Internal Medicine, Ziekenhuisgroep Twente, Almelo, Netherlands
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Wang YY, Ying HM, Tian F, Qian XL, Zhou ZF, Zhou CC. Automated insulin delivery in children with type 1 diabetes during physical activity: a meta-analysis. J Pediatr Endocrinol Metab 2024; 37:505-515. [PMID: 38700489 DOI: 10.1515/jpem-2024-0098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Accepted: 04/18/2024] [Indexed: 05/05/2024]
Abstract
OBJECTIVES The aim of this study was to evaluate the performance of the automated insulin delivery (AID) in adolescents, and children with type 1 diabetes (T1D) during physical activity. METHODS Relevant studies were searched electronically in the Cochrane Library, PubMed, and Embase utilizing the key words "Child", "Insulin Infusion Systems", and "Diabetes Mellitus" from inception to 17th March 2024 to evaluate the performance of the AID in adolescents, and children with T1D during physical activity. RESULTS Twelve studies involving 514 patients were identified. AID did not show a beneficial effect on duration of hypoglycemia<70 mg/dL during study period (p>0.05; I2=96 %) and during the physical activity (p>0.99). Percentage of sensor glucose values in TIR was higher in AID than the non-AID pumps during study period (p<0.001; I2=94 %). The duration of hyperglycemic time was significantly decreased in AID group compared to the non-AID pumps group during study period (p<0.05; I2>50 %). CONCLUSIONS AID improved TIR and decreased the duration of hyperglycemic time, but did not appear to have a significant beneficial effect on the already low post-exercise duration of hypoglycemia achievable by open loop or sensor-augmented pumps in adolescents and children with T1D during physical activity; further research is needed to confirm the beneficial effect of AID on duration of hypoglycemia.
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Affiliation(s)
- Yuan-Yuan Wang
- Department of Endocrinology, 631689 Xixi Hospital of Hangzhou , Hangzhou, Zhejiang Province, P.R. China
| | - Hui-Min Ying
- Department of Endocrinology, 631689 Xixi Hospital of Hangzhou , Hangzhou, Zhejiang Province, P.R. China
| | - Fang Tian
- Department of Endocrinology, 631689 Xixi Hospital of Hangzhou , Hangzhou, Zhejiang Province, P.R. China
| | - Xiao-Lu Qian
- Department of Endocrinology, 631689 Xixi Hospital of Hangzhou , Hangzhou, Zhejiang Province, P.R. China
| | - Zhen-Feng Zhou
- Department of Anesthesiology, Hangzhou Women's Hospital (Hangzhou Maternity and Child Health Care Hospital, Hangzhou First People's Hospital Qianjiang New City Campus, Zhejiang Chinese Medical University), Hangzhou, P.R. China
| | - Chun-Cong Zhou
- Department of Urolithiasis and Anorectal Surgery, Ningbo No. 2 Hospital, Ningbo, Zhejiang Province, P.R. China
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Varas N, Grabowski R, Jarosinski MA, Tai N, Herzog RI, Ismail-Beigi F, Yang Y, Cherrington AD, Weiss MA. Ultra-stable insulin-glucagon fusion protein exploits an endogenous hepatic switch to mitigate hypoglycemic risk. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.20.594997. [PMID: 38826486 PMCID: PMC11142066 DOI: 10.1101/2024.05.20.594997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
The risk of hypoglycemia and its serious medical sequelae restrict insulin replacement therapy for diabetes mellitus. Such adverse clinical impact has motivated development of diverse glucose-responsive technologies, including algorithm-controlled insulin pumps linked to continuous glucose monitors ("closed-loop systems") and glucose-sensing ("smart") insulins. These technologies seek to optimize glycemic control while minimizing hypoglycemic risk. Here, we describe an alternative approach that exploits an endogenous glucose-dependent switch in hepatic physiology: preferential insulin signaling (under hyperglycemic conditions) versus preferential counter-regulatory glucagon signaling (during hypoglycemia). Motivated by prior reports of glucagon-insulin co-infusion, we designed and tested an ultra-stable glucagon-insulin fusion protein whose relative hormonal activities were calibrated by respective modifications; physical stability was concurrently augmented to facilitate formulation, enhance shelf life and expand access. An N-terminal glucagon moiety was stabilized by an α-helix-compatible Lys 13 -Glu 17 lactam bridge; A C-terminal insulin moiety was stabilized as a single chain with foreshortened C domain. Studies in vitro demonstrated (a) resistance to fibrillation on prolonged agitation at 37 °C and (b) dual hormonal signaling activities with appropriate balance. Glucodynamic responses were monitored in rats relative to control fusion proteins lacking one or the other hormonal activity, and continuous intravenous infusion emulated basal subcutaneous therapy. Whereas efficacy in mitigating hyperglycemia was unaffected by the glucagon moiety, the fusion protein enhanced endogenous glucose production under hypoglycemic conditions. Together, these findings provide proof of principle toward a basal glucose-responsive insulin biotechnology of striking simplicity. The fusion protein's augmented stability promises to circumvent the costly cold chain presently constraining global insulin access. Significance Statement The therapeutic goal of insulin replacement therapy in diabetes is normalization of blood-glucose concentration, which prevents or delays long-term complications. A critical barrier is posed by recurrent hypoglycemic events that results in short- and long-term morbidities. An innovative approach envisions co-injection of glucagon (a counter-regulatory hormone) to exploit a glycemia-dependent hepatic switch in relative hormone responsiveness. To provide an enabling technology, we describe an ultra-stable fusion protein containing insulin- and glucagon moieties. Proof of principle was obtained in rats. A single-chain insulin moiety provides glycemic control whereas a lactam-stabilized glucagon extension mitigates hypoglycemia. This dual-hormone fusion protein promises to provide a basal formulation with reduced risk of hypoglycemia. Resistance to fibrillation may circumvent the cold chain required for global access.
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Dyess RJ, McKay T, Feygin Y, Wintergerst K, Thrasher BJ. Factory-Calibrated Continuous Glucose Monitoring System Accuracy During Exercise in Adolescents With Type 1 Diabetes Mellitus. J Diabetes Sci Technol 2024; 18:584-591. [PMID: 36047647 PMCID: PMC11089875 DOI: 10.1177/19322968221120433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Continuous glucose monitors (CGMs) are widely used for individuals with diabetes mellitus, particularly those with type 1 diabetes (T1D). Advancements in CGM technology allow for glycemic assessment without capillary glucose measurements as many come factory calibrated. However, exercise, an essential component of diabetes care, has been reported to alter accuracy of earlier generation CGM. Considering the importance of physical activity for individuals with T1D and the progression of CGM technology, we aimed to investigate the accuracy of the Dexcom G6 during physical activity. METHODS Adolescents (ages 13-20 years) exercised on a treadmill for 40 minutes, with a 10-minute break at minute 20. We obtained paired CGM and glucometer measurements before and every 10 minutes during and after exercise. Accuracy analysis was determined by mean absolute relative difference (MARD), mean absolute difference (MAD), and Clarke Error Grid Analyses. RESULTS Mean absolute relative difference and MAD increased during exercise (14%-33% and 24.3-34 mg/dL) but improved after exercise. We noted certain CGM locations produced greater changes in accuracy as MARD and MAD increased markedly when the CGM was on the buttocks (18%-46% and 30-41 mg/dL). We also noted decreased odds of Zone A in the Clarke error grid when the CGM was on the buttocks compared to the abdomen (odds ratio [OR]: 0.146; P = 0.0003; 95% CI = 0.052-0.415). CONCLUSIONS This CGM system showed alterations in accuracy during exercise. Our findings additionally suggest interstitial fluid changes in muscles during exercise alter accuracy of CGM; however, additional research is required.
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Affiliation(s)
- Ryan J. Dyess
- Division of Pediatric Endocrinology, Department of Pediatrics, University of Louisville School of Medicine, Louisville, KY, USA
- Wendy Novak Diabetes Center and University of Louisville School of Medicine, Louisville, KY, USA
- Norton Children’s Medical Group and University of Louisville School of Medicine, Louisville, KY, USA
| | - Timothy McKay
- Wendy Novak Diabetes Center and University of Louisville School of Medicine, Louisville, KY, USA
- Norton Children’s Research Institute and University of Louisville School of Medicine, Louisville, KY, USA
| | - Yana Feygin
- Norton Children’s Research Institute and University of Louisville School of Medicine, Louisville, KY, USA
| | - Kupper Wintergerst
- Division of Pediatric Endocrinology, Department of Pediatrics, University of Louisville School of Medicine, Louisville, KY, USA
- Wendy Novak Diabetes Center and University of Louisville School of Medicine, Louisville, KY, USA
- Norton Children’s Medical Group and University of Louisville School of Medicine, Louisville, KY, USA
| | - Bradly J. Thrasher
- Division of Pediatric Endocrinology, Department of Pediatrics, University of Louisville School of Medicine, Louisville, KY, USA
- Wendy Novak Diabetes Center and University of Louisville School of Medicine, Louisville, KY, USA
- Norton Children’s Medical Group and University of Louisville School of Medicine, Louisville, KY, USA
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Zhu T, Kuang L, Piao C, Zeng J, Li K, Georgiou P. Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2024; 18:236-246. [PMID: 38163299 DOI: 10.1109/tbcas.2023.3348844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
Leveraging continuous glucose monitoring (CGM) systems, real-time blood glucose (BG) forecasting is essential for proactive interventions, playing a crucial role in enhancing the management of type 1 diabetes (T1D) and type 2 diabetes (T2D). However, developing a model generalized to a population and subsequently embedding it within a microchip of a wearable device presents significant technical challenges. Furthermore, the domain of BG prediction in T2D remains under-explored in the literature. In light of this, we propose a population-specific BG prediction model, leveraging the capabilities of the temporal fusion Transformer (TFT) to adjust predictions based on personal demographic data. Then the trained model is embedded within a system-on-chip, integral to our low-power and low-cost customized wearable device. This device seamlessly communicates with CGM systems through Bluetooth and provides timely BG predictions using edge computing. When evaluated on two publicly available clinical datasets with a total of 124 participants with T1D or T2D, the embedded TFT model consistently demonstrated superior performance, achieving the lowest prediction errors when compared with a range of machine learning baseline methods. Executing the TFT model on our wearable device requires minimal memory and power consumption, enabling continuous decision support for more than 51 days on a single Li-Poly battery charge. These findings demonstrate the significant potential of the proposed TFT model and wearable device in enhancing the quality of life for people with diabetes and effectively addressing real-world challenges.
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Vulpe G, Liu G, Oakley S, Yang G, Ajith Mohan A, Waldron M, Sharma S. Lab on skin: real-time metabolite monitoring with polyphenol film based subdermal wearable patches. LAB ON A CHIP 2024; 24:2039-2048. [PMID: 38411270 DOI: 10.1039/d4lc00073k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
The advent of digital technologies has spurred the development of wearable sensing devices marking a significant shift in obtaining real-time physiological information. The principal objective is to transition from blood-centric monitoring to minimally invasive modalities, which will enable movement from specialised settings to more accessible environments such as the practices of general practitioners or even home settings. While subcutaneously implanted continuous monitoring devices have demonstrated this transition, detection of analytes from sample matrices like skin interstitial fluid (ISF), is a frontier that offers attractive minimally invasive routes for detection of biomarkers. This manuscript presents a comprehensive overview of our work in subdermal wearable biosensing patches for the simultaneous monitoring of glucose and lactate from ISF in ambulatory conditions. The performance of the subdermal wearable glucose monitoring patch was evaluated over a duration of three days, which is the longest reported duration reported till date. The subdermal wearable lactate sensing patch was worn for the duration of the exercise. Our findings highlight a critical observation that biofouling effects become apparent after a 24 h period. The data presented in this manuscript extends on the knowledge in the areas of continuous metabolite monitoring by introducing multifunctional polyphenol polymer films that can be used for both glucose and lactate monitoring with appropriate modifications. This study underscores the potential of subdermal wearable patches as versatile tools for real-time metabolite monitoring, positioning them as valuable assets in the evolution of personalised healthcare in diverse settings.
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Affiliation(s)
- Georgeta Vulpe
- Faculty of Science and Engineering, Swansea University, Fabian Way, Bay Campus, Swansea SA1 8EN, UK.
| | - Guoyi Liu
- Faculty of Science and Engineering, Swansea University, Fabian Way, Bay Campus, Swansea SA1 8EN, UK.
- Key Laboratory of Optoelectronic Technology & Systems (Chongqing University), Chongqing 400044, China
| | - Sam Oakley
- Faculty of Science and Engineering, Swansea University, Fabian Way, Bay Campus, Swansea SA1 8EN, UK.
| | - Guanghao Yang
- Faculty of Science and Engineering, Swansea University, Fabian Way, Bay Campus, Swansea SA1 8EN, UK.
- Key Laboratory of Optoelectronic Technology & Systems (Chongqing University), Chongqing 400044, China
| | - Arjun Ajith Mohan
- Faculty of Science and Engineering, Swansea University, Fabian Way, Bay Campus, Swansea SA1 8EN, UK.
| | - Mark Waldron
- Faculty of Science and Engineering, Swansea University, Fabian Way, Bay Campus, Swansea SA1 8EN, UK.
| | - Sanjiv Sharma
- Faculty of Science and Engineering, Swansea University, Fabian Way, Bay Campus, Swansea SA1 8EN, UK.
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Tozzo V, Genco M, Omololu SO, Mow C, Patel HR, Patel CH, Ho SN, Lam E, Abdulsater B, Patel N, Cohen RM, Nathan DM, Powe CE, Wexler DJ, Higgins JM. Estimating Glycemia From HbA1c and CGM: Analysis of Accuracy and Sources of Discrepancy. Diabetes Care 2024; 47:460-466. [PMID: 38394636 PMCID: PMC10909686 DOI: 10.2337/dc23-1177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 12/12/2023] [Indexed: 02/25/2024]
Abstract
OBJECTIVE To examine the accuracy of different periods of continuous glucose monitoring (CGM), hemoglobin A1c (HbA1c), and their combination for estimating mean glycemia over 90 days (AG90). RESEARCH DESIGN AND METHODS We retrospectively studied 985 CGM periods of 90 days with <10% missing data from 315 adults (86% of whom had type 1 diabetes) with paired HbA1c measurements. The impact of mean red blood cell age as a proxy for nonglycemic effects on HbA1c was estimated using published theoretical models and in comparison with empirical data. Given the lack of a gold standard measurement for AG90, we applied correction methods to generate a reference (eAG90) that we used to assess accuracy for HbA1c and CGM. RESULTS Using 14 days of CGM at the end of the 90-day period resulted in a mean absolute error (95th percentile) of 14 (34) mg/dL when compared with eAG90. Nonglycemic effects on HbA1c led to a mean absolute error for average glucose calculated from HbA1c of 12 (29) mg/dL. Combining 14 days of CGM with HbA1c reduced the error to 10 (26) mg/dL. Mismatches between CGM and HbA1c >40 mg/dL occurred more than 5% of the time. CONCLUSIONS The accuracy of estimates of eAG90 from limited periods of CGM can be improved by averaging with an HbA1c-based estimate or extending the monitoring period beyond ∼26 days. Large mismatches between eAG90 estimated from CGM and HbA1c are not unusual and may persist due to stable nonglycemic factors.
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Affiliation(s)
- Veronica Tozzo
- Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA
- Department of Systems Biology, Harvard Medical School, Boston, MA
| | - Matthew Genco
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Cincinnati College of Medicine, Cincinnati, OH
- Medical Service, Cincinnati Veterans Affairs Medical Center, Cincinnati, OH
| | | | - Christopher Mow
- Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA
- Mass General Brigham Enterprise Research IS, Boston, MA
| | - Hasmukh R. Patel
- Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA
| | - Chhaya H. Patel
- Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA
| | - Samantha N. Ho
- Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA
| | - Evie Lam
- Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA
| | - Batoul Abdulsater
- Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA
| | - Nikita Patel
- Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA
| | - Robert M. Cohen
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Cincinnati College of Medicine, Cincinnati, OH
- Medical Service, Cincinnati Veterans Affairs Medical Center, Cincinnati, OH
| | - David M. Nathan
- Diabetes Research Center, Department of Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
| | - Camille E. Powe
- Diabetes Research Center, Department of Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
- Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA
- Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA
| | - Deborah J. Wexler
- Diabetes Research Center, Department of Medicine, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
| | - John M. Higgins
- Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA
- Department of Systems Biology, Harvard Medical School, Boston, MA
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11
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Moser O, Pemberton JS. Rethinking the safety and efficacy assessment of (Hybrid) Closed Loop systems: Should we promote the need for a minimum of exercise data within the regulatory approval? Diabet Med 2024; 41:e15305. [PMID: 38332559 DOI: 10.1111/dme.15305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Affiliation(s)
- Othmar Moser
- Department of Exercise Physiology and Metabolism, University of Bayreuth, Bayreuth, Germany
- Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria
| | - John S Pemberton
- Department of Endocrinology and Diabetes, Birmingham Children's Hospital, Birmingham Women's, and Children's NHS Foundation Trust, Birmingham, UK
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12
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Dave D, Vyas K, Branan K, McKay S, DeSalvo DJ, Gutierrez-Osuna R, Cote GL, Erraguntla M. Detection of Hypoglycemia and Hyperglycemia Using Noninvasive Wearable Sensors: Electrocardiograms and Accelerometry. J Diabetes Sci Technol 2024; 18:351-362. [PMID: 35927975 PMCID: PMC10973850 DOI: 10.1177/19322968221116393] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Monitoring glucose excursions is important in diabetes management. This can be achieved using continuous glucose monitors (CGMs). However, CGMs are expensive and invasive. Thus, alternative low-cost noninvasive wearable sensors capable of predicting glycemic excursions could be a game changer to manage diabetes. METHODS In this article, we explore two noninvasive sensor modalities, electrocardiograms (ECGs) and accelerometers, collected on five healthy participants over two weeks, to predict both hypoglycemic and hyperglycemic excursions. We extract 29 features encompassing heart rate variability features from the ECG, and time- and frequency-domain features from the accelerometer. We evaluated two machine learning approaches to predict glycemic excursions: a classification model and a regression model. RESULTS The best model for both hypoglycemia and hyperglycemia detection was the regression model based on ECG and accelerometer data, yielding 76% sensitivity and specificity for hypoglycemia and 79% sensitivity and specificity for hyperglycemia. This had an improvement of 5% in sensitivity and specificity for both hypoglycemia and hyperglycemia when compared with using ECG data alone. CONCLUSIONS Electrocardiogram is a promising alternative not only to detect hypoglycemia but also to predict hyperglycemia. Supplementing ECG data with contextual information from accelerometer data can improve glucose prediction.
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Affiliation(s)
- Darpit Dave
- Wm Michael Barnes '64 Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, USA
| | - Kathan Vyas
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
| | - Kimberly Branan
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA
| | - Siripoom McKay
- Baylor College of Medicine, Houston, TX, USA
- Texas Children’s Hospital Clinical Care Center, Houston, TX, USA
| | - Daniel J. DeSalvo
- Baylor College of Medicine, Houston, TX, USA
- Texas Children’s Hospital Clinical Care Center, Houston, TX, USA
| | - Ricardo Gutierrez-Osuna
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
| | - Gerard L. Cote
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA
| | - Madhav Erraguntla
- Wm Michael Barnes '64 Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, USA
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13
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O'Neal DN, Zaharieva DP, Morrison D, McCarthy O, Nørgaard K. Exercising Safely with the MiniMed™ 780G Automated Insulin Delivery System. Diabetes Technol Ther 2024; 26:84-96. [PMID: 38377316 DOI: 10.1089/dia.2023.0420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
The physical and psychological benefits of exercise are particularly pertinent to people with type 1 diabetes (T1D). The variability in subcutaneous insulin absorption and the delay in offset and onset in glucose lowering action impose limitations, given the rapidly varying insulin requirements with exercise. Simultaneously, there are challenges to glucose monitoring. Consequently, those with T1D are less likely to exercise because of concerns regarding glucose instability. While glucose control with exercise can be enhanced using automated insulin delivery (AID), all commercially available AID systems remain limited by the pharmacokinetics of subcutaneous insulin delivery. Although glycemic responses may vary with exercises of differing intensities and durations, the principles providing the foundation for guidelines include minimization of insulin on board before exercise commencement, judicious and timely carbohydrate supplementation, and when possible, a reduction in insulin delivered in anticipation of planned exercise. There is an increasing body of evidence in support of superior glucose control with AID over manual insulin dosing in people in T1D who wish to exercise. The MiniMed™ 780G AID system varies basal insulin delivery with superimposed automated correction boluses. It incorporates a temporary (elevated glucose) target of 8.3 mmol/L (150 mg/dL) and when it is functioning, the autocorrection boluses are stopped. As the device has recently become commercially available, there are limited data assessing glucose control with the MiniMed™ 780G under exercise conditions. Importantly, when exercise was planned and implemented within consensus guidelines, %time in range and %time below range targets were met. A practical approach to exercising with the device is provided with illustrative case studies. While there are limitations to spontaneity imposed on any AID device due to the pharmacokinetics associated with the subcutaneous delivery of current insulin formulations, the MiniMed™ 780G system provides people with T1D an excellent option for exercising safely if the appropriate strategies are implemented.
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Affiliation(s)
- David N O'Neal
- Department of Medicine, The University of Melbourne, Parkville, Australia
- Department of Endocrinology, St. Vincent's Hospital Melbourne, Fitzroy, Australia
- Australian Centre for Accelerating Diabetes Innovations, Parkville, Australia
| | - Dessi P Zaharieva
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA
| | - Dale Morrison
- Department of Medicine, The University of Melbourne, Parkville, Australia
- Department of Endocrinology, St. Vincent's Hospital Melbourne, Fitzroy, Australia
- Australian Centre for Accelerating Diabetes Innovations, Parkville, Australia
| | - Olivia McCarthy
- Copenhagen University Hospital-Steno Diabetes Center Copenhagen, Herlev, Denmark
- Technology, Exercise and Medicine Research Centre, Applied Sport, Swansea University, Swansea, United Kingdom
| | - Kirsten Nørgaard
- Copenhagen University Hospital-Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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14
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Brummer J, Glasbrenner C, Hechenbichler Figueroa S, Koehler K, Höchsmann C. Continuous glucose monitoring for automatic real-time assessment of eating events and nutrition: a scoping review. Front Nutr 2024; 10:1308348. [PMID: 38264192 PMCID: PMC10804456 DOI: 10.3389/fnut.2023.1308348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 12/13/2023] [Indexed: 01/25/2024] Open
Abstract
Background Accurate dietary assessment remains a challenge, particularly in free-living settings. Continuous glucose monitoring (CGM) shows promise in optimizing the assessment and monitoring of ingestive activity (IA, i.e., consumption of calorie-containing foods/beverages), and it might enable administering dietary Just-In-Time Adaptive Interventions (JITAIs). Objective In a scoping review, we aimed to answer the following questions: (1) Which CGM approaches to automatically detect IA in (near-)real-time have been investigated? (2) How accurate are these approaches? (3) Can they be used in the context of JITAIs? Methods We systematically searched four databases until October 2023 and included publications in English or German that used CGM-based approaches for human (all ages) IA detection. Eligible publications included a ground-truth method as a comparator. We synthesized the evidence qualitatively and critically appraised publication quality. Results Of 1,561 potentially relevant publications identified, 19 publications (17 studies, total N = 311; for 2 studies, 2 publications each were relevant) were included. Most publications included individuals with diabetes, often using meal announcements and/or insulin boluses accompanying meals. Inpatient and free-living settings were used. CGM-only approaches and CGM combined with additional inputs were deployed. A broad range of algorithms was tested. Performance varied among the reviewed methods, ranging from unsatisfactory to excellent (e.g., 21% vs. 100% sensitivity). Detection times ranged from 9.0 to 45.0 min. Conclusion Several CGM-based approaches are promising for automatically detecting IA. However, response times need to be faster to enable JITAIs aimed at impacting acute IA. Methodological issues and overall heterogeneity among articles prevent recommending one single approach; specific cases will dictate the most suitable approach.
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15
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Tucker AP, Erdman AG, Schreiner PJ, Ma S, Chow LS. Neural Networks With Gated Recurrent Units Reduce Glucose Forecasting Error Due to Changes in Sensor Location. J Diabetes Sci Technol 2024; 18:124-134. [PMID: 35658633 PMCID: PMC10899835 DOI: 10.1177/19322968221100839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Continuous glucose monitors (CGMs) have become important tools for providing estimates of glucose to patients with diabetes. Recently, neural networks (NNs) have become a common method for forecasting glucose values using data from CGMs. One method of forecasting glucose values is a time-delay feedforward (FF) NN, but a change in the CGM location on a participant can increase forecast error in a FF NN. METHODS In response, we examined a NN with gated recurrent units (GRUs) as a method of reducing forecast error due to changes in sensor location. RESULTS We observed that for 13 participants with type 2 diabetes wearing blinded CGMs on both arms for 12 weeks (FreeStyle Libre Pro-Abbott), GRU NNs did not produce significantly different errors in glucose prediction due to sensor location changes (P < .05). CONCLUSION We observe that GRU NNs can mitigate error in glucose prediction due to differences in CGM location.
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Affiliation(s)
- Aaron P. Tucker
- Earl E. Bakken Medical Devices Center, University of Minnesota, Minneapolis, MN, USA
| | - Arthur G. Erdman
- Earl E. Bakken Medical Devices Center, University of Minnesota, Minneapolis, MN, USA
| | - Pamela J. Schreiner
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Sisi Ma
- Division of General Internal Medicine, University of Minnesota, Minneapolis, MN, USA
| | - Lisa S. Chow
- Division of Diabetes, Endocrinology and Metabolism, University of Minnesota, Minneapolis, MN, USA
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Zimmer RT, Auth A, Schierbauer J, Haupt S, Wachsmuth N, Zimmermann P, Voit T, Battelino T, Sourij H, Moser O. (Hybrid) Closed-Loop Systems: From Announced to Unannounced Exercise. Diabetes Technol Ther 2023. [PMID: 38133645 DOI: 10.1089/dia.2023.0293] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Physical activity and exercise have many beneficial effects on general and type 1 diabetes (T1D) specific health and are recommended for individuals with T1D. Despite these health benefits, many people with T1D still avoid exercise since glycemic management during physical activity poses substantial glycemic and psychological challenges - which hold particularly true for unannounced exercise when using an AID system. Automated insulin delivery (AID) systems have demonstrated their efficacy in improving overall glycemia and in managing announced exercise in numerous studies. They are proven to increase time in range (70-180 mg/dL) and can especially counteract nocturnal hypoglycemia, even when evening exercise was performed. AID-systems consist of a pump administering insulin as well as a CGM sensor (plus transmitter), both communicating with a control algorithm integrated into a device (insulin pump, mobile phone/smart watch). Nevertheless, without manual pre-exercise adaptions, these systems still face a significant challenge around physical activity. Automatically adapting to the rapidly changing insulin requirements during unannounced exercise and physical activity is still the Achilles' heel of current AID systems. There is an urgent need for improving current AID-systems to safely and automatically maintain glucose management without causing derailments - so that going forward, exercise announcements will not be necessary in the future. Therefore, this narrative literature review aimed to discuss technological strategies to how current AID-systems can be improved in the future and become more proficient in overcoming the hurdle of unannounced exercise. For this purpose, the current state-of-the-art therapy recommendations for AID and exercise as well as novel research approaches are presented along with potential future solutions - in order to rectify their deficiencies in the endeavor to achieve fully automated AID-systems even around unannounced exercise.
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Affiliation(s)
- Rebecca Tanja Zimmer
- University of Bayreuth, 26523, Division Exercise Physiology and Metabolism Institute of Sport Science, Bayreuth, Bavaria, Germany;
| | - Alexander Auth
- University of Bayreuth, 26523, Division Exercise Physiology and Metabolism Institute of Sport Science, Bayreuth, Bavaria, Germany;
| | - Janis Schierbauer
- University of Bayreuth, 26523, Division Exercise Physiology and Metabolism Institute of Sport Science, Bayreuth, Bavaria, Germany;
| | - Sandra Haupt
- University of Bayreuth, 26523, Division Exercise Physiology and Metabolism Institute of Sport Science, Bayreuth, Bavaria, Germany;
| | - Nadine Wachsmuth
- University of Bayreuth, 26523, Division Exercise Physiology and Metabolism Institute of Sport Science, Bayreuth, Bavaria, Germany;
| | - Paul Zimmermann
- University of Bayreuth, 26523, Division Exercise Physiology and Metabolism Institute of Sport Science, Bayreuth, Bavaria, Germany;
| | - Thomas Voit
- University of Bayreuth, 26523, Division Exercise Physiology and Metabolism Institute of Sport Science, Bayreuth, Bavaria, Germany;
| | - Tadej Battelino
- University Children's Hospital, Ljubljana, Slovenia, Department of Endocrinology, Diabetes and Metabolism, Bohoriceva 20, Ljubljana, Slovenia, 1000
- Slovenia;
| | - Harald Sourij
- Medical University of Graz, 31475, Auenbruggerplatz 15, 8036 Graz, Graz, Austria, 8036;
| | - Othmar Moser
- University of Bayreuth, 26523, Division Exercise Physiology and Metabolism Institute of Sport Science, Universitätsstraße 30, Bayreuth, Bayern, Germany, 95440;
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Lundemose SB, Laugesen C, Ranjan AG, Nørgaard K. Factory-Calibrated Continuous Glucose Monitoring Systems in Type 1 Diabetes: Accuracy during In-Clinic Exercise and Home Use. SENSORS (BASEL, SWITZERLAND) 2023; 23:9256. [PMID: 38005642 PMCID: PMC10675113 DOI: 10.3390/s23229256] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/06/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023]
Abstract
Continuous glucose monitors (CGMs) are valuable tools for improving glycemic control, yet their accuracy might be influenced by physical activity. This study sought to assess the accuracy of the three latest factory-calibrated CGM systems available in Europe at the time the study was conducted, both during aerobic exercise and in typical daily scenarios. The accuracy evaluation, based on metrics such as the median absolute relative difference (MARD) and point and rate error-grid analyses (PEGA and REGA), involved 13 adults with type 1 diabetes. Participants wore all sensors during a 1 h in-clinic exercise session followed by a subsequent 3-day home period, with blood glucose measurements serving as reference values in both contexts. During exercise, no statistically significant differences in MARD were observed (Dexcom G6: 12.6%, Guardian 4: 10.7%, and Freestyle Libre 2: 17.2%; p = 0.31), and similarly, no significant differences emerged in PEGA-zone-AB (100%, 100%, 96.8%; p = 0.37). Nevertheless, Freestyle Libre 2 showed comparatively diminished accuracy in estimating glucose trends during exercise (REGA-zone-AB: 100%, 93.0%, 73.3%; p = 0.0003). In the home environment, Freestyle Libre 2 exhibited a significantly higher MARD when compared to the other systems (10.2%, 11.9%, 16.7%, p = 0.02). Overall, Dexcom G6 and Guardian 4 demonstrated superior accuracy in both exercise and daily life scenarios compared to Freestyle Libre 2.
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Affiliation(s)
- Sissel Banner Lundemose
- Steno Diabetes Center Copenhagen, Clinical Research, Diabetes Technology Research, Borgmester Ib Juuls Vej 83, DK-2730 Herlev, Denmark; (C.L.); (A.G.R.); (K.N.)
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18
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Kistkins S, Mihailovs T, Lobanovs S, Pīrāgs V, Sourij H, Moser O, Bļizņuks D. Comparative Analysis of Predictive Interstitial Glucose Level Classification Models. SENSORS (BASEL, SWITZERLAND) 2023; 23:8269. [PMID: 37837098 PMCID: PMC10574913 DOI: 10.3390/s23198269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/02/2023] [Accepted: 10/04/2023] [Indexed: 10/15/2023]
Abstract
BACKGROUND New methods of continuous glucose monitoring (CGM) provide real-time alerts for hypoglycemia, hyperglycemia, and rapid fluctuations of glucose levels, thereby improving glycemic control, which is especially crucial during meals and physical activity. However, complex CGM systems pose challenges for individuals with diabetes and healthcare professionals, particularly when interpreting rapid glucose level changes, dealing with sensor delays (approximately a 10 min difference between interstitial and plasma glucose readings), and addressing potential malfunctions. The development of advanced predictive glucose level classification models becomes imperative for optimizing insulin dosing and managing daily activities. METHODS The aim of this study was to investigate the efficacy of three different predictive models for the glucose level classification: (1) an autoregressive integrated moving average model (ARIMA), (2) logistic regression, and (3) long short-term memory networks (LSTM). The performance of these models was evaluated in predicting hypoglycemia (<70 mg/dL), euglycemia (70-180 mg/dL), and hyperglycemia (>180 mg/dL) classes 15 min and 1 h ahead. More specifically, the confusion matrices were obtained and metrics such as precision, recall, and accuracy were computed for each model at each predictive horizon. RESULTS As expected, ARIMA underperformed the other models in predicting hyper- and hypoglycemia classes for both the 15 min and 1 h horizons. For the 15 min forecast horizon, the performance of logistic regression was the highest of all the models for all glycemia classes, with recall rates of 96% for hyper, 91% for norm, and 98% for hypoglycemia. For the 1 h forecast horizon, the LSTM model turned out to be the best for hyper- and hypoglycemia classes, achieving recall values of 85% and 87% respectively. CONCLUSIONS Our findings suggest that different models may have varying strengths and weaknesses in predicting glucose level classes, and the choice of model should be carefully considered based on the specific requirements and context of the clinical application. The logistic regression model proved to be more accurate for the next 15 min, particularly in predicting hypoglycemia. However, the LSTM model outperformed logistic regression in predicting glucose level class for the next hour. Future research could explore hybrid models or ensemble approaches that combine the strengths of multiple models to further enhance the accuracy and reliability of glucose predictions.
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Affiliation(s)
- Svjatoslavs Kistkins
- Research Institute of Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia; (S.K.); (V.P.)
| | - Timurs Mihailovs
- Institute of Smart Computing Technologies, Riga Technical University, LV-1048 Riga, Latvia; (T.M.); (D.B.)
| | - Sergejs Lobanovs
- Research Institute of Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia; (S.K.); (V.P.)
| | - Valdis Pīrāgs
- Research Institute of Pauls Stradins Clinical University Hospital, LV-1002 Riga, Latvia; (S.K.); (V.P.)
| | - Harald Sourij
- Interdisciplinary Metabolic Medicine Trials Unit, Division of Endocrinology and Diabetology, Medical University of Graz, 8010 Graz, Austria;
| | - Othmar Moser
- Division of Exercise Physiology and Metabolism, Institute of Sport Science, University of Bayreuth, 95447 Bayreuth, Germany;
| | - Dmitrijs Bļizņuks
- Institute of Smart Computing Technologies, Riga Technical University, LV-1048 Riga, Latvia; (T.M.); (D.B.)
- SIA “R4U”, LV-1016 Riga, Latvia
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19
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Bauhaus H, Erdogan P, Braun H, Thevis M. Continuous Glucose Monitoring (CGM) in Sports-A Comparison between a CGM Device and Lab-Based Glucose Analyser under Resting and Exercising Conditions in Athletes. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6440. [PMID: 37568982 PMCID: PMC10418731 DOI: 10.3390/ijerph20156440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/12/2023] [Accepted: 07/19/2023] [Indexed: 08/13/2023]
Abstract
The objective of this pilot study was to compare glucose concentrations in capillary blood (CB) samples analysed in a laboratory by a validated method and glucose concentrations measured in the interstitial fluid (ISF) by continuous glucose monitoring (CGM) under different physical activity levels in a postprandial state in healthy athletes without diabetes. As a physiological shift occurs between glucose concentration from the CB into the ISF, the applicability of CGM in sports, especially during exercise, as well as the comparability of CB and ISF data necessitate an in-depth assessment. Ten subjects (26 ± 4 years, 67 ± 11 kg bodyweight (BW), 11 ± 3 h) were included in the study. Within 14 days, they underwent six tests consisting of (a) two tests resting fasted (HC_Rest/Fast and LC_Rest/Fast), (b) two tests resting with intake of 1 g glucose/kg BW (HC_Rest/Glc and LC_Rest/Glc), (c) running for 60 min at moderate (ModExerc/Glc), and (d) high intensity after intake of 1 g glucose/kg BW (IntExerc/Glc). Data were collected in the morning, following a standardised dinner before test day. Sensor-based glucose concentrations were compared to those determined from capillary blood samples collected at the time of sensor-based analyses and subjected to laboratory glucose measurements. Pearson's r correlation coefficient was highest for Rest/Glc (0.92, p < 0.001) compared to Rest/Fast (0.45, p < 0.001), ModExerc/Glc (0.60, p < 0.001) and IntExerc/Glc (0.70, p < 0.001). Mean absolute relative deviation (MARD) and standard deviation (SD) was smallest for resting fasted and similar between all other conditions (Rest/Fast: 8 ± 6%, Rest/Glc: 17 ± 12%, ModExerc/Glc: 22 ± 24%, IntExerc/Glc: 18 ± 17%). However, Bland-Altman plot analysis showed a higher range between lower and upper limits of agreement (95% confidence interval) of paired data under exercising compared to resting conditions. Under resting fasted conditions, both methods produce similar outcomes. Under resting postprandial and exercising conditions, respectively, there are differences between both methods. Based on the results of this study, the application of CGM in healthy athletes is not recommended without concomitant nutritional or medical advice.
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Affiliation(s)
- Helen Bauhaus
- Institute of Biochemistry, German Sport University Cologne, 50933 Cologne, Germany
- German Research Centre of Elite Sports, German Sport University Cologne, 50933 Cologne, Germany;
| | - Pinar Erdogan
- Institute of Biochemistry, German Sport University Cologne, 50933 Cologne, Germany
- German Research Centre of Elite Sports, German Sport University Cologne, 50933 Cologne, Germany;
| | - Hans Braun
- German Research Centre of Elite Sports, German Sport University Cologne, 50933 Cologne, Germany;
- Manfred Donike Institute for Doping Analysis, 50933 Cologne, Germany
| | - Mario Thevis
- Institute of Biochemistry, German Sport University Cologne, 50933 Cologne, Germany
- German Research Centre of Elite Sports, German Sport University Cologne, 50933 Cologne, Germany;
- Manfred Donike Institute for Doping Analysis, 50933 Cologne, Germany
- Centre for Preventive Doping Research, German Sport University Cologne, 50933 Cologne, Germany
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20
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Bishop FK, Addala A, Corbin KD, Muntis FR, Pratley RE, Riddell MC, Mayer-Davis EJ, Maahs DM, Zaharieva DP. An Overview of Diet and Physical Activity for Healthy Weight in Adolescents and Young Adults with Type 1 Diabetes: Lessons Learned from the ACT1ON Consortium. Nutrients 2023; 15:nu15112500. [PMID: 37299463 DOI: 10.3390/nu15112500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 05/18/2023] [Accepted: 05/24/2023] [Indexed: 06/12/2023] Open
Abstract
The prevalence of overweight and obesity in young people with type 1 diabetes (T1D) now parallels that of the general population. Excess adiposity increases the risk of cardiovascular disease, which is already elevated up to 10-fold in T1D, underscoring a compelling need to address weight management as part of routine T1D care. Sustainable weight management requires both diet and physical activity (PA). Diet and PA approaches must be optimized towards the underlying metabolic and behavioral challenges unique to T1D to support glycemic control throughout the day. Diet strategies for people with T1D need to take into consideration glycemic management, metabolic status, clinical goals, personal preferences, and sociocultural considerations. A major barrier to weight management in this high-risk population is the challenge of integrating regular PA with day-to-day management of T1D. Specifically, exercise poses a substantial challenge due to the increased risk of hypoglycemia and/or hyperglycemia. Indeed, about two-thirds of individuals with T1D do not engage in the recommended amount of PA. Hypoglycemia presents a serious health risk, yet prevention and treatment often necessitates the consumption of additional calories, which may prohibit weight loss over time. Exercising safely is a concern and challenge with weight management and maintaining cardiometabolic health for individuals living with T1D and many healthcare professionals. Thus, a tremendous opportunity exists to improve exercise participation and cardiometabolic outcomes in this population. This article will review dietary strategies, the role of combined PA and diet for weight management, current resources for PA and glucose management, barriers to PA adherence in adults with T1D, as well as findings and lessons learned from the Advancing Care for Type 1 Diabetes and Obesity Network (ACT1ON).
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Affiliation(s)
- Franziska K Bishop
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
| | - Ananta Addala
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
| | - Karen D Corbin
- AdventHealth, Translational Research Institute, Orlando, FL 32804, USA
| | - Franklin R Muntis
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Richard E Pratley
- AdventHealth, Translational Research Institute, Orlando, FL 32804, USA
| | - Michael C Riddell
- School of Kinesiology and Health Science, Muscle Health Research Centre, York University, Toronto, ON M3J 1P3, Canada
| | - Elizabeth J Mayer-Davis
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - David M Maahs
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
- Stanford Diabetes Research Center, Stanford, CA 94305, USA
| | - Dessi P Zaharieva
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
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Scott SN, Hayes C, Zeuger T, Davies AP, Andrews RC, Cocks M. Clinical Considerations and Practical Advice for People Living With Type 2 Diabetes Who Undertake Regular Exercise or Aim to Exercise Competitively. Diabetes Spectr 2023; 36:114-126. [PMID: 37193206 PMCID: PMC10182970 DOI: 10.2337/dsi22-0015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
This article provides practical tips for advising people with type 2 diabetes on how to engage in regular exercise safely and effectively. Its focus is on individuals who wish to exceed the minimum physical activity recommendation of 150 minutes/week of moderate-intensity exercise or even compete in their chosen sport. Health care professionals who work with such individuals must have a basic understanding of glucose metabolism during exercise, nutritional requirements, blood glucose management, medications, and sport-related considerations. This article reviews three key aspects of individualized care for physically active people with type 2 diabetes: 1) initial medical assessment and pre-exercise screenings, 2) glucose monitoring and nutritional considerations, and 3) the combined glycemic effects of exercise and medications.
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Affiliation(s)
- Sam N. Scott
- Team Novo Nordisk Professional Cycling Team, Atlanta, GA
| | | | - Thomas Zeuger
- Department of Endocrinology and Metabolic Diseases, Kantonsspital Olten, Olten, Switzerland
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern, University Hospital, University of Bern, Bern, Switzerland
| | - Andrew P. Davies
- Research Institute for Sport and Exercise Science, Liverpool John Moores University, Liverpool, U.K
| | - Rob C. Andrews
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K
| | - Matthew Cocks
- Research Institute for Sport and Exercise Science, Liverpool John Moores University, Liverpool, U.K
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22
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Zaharieva DP, Morrison D, Paldus B, Lal RA, Buckingham BA, O'Neal DN. Practical Aspects and Exercise Safety Benefits of Automated Insulin Delivery Systems in Type 1 Diabetes. Diabetes Spectr 2023; 36:127-136. [PMID: 37193203 PMCID: PMC10182962 DOI: 10.2337/dsi22-0018] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Regular exercise is essential to overall cardiovascular health and well-being in people with type 1 diabetes, but exercise can also lead to increased glycemic disturbances. Automated insulin delivery (AID) technology has been shown to modestly improve glycemic time in range (TIR) in adults with type 1 diabetes and significantly improve TIR in youth with type 1 diabetes. Available AID systems still require some user-initiated changes to the settings and, in some cases, significant pre-planning for exercise. Many exercise recommendations for type 1 diabetes were developed initially for people using multiple daily insulin injections or insulin pump therapy. This article highlights recommendations and practical strategies for using AID around exercise in type 1 diabetes.
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Affiliation(s)
- Dessi P Zaharieva
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Dale Morrison
- Department of Medicine, The University of Melbourne, Melbourne, Australia
| | - Barbora Paldus
- Department of Medicine, The University of Melbourne, Melbourne, Australia
- Department of Endocrinology & Diabetes, St Vincent's Hospital Melbourne, Melbourne, Australia
| | - Rayhan A Lal
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford, CA
- Division of Endocrinology, Department of Medicine, Stanford University School of Medicine, Stanford, CA
| | - Bruce A Buckingham
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford, CA
| | - David N O'Neal
- Department of Medicine, The University of Melbourne, Melbourne, Australia
- Department of Endocrinology & Diabetes, St Vincent's Hospital Melbourne, Melbourne, Australia
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23
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Davis EA, Shetty VB, Teo SY, Lim RJ, Patton SR, Taplin CE. Physical Activity Management for Youth With Type 1 Diabetes: Supporting Active and Inactive Children. Diabetes Spectr 2023; 36:137-145. [PMID: 37193201 PMCID: PMC10182969 DOI: 10.2337/dsi22-0020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Regular physical activity and exercise are important for youth and essential components of a healthy lifestyle. For youth with type 1 diabetes, regular physical activity can promote cardiovascular fitness, bone health, insulin sensitivity, and glucose management. However, the number of youth with type 1 diabetes who regularly meet minimum physical activity guidelines is low, and many encounter barriers to regular physical activity. Additionally, some health care professionals (HCPs) may be unsure how to approach the topic of exercise with youth and families in a busy clinic setting. This article provides an overview of current physical activity research in youth with type 1 diabetes, a basic description of exercise physiology in type 1 diabetes, and practical strategies for HCPs to conduct effective and individualized exercise consultations for youth with type 1 diabetes.
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Affiliation(s)
- Elizabeth A. Davis
- Department of Endocrinology and Diabetes, Perth Children’s Hospital, Perth, Western Australia, Australia
- Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
- Centre for Child Health Research, University of Western Australia, Perth, Western Australia, Australia
| | - Vinutha B. Shetty
- Department of Endocrinology and Diabetes, Perth Children’s Hospital, Perth, Western Australia, Australia
- Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
- Centre for Child Health Research, University of Western Australia, Perth, Western Australia, Australia
| | - Shaun Y.M. Teo
- Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
| | - Rachel J. Lim
- Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
| | | | - Craig E. Taplin
- Department of Endocrinology and Diabetes, Perth Children’s Hospital, Perth, Western Australia, Australia
- Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
- Centre for Child Health Research, University of Western Australia, Perth, Western Australia, Australia
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24
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Handy C, Chaudhry MS, Qureshi MRA, Love B, Shillingford J, Plum-Mörschel L, Zijlstra E. Noninvasive Continuous Glucose Monitoring With a Novel Wearable Dial Resonating Sensor: A Clinical Proof-of-Concept Study. J Diabetes Sci Technol 2023:19322968231170242. [PMID: 37102600 DOI: 10.1177/19322968231170242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
BACKGROUND A noninvasive, wearable continuous glucose monitor would be a major advancement in diabetes therapy. This trial investigated a novel noninvasive glucose monitor which analyzes spectral variations in radio frequency/microwave signals reflected from the wrist. METHODS A single-arm, open-label, experimental study compared glucose values from a prototype investigational device with laboratory glucose measurements from venous blood samples (Super GL Glucose Analyzer, Dr. Müller Gerätebau GmbH) at varying levels of glycemia. The study included 29 male participants with type 1 diabetes (age range = 19-56 years). The study comprised three stages with the following aims: (1) demonstrate initial proof-of-principle, (2) test an improved device design, and (3) test performance on two consecutive days without device recalibration. The co-primary endpoints in all trial stages were median and mean absolute relative difference (ARD) calculated across all data points. RESULTS In stage 1, the median and mean ARDs were 30% and 46%, respectively. Stage 2 produced marked performance improvements with a median and mean ARD of 22% and 28%, respectively. Stage 3 showed that, without recalibration, the device performed as well as the initial prototype (stage 1) with a median and mean ARD of 35% and 44%, respectively. CONCLUSION This proof-of-concept study shows that a novel noninvasive continuous glucose monitor was capable of detecting glucose levels. Furthermore, the ARD results are comparable to first models of commercially available minimally invasive products without the need to insert a needle. The prototype has been further developed and is being tested in subsequent studies. TRIAL REGISTRATION NUMBER NCT05023798.
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25
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Pemberton JS, Wilmot EG, Barnard-Kelly K, Leelarathna L, Oliver N, Randell T, Taplin CE, Choudhary P, Adolfsson P. CGM accuracy: Contrasting CE marking with the governmental controls of the USA (FDA) and Australia (TGA): A narrative review. Diabetes Obes Metab 2023; 25:916-939. [PMID: 36585365 DOI: 10.1111/dom.14962] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 12/12/2022] [Accepted: 12/23/2022] [Indexed: 01/01/2023]
Abstract
The National Institute for Clinical Excellence updated guidance for continuous glucose monitoring (CGM) in 2022, recommending that CGM be available to all people living with type 1 diabetes. Manufacturers can trade in the UK with Conformité Européenne (CE) marking without an initial national assessment. The regulatory process for CGM CE marking, in contrast to the Food and Drug Administration (FDA) and Australian Therapeutic Goods Administration (TGA) process, is described. Manufacturers operating in the UK provided clinical accuracy studies submitted for CE marking. Critical appraisal of the studies shows several CGM devices have CE marking for wide-ranging indications beyond available data, unlike FDA and TGA approval. The FDA and TGA use tighter controls, requiring comprehensive product-specific clinical data evaluation. In 2018, the FDA published the integrated CGM (iCGM) criteria permitting interoperability. Applying the iCGM criteria to clinical data provided by manufacturers trading in the UK identified several study protocols that minimized glucose variability, thereby improving CGM accuracy on all metrics. These results do not translate into real-life performance. Furthermore, for many CGM devices available in the UK, accuracy reported in the hypoglycaemic range is below iCGM standards, or measurement is absent. We offer a framework to evaluate CGM accuracy studies critically. The review concludes that FDA- and TGA-approved indications match the available clinical data, whereas CE marking indications can have discrepancies. The UK can bolster regulation with UK Conformity Assessed marking from January 2025. However, balanced regulation is needed to ensure innovation and timely technological access are not hindered.
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Affiliation(s)
- John S Pemberton
- Department of Endocrinology and Diabetes, Birmingham Children's Hospital, Birmingham Women's, and Children's NHS Foundation Trust, Birmingham, UK
| | - Emma G Wilmot
- University Hospitals of Derby and Burton NHS Foundation Trust, Derby, UK
- University of Nottingham, Nottingham, UK
| | | | - Lalantha Leelarathna
- Manchester Diabetes Centre, Manchester Royal Infirmary, 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
| | - Nick Oliver
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | | | - Craig E Taplin
- Department of Endocrinology and Diabetes, Perth Children's Hospital, Perth, Australia
- Telethon Kids Institute, University of Western Australia, Perth, Australia
- Centre for Child Health Research, University of Western Australia, Perth, Australia
| | - Pratik Choudhary
- Leicester Diabetes Center, University of Leicester, Leicester, UK
| | - Peter Adolfsson
- Department of Paediatrics, Kungsbacka Hospital; Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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26
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Friedman JG, Cardona Matos Z, Szmuilowicz ED, Aleppo G. Use of Continuous Glucose Monitors to Manage Type 1 Diabetes Mellitus: Progress, Challenges, and Recommendations. Pharmgenomics Pers Med 2023; 16:263-276. [PMID: 37025558 PMCID: PMC10072139 DOI: 10.2147/pgpm.s374663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/25/2023] [Indexed: 04/08/2023] Open
Abstract
Type 1 diabetes (T1D) management has been revolutionized with the development and routine utilization of continuous glucose monitoring (CGM). CGM technology has allowed for the ability to track dynamic glycemic fluctuations and trends over time allowing for optimization of medical therapy and the prevention of dangerous hypoglycemic events. This review details currently-available real-time and intermittently-scanned CGM devices, clinical benefits, and challenges of CGM use, and current guidelines supporting its use in the clinical care of patients with T1D. We additionally describe future issues that will need to be addressed as CGM technology continues to evolve.
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Affiliation(s)
- Jared G Friedman
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Zulma Cardona Matos
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Emily D Szmuilowicz
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
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27
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Sheng T, Jin R, Yang C, Qiu K, Wang M, Shi J, Zhang J, Gao Y, Wu Q, Zhou X, Wang H, Zhang J, Fang Q, Pan N, Xue Y, Wang Y, Xiong R, Gao F, Zhang Y, Lu H, Yu J, Gu Z. Unmanned Aerial Vehicle Mediated Drug Delivery for First Aid. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2208648. [PMID: 36563167 DOI: 10.1002/adma.202208648] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/31/2022] [Indexed: 06/17/2023]
Abstract
Timely administration of key medications toward patients with sudden diseases is critical to saving lives. However, slow transport of first-aid therapeutics and the potential absence of trained people for drug usage can lead to severe injuries or even death. Herein, an unmanned aerial vehicle (UAV)-mediated first-aid system for targeted delivery (uFAST) is developed. It allows unattended administration of emergency therapeutics-loaded transdermal microneedle (MN) patches toward patients to relieve symptoms by a contact-triggered microneedle applicator (CTMA). The implementability and safety of the uFAST for first aid is demonstrated in a severe hypoglycemic pig model by automatically delivering a glucagon patch with immediate and bioresponsive dual release modes. This platform technique may facilitate the development of UAV-mediated first-aid treatments for other sudden diseases.
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Affiliation(s)
- Tao Sheng
- Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Rui Jin
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
- Huzhou Institute of Zhejiang University, Huzhou, 313000, China
| | - Changwei Yang
- Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Ke Qiu
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
| | - Mingyang Wang
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
- Huzhou Institute of Zhejiang University, Huzhou, 313000, China
| | - Jiaqi Shi
- Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Jingyu Zhang
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
| | - Yuman Gao
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
- Huzhou Institute of Zhejiang University, Huzhou, 313000, China
| | - Qing Wu
- Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Xin Zhou
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
- Huzhou Institute of Zhejiang University, Huzhou, 313000, China
| | - Hao Wang
- Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Juan Zhang
- Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Qin Fang
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
| | - Neng Pan
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
- Huzhou Institute of Zhejiang University, Huzhou, 313000, China
| | - Yanan Xue
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
| | - Yue Wang
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
| | - Rong Xiong
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
| | - Fei Gao
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
- Huzhou Institute of Zhejiang University, Huzhou, 313000, China
| | - Yuqi Zhang
- Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- Department of Burns and Wound Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China
| | - Haojian Lu
- State Key Laboratory of Industrial Control and Technology, Zhejiang University, Hangzhou, 310027, China
- Institute of Cyber-Systems and Control, the Department of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Reach Center for Oral Diease of Zhejiang Province, Key Laboratory of Oral Biomedical Reach of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China
| | - Jicheng Yu
- Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
- Jinhua Institute of Zhejiang University, Jinhua, 321299, China
| | - Zhen Gu
- Key Laboratory of Advanced Drug Delivery Systems of Zhejiang Province, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
- Jinhua Institute of Zhejiang University, Jinhua, 321299, China
- MOE Key Laboratory of Macromolecular Synthesis and Functionalization, Department of Polymer Science, Zhejiang University, Hangzhou, 310027, China
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28
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Momeni Z, Boulé NG, Prado CM, Hinz HA, Yardley JE. The Effect of Starting Blood Glucose Levels on Serum Electrolyte Concentrations during and after Exercise in Type 1 Diabetes. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:2109. [PMID: 36767477 PMCID: PMC9915529 DOI: 10.3390/ijerph20032109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 01/20/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
Fear of hypoglycemia is a major exercise barrier for people with type 1 diabetes (PWT1D). Consequently, although guidelines recommend starting exercise with blood glucose (BG) concentration at 7-10 mmol/L, PWT1D often start higher, potentially affecting hydration and serum electrolyte concentrations. To test this, we examined serum and urine electrolyte concentrations during aerobic exercise (cycling 45 min at 60%VO2peak) in 12 PWT1D (10F/2M, mean ± SEM: age 29 ± 2.3 years, VO2peak 37.9 ± 2.2 mL·kg-1·min-1) with starting BG levels: 8-10 (MOD), and 12-14 (HI) mmol/L. Age, sex, and fitness-matched controls without diabetes (CON) completed one exercise session with BG in the normal physiological range. Serum glucose was significantly higher during exercise and recovery in HI versus MOD (p = 0.0002 and p < 0.0001, respectively) and in MOD versus CON (p < 0.0001). During exercise and recovery, MOD and HI were not significantly different in serum insulin (p = 0.59 and p = 0.63), sodium (p = 0.058 and p = 0.08), potassium (p = 0.17 and p = 0.16), calcium (p = 0.75 and 0.19), and magnesium p = 0.24 and p = 0.09). Our findings suggest that exercise of moderate intensity and duration with higher BG levels may not pose an immediate risk to hydration or serum electrolyte concentrations for PWT1D.
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Affiliation(s)
- Zeinab Momeni
- Augustana Faculty, University of Alberta, 4901-46th Avenue, Camrose, AB T4V 2R3, Canada
- Physical Activity and Diabetes Laboratory, Alberta Diabetes Institute, 112 Street, Edmonton, AB T6G 2T9, Canada
- Women’s and Children’s Health Research Institute, University of Alberta, Edmonton, AB T6G 1C9, Canada
| | - Normand G. Boulé
- Physical Activity and Diabetes Laboratory, Alberta Diabetes Institute, 112 Street, Edmonton, AB T6G 2T9, Canada
- Faculty of Kinesiology, Sport, and Recreation, University of Alberta, 3-100 University Hall, Van Vliet Complex, Edmonton, AB T6G 2H9, Canada
| | - Carla M. Prado
- Women’s and Children’s Health Research Institute, University of Alberta, Edmonton, AB T6G 1C9, Canada
- Human Nutrition Research Unit, Alberta Diabetes Institute, 112 Street, Edmonton, AB T6G 2T9, Canada
- Faculty of Agricultural, Life and Environmental Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Heather A. Hinz
- Physical Activity and Diabetes Laboratory, Alberta Diabetes Institute, 112 Street, Edmonton, AB T6G 2T9, Canada
- Faculty of Kinesiology, Sport, and Recreation, University of Alberta, 3-100 University Hall, Van Vliet Complex, Edmonton, AB T6G 2H9, Canada
| | - Jane E. Yardley
- Augustana Faculty, University of Alberta, 4901-46th Avenue, Camrose, AB T4V 2R3, Canada
- Physical Activity and Diabetes Laboratory, Alberta Diabetes Institute, 112 Street, Edmonton, AB T6G 2T9, Canada
- Women’s and Children’s Health Research Institute, University of Alberta, Edmonton, AB T6G 1C9, Canada
- Faculty of Kinesiology, Sport, and Recreation, University of Alberta, 3-100 University Hall, Van Vliet Complex, Edmonton, AB T6G 2H9, Canada
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29
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Ubl M, Koutny T, Della Cioppa A, De Falco I, Tarantino E, Scafuri U. Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment. SENSORS (BASEL, SWITZERLAND) 2022; 22:9445. [PMID: 36502149 PMCID: PMC9739839 DOI: 10.3390/s22239445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 11/28/2022] [Accepted: 11/29/2022] [Indexed: 06/17/2023]
Abstract
Diabetes is a heterogeneous group of diseases that share a common trait of elevated blood glucose levels. Insulin lowers this level by promoting glucose utilization, thus avoiding short- and long-term organ damage due to the elevated blood glucose level. A patient with diabetes uses an insulin pump to dose insulin. The pump uses a controller to compute and dose the correct amount of insulin to keep blood glucose levels in a safe range. Insulin-pump controller development is an ongoing process aiming at fully closed-loop control. Controllers entering the market must be evaluated for safety. We propose an evaluation method that exploits an FDA-approved diabetic patient simulator. The method evaluates a Cartesian product of individual insulin-pump parameters with a fine degree of granularity. As this is a computationally intensive task, the simulator executes on a distributed cluster. We identify safe and risky combinations of insulin-pump parameter settings by applying the binomial model and decision tree to this product. As a result, we obtain a tool for insulin-pump settings and controller safety assessment. In this paper, we demonstrate the tool with the Low-Glucose Suspend and OpenAPS controllers. For average ± standard deviation, LGS and OpenAPS exhibited 1.7 ± 0.6% and 3.2 ± 1.8% of local extrema (i.e., good insulin-pump settings) out of all the entire Cartesian products, respectively. A continuous region around the best-discovered settings (i.e., the global extremum) of the insulin-pump settings spread across 4.0 ± 1.1% and 4.1 ± 1.3% of the Cartesian products, respectively.
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Affiliation(s)
- Martin Ubl
- Department of Computer Science and Engineering, University of West Bohemia, Technicka 18, 330 01 Pilsen, Czech Republic
| | - Tomas Koutny
- Department of Computer Science and Engineering, New Technologies for Information Society, University of West Bohemia, Technicka 18, 330 01 Pilsen, Czech Republic
| | - Antonio Della Cioppa
- Natural Computation Lab, Department of Information Engineering, Electrical Engineering and Applied Mathematics, University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, Italy
| | - Ivanoe De Falco
- ICAR-National Research Council of Italy, Via P. Castellino, 80131 Naples, Italy
| | - Ernesto Tarantino
- ICAR-National Research Council of Italy, Via P. Castellino, 80131 Naples, Italy
| | - Umberto Scafuri
- ICAR-National Research Council of Italy, Via P. Castellino, 80131 Naples, Italy
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30
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Adolfsson P, Taplin CE, Zaharieva DP, Pemberton J, Davis EA, Riddell MC, McGavock J, Moser O, Szadkowska A, Lopez P, Santiprabhob J, Frattolin E, Griffiths G, DiMeglio LA. ISPAD Clinical Practice Consensus Guidelines 2022: Exercise in children and adolescents with diabetes. Pediatr Diabetes 2022; 23:1341-1372. [PMID: 36537529 PMCID: PMC10107219 DOI: 10.1111/pedi.13452] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/07/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- Peter Adolfsson
- Department of Pediatrics, Kungsbacka Hospital, Kungsbacka, Sweden.,Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Craig E Taplin
- Department of Endocrinology and Diabetes, Perth Children's Hospital, Nedlands, Western Australia, Australia.,Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia.,Centre for Child Health Research, University of Western Australia, Perth, Western Australia, Australia
| | - Dessi P Zaharieva
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, California, USA
| | - John Pemberton
- Department of Endocrinology and Diabetes, Birmingham Women's and Children's Hospital, Birmingham, UK
| | - Elizabeth A Davis
- Department of Endocrinology and Diabetes, Perth Children's Hospital, Nedlands, Western Australia, Australia.,Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia.,Centre for Child Health Research, University of Western Australia, Perth, Western Australia, Australia
| | - Michael C Riddell
- Muscle Health Research Centre, York University, Toronto, Ontario, Canada
| | - Jonathan McGavock
- Faculty of Kinesiology and Recreation Management, University of Manitoba, Winnipeg, Manitoba, Canada.,Diabetes Research Envisioned and Accomplished in Manitoba (DREAM) Theme, Children's Hospital Research Institute of Manitoba, Winnipeg, Manitoba, Canada.,Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, Manitoba, Canada.,Diabetes Action Canada SPOR Network, Toronto, Ontario, Canada
| | - Othmar Moser
- Division Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, Bayreuth, Germany.,Interdisciplinary Metabolic Medicine Trials Unit, Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Agnieszka Szadkowska
- Department of Pediatrics, Diabetology, Endocrinology & Nephrology, Medical University of Lodz, Lodz, Poland
| | - Prudence Lopez
- Department of Paediatrics, John Hunter Children's Hospital, Newcastle, New South Wales, Australia.,University of Newcastle, Newcastle, New South Wales, Australia
| | - Jeerunda Santiprabhob
- Siriraj Diabetes Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.,Division of Endocrinology and Metabolism, Department of Pediatrics, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | | | | | - Linda A DiMeglio
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetology, Indiana University School of Medicine, Riley Hospital for Children, Indianapolis, Indiana, USA
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31
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Rigon FA, Ronsoni MF, Vianna AGD, de Lucca Schiavon L, Hohl A, van de Sande-Lee S. Flash glucose monitoring system in special situations. ARCHIVES OF ENDOCRINOLOGY AND METABOLISM 2022; 66:883-894. [PMID: 35657123 PMCID: PMC10118756 DOI: 10.20945/2359-3997000000479] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 02/04/2022] [Indexed: 02/08/2023]
Abstract
The management of diabetes mellitus (DM) requires maintaining glycemic control, and patients must keep their blood glucose levels close to the normal range to reduce the risk of microvascular complications and cardiovascular events. While glycated hemoglobin (A1C) is currently the primary measure for glucose management and a key marker for long-term complications, it does not provide information on acute glycemic excursions and overall glycemic variability. These limitations may even be higher in some special situations, thereby compromising A1C accuracy, especially when wider glycemic variability is expected and/or when the glycemic goal is more stringent. To attain adequate glycemic control, continuous glucose monitoring (CGM) is more useful than self-monitoring of blood glucose (SMBG), as it is more convenient and provides a greater amount of data. Flash Glucose Monitoring (isCGM /FGM) is a widely accepted option of CGM for measuring interstitial glucose levels in individuals with DM. However, its application under special conditions, such as pregnancy, patients on hemodialysis, patients with cirrhosis, during hospitalization in the intensive care unit and during physical exercise has not yet been fully validated. This review addresses some of these specific situations in which hypoglycemia should be avoided, or in pregnancy, where strict glycemic control is essential, and the application of isCGM/FGM could alleviate the shortcomings associated with poor glucose control or high glycemic variability, thereby contributing to high-quality care.
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Affiliation(s)
- Fernanda Augustini Rigon
- Programa de Pós-graduação em Ciências Médicas, Universidade Federal de Santa Catarina, Florianópolis, SC, Brasil,
| | - Marcelo Fernando Ronsoni
- Departamento de Clínica Médica, Universidade Federal de Santa Catarina, Florianópolis, SC, Brasil
| | - André Gustavo Daher Vianna
- Centro de Diabetes de Curitiba, Departamento de Doenças Endócrinas, Hospital Nossa Senhora das Graças, Curitiba, PR, Brasil
| | | | - Alexandre Hohl
- Departamento de Clínica Médica, Universidade Federal de Santa Catarina, Florianópolis, SC, Brasil
| | - Simone van de Sande-Lee
- Departamento de Clínica Médica, Universidade Federal de Santa Catarina, Florianópolis, SC, Brasil
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32
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Da Prato G, Pasquini S, Rinaldi E, Lucianer T, Donà S, Santi L, Negri C, Bonora E, Moghetti P, Trombetta M. Accuracy of CGM Systems During Continuous and Interval Exercise in Adults with Type 1 Diabetes. J Diabetes Sci Technol 2022; 16:1436-1443. [PMID: 34111989 PMCID: PMC9631517 DOI: 10.1177/19322968211023522] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND continuous glucose monitoring systems (CGMs) play an important role in the management of T1D, but their accuracy may reduce during rapid glucose excursions. The aim of study was to assess the accuracy of recent rt-CGMs available in Italy, in subjects with T1D during 2 sessions of physical activity: moderate continuous (CON) and interval exercise (IE). METHOD we recruited 22 patients with T1D, on CSII associated or integrated with a CGM, to which a second different sensor was applied. Data recorded by CGMs were compared with the corresponding plasma glucose (PG) values, measured every 5 minutes with the glucose analyzer. To assess the accuracy of the CGMs, we evaluated the Sensor Bias (SB), the Mean Absolute Relative Difference (MARD) and the Clarke error grid (CEG). RESULTS a total of 2355 plasma-sensor glucose paired points were collected. Both average plasma and interstitial glucose concentrations did not significantly differ during CON and IE. During CON: 1. PG change at the end of exercise was greater than during IE (P = .034); 2. all sensors overestimated PG more than during IE, as shown by SB (P < .001) and MARD (P < .001) comparisons. Classifying the performance according to the CEG, significant differences were found between the 2 sessions in distribution of points in A and B zones. CONCLUSIONS the exercise affects the accuracy of currently available CGMs, especially during CON, suggesting, in this circumstance, the need to maintain blood glucose in a "prudent" range, above that generally recommended. Further studies are needed to investigate additional types of activities.
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Affiliation(s)
- G. Da Prato
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
| | - S. Pasquini
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
| | - E. Rinaldi
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
| | - T. Lucianer
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
| | - S. Donà
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
| | - L. Santi
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
| | - C. Negri
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
| | - E. Bonora
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
| | - P. Moghetti
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
| | - M. Trombetta
- Department of Medicine, Division of
Endocrinology, Diabetes and Metabolism, University and Hospital of Verona, Verona,
Italy
- M. Trombetta, Department of Medicine,
Section of Endocrinology, Diabetes and Metabolism, University Hospital of
Verona, Piazzale Stefani 1, Verona, 37126, Italy.
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Ong KM, J. Rossitto J, Ray K, A. Dufurrena Q, Blue RS. Blood Glucose Alterations and Continuous Glucose Monitoring in Centrifuge-Simulated Spaceflight. Aerosp Med Hum Perform 2022; 93:688-695. [DOI: 10.3357/amhp.6110.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
INTRODUCTION: Sympathetic stimulation is known to be associated with transient alterations of blood glucose (BG) concentration; spaceflight acceleration may be similarly associated with alterations of BG, potentially posing a risk to diabetic individuals engaging in future spaceflight
activities. Despite prior studies demonstrating diabetic subjects’ tolerance to centrifuge-simulated spaceflight, data are lacking regarding blood glucose response to hypergravity. It remains unclear whether hypergravity or associated physiological response may pose a risk to diabetics.
Continuous glucose monitors (CGM) offer a means of noninvasive glucose monitoring and may be useful in spaceflight and analog environments. Here, we describe the results of continuous glucose monitoring during centrifuge-simulated spaceflight.METHODS: Subjects participated in 1–5
centrifuge-simulated spaceflight profiles (maximum +4.0 Gz, +6.0 Gx, 6.1 G resultant). Data collection included heart rate, blood pressure, electrocardiogram, continuous glucose via CGM, intermittent fingerstick BG, and postrun questionnaires regarding symptoms related
to hypergravity exposure.RESULTS: CGM data were collected from 26 subjects, including 4 diabetics. While diabetic subjects had significantly higher BG compared to nondiabetics, this was not associated with any difference in symptoms or tolerance. Transient hypergravity-associated
CGM glucose alterations did not affect tolerance of the centrifuge experience. CGM data were found to be reliable with occasional exceptions, including four instances of false critical low glucose alarms.DISCUSSION: While further study is necessary to better characterize CGM fidelity
during hypergravity and other spaceflight-related stressors, CGM may be a feasible option for spaceflight and analog settings. As in prior studies, individuals with well-controlled diabetes appear able to tolerate the accelerations anticipated for commercial spaceflight.Ong KM, Rossitto
JJ, Ray K, Dufurrena QA, Blue RS. Blood glucose alterations and continuous glucose monitoring in centrifuge-simulated spaceflight. Aerosp Med Hum Perform. 2022; 93(9):688–695.
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34
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Marks BE, Wolfsdorf JI. Monitoring of paediatric type 1 diabetes. Curr Opin Pediatr 2022; 34:391-399. [PMID: 35836398 DOI: 10.1097/mop.0000000000001136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW This article reviews recent developments in methods used to monitor paediatric type 1 diabetes (T1D), including an examination of the role of glycated haemoglobin (haemoglobin A1c) and its limitations for long-term assessment of glycaemia in individual patients, self-monitoring of blood glucose, continuous glucose monitoring (CGM) systems and ketone monitoring. RECENT FINDINGS Monitoring of glycemia and ketones, when indicated, is a cornerstone of paediatric T1D management and is essential to optimize glycaemic control. Ongoing technological advancements have led to rapid changes and considerable improvement in the methods used to monitor glucose concentrations in people with T1D. As a result of recent innovations that have enhanced accuracy and usability, CGM is now considered the optimal method for monitoring glucose concentrations and should be introduced soon after diagnosis of T1D. SUMMARY Patients/families and healthcare providers must receive comprehensive education and proper training in the use of CGM and interpretation of the vast amounts of data. Future challenges include ensuring equal access to and optimizing clinical use of CGM to further improve T1D care and outcomes.
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Affiliation(s)
- Brynn E Marks
- Children's National Hospital, Division of Endocrinology, Washington, District of Columbia
| | - Joseph I Wolfsdorf
- Boston Children's Hospital, Division of Endocrinology, Boston, Massachusetts, USA
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35
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Daskalaki E, Parkinson A, Brew-Sam N, Hossain MZ, O'Neal D, Nolan CJ, Suominen H. The Potential of Current Noninvasive Wearable Technology for the Monitoring of Physiological Signals in the Management of Type 1 Diabetes: Literature Survey. J Med Internet Res 2022; 24:e28901. [PMID: 35394448 PMCID: PMC9034434 DOI: 10.2196/28901] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 12/06/2021] [Accepted: 12/23/2021] [Indexed: 11/13/2022] Open
Abstract
Background Monitoring glucose and other parameters in persons with type 1 diabetes (T1D) can enhance acute glycemic management and the diagnosis of long-term complications of the disease. For most persons living with T1D, the determination of insulin delivery is based on a single measured parameter—glucose. To date, wearable sensors exist that enable the seamless, noninvasive, and low-cost monitoring of multiple physiological parameters. Objective The objective of this literature survey is to explore whether some of the physiological parameters that can be monitored with noninvasive, wearable sensors may be used to enhance T1D management. Methods A list of physiological parameters, which can be monitored by using wearable sensors available in 2020, was compiled by a thorough review of the devices available in the market. A literature survey was performed using search terms related to T1D combined with the identified physiological parameters. The selected publications were restricted to human studies, which had at least their abstracts available. The PubMed and Scopus databases were interrogated. In total, 77 articles were retained and analyzed based on the following two axes: the reported relations between these parameters and T1D, which were found by comparing persons with T1D and healthy control participants, and the potential areas for T1D enhancement via the further analysis of the found relationships in studies working within T1D cohorts. Results On the basis of our search methodology, 626 articles were returned, and after applying our exclusion criteria, 77 (12.3%) articles were retained. Physiological parameters with potential for monitoring by using noninvasive wearable devices in persons with T1D included those related to cardiac autonomic function, cardiorespiratory control balance and fitness, sudomotor function, and skin temperature. Cardiac autonomic function measures, particularly the indices of heart rate and heart rate variability, have been shown to be valuable in diagnosing and monitoring cardiac autonomic neuropathy and, potentially, predicting and detecting hypoglycemia. All identified physiological parameters were shown to be associated with some aspects of diabetes complications, such as retinopathy, neuropathy, and nephropathy, as well as macrovascular disease, with capacity for early risk prediction. However, although they can be monitored by available wearable sensors, most studies have yet to adopt them, as opposed to using more conventional devices. Conclusions Wearable sensors have the potential to augment T1D sensing with additional, informative biomarkers, which can be monitored noninvasively, seamlessly, and continuously. However, significant challenges associated with measurement accuracy, removal of noise and motion artifacts, and smart decision-making exist. Consequently, research should focus on harvesting the information hidden in the complex data generated by wearable sensors and on developing models and smart decision strategies to optimize the incorporation of these novel inputs into T1D interventions.
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Affiliation(s)
- Elena Daskalaki
- School of Computing, College of Engineering and Computer Science, The Australian National University, Canberra, Australia
| | - Anne Parkinson
- Department of Health Services Research and Policy, Research School of Population Health, College of Health and Medicine, The Australian National University, Canberra, Australia
| | - Nicola Brew-Sam
- Department of Health Services Research and Policy, Research School of Population Health, College of Health and Medicine, The Australian National University, Canberra, Australia
| | - Md Zakir Hossain
- School of Computing, College of Engineering and Computer Science, The Australian National University, Canberra, Australia.,School of Biology, College of Science, The Australian National University, Canberra, Australia.,Bioprediction Activity, Commonwealth Industrial and Scientific Research Organisation, Canberra, Australia
| | - David O'Neal
- Department of Medicine, University of Melbourne, Melbourne, Australia.,Department of Endocrinology and Diabetes, St Vincent's Hospital Melbourne, Melbourne, Australia
| | - Christopher J Nolan
- Australian National University Medical School and John Curtin School of Medical Research, College of Health and Medicine, The Autralian National University, Canberra, Australia.,Department of Diabetes and Endocrinology, The Canberra Hospital, Canberra, Australia
| | - Hanna Suominen
- School of Computing, College of Engineering and Computer Science, The Australian National University, Canberra, Australia.,Data61, Commonwealth Industrial and Scientific Research Organisation, Canberra, Australia.,Department of Computing, University of Turku, Turku, Finland
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36
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Hall RM, Dyhrberg S, McTavish A, McTavish L, Corley B, Krebs JD. Where can you wear your Libre? Using the FreeStyle Libre continuous glucose monitor on alternative sites. Diabetes Obes Metab 2022; 24:675-683. [PMID: 34931427 DOI: 10.1111/dom.14630] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 12/03/2021] [Accepted: 12/18/2021] [Indexed: 11/29/2022]
Abstract
AIM To investigate the accuracy and acceptability of the FreeStyle Libre Flash continuous glucose monitoring system (FSL-CGM) at alternative sites during free living and under experimental conditions. MATERIALS AND METHODS Participants with type 1 diabetes were provided with three FSL-CGM sensors applied to the upper arm, the lower back, and the anterior chest. On day 2 or 3, FSL-CGM sensor glucose was compared with venous glucose following a standard meal, during and after an exercise test, and after skin cooling. Participants completed 14-day use of the sensors with concomitant sensor scanning at all sites and capillary glucose tests. The primary outcome was accuracy between sensor sites of 14-day mean glucose. Clarke's error grids, precision absolute relative deviation, and mean absolute relative deviation were calculated. RESULTS In the 20 participants, compared with the arm sensor, the accuracy of the back sensor and the chest sensor was 97.9% and 98%, respectively. Under experimental conditions, the arm sensor was more accurate than that of the back and chest. All the sensors recorded higher glucose concentration than venous samples during exercise. The arm and chest sites were most preferred, with the greatest sensor failures from the back. CONCLUSIONS The FSL-CGM is clinically accurate when the sensors are applied to alternate chest or back sites. Greater variability occurs during rapid changes in glucose concentration with all sensor sites compared with venous glucose. Understanding these variabilities allows appropriate use of an economically viable continuous glucose monitor.
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Affiliation(s)
- Rosemary M Hall
- Endocrine, Diabetes and Research Centre, Wellington Regional Hospital, Wellington, New Zealand
- Department of Medicine, University of Otago, Wellington, New Zealand
| | | | | | - Lindsay McTavish
- Endocrine, Diabetes and Research Centre, Wellington Regional Hospital, Wellington, New Zealand
| | - Brian Corley
- Endocrine, Diabetes and Research Centre, Wellington Regional Hospital, Wellington, New Zealand
| | - Jeremy D Krebs
- Endocrine, Diabetes and Research Centre, Wellington Regional Hospital, Wellington, New Zealand
- Department of Medicine, University of Otago, Wellington, New Zealand
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37
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Riddell MC, Shakeri D, Scott SN. A Brief Review on the Evolution of Technology in Exercise and Sport in Type 1 Diabetes: Past, Present, and Future. Diabetes Technol Ther 2022; 24:289-298. [PMID: 34809493 DOI: 10.1089/dia.2021.0427] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
One hundred years ago, insulin was first used to successfully lower blood glucose levels in young people living with what was then called juvenile diabetes. While insulin was not a cure for diabetes, it allowed individuals to resume a near normal life and have some freedom to eat more liberally and gain the strength they needed to live a more active lifestyle. Since then, a number of therapeutic and technical advances have arisen to further improve the health and wellbeing of individuals living with type 1 diabetes, allowing many to participate in sport at the local, regional, national or international level of competition. This review and commentary highlights some of the key advances in diabetes management in sport over the last 100 years since the discovery of insulin.
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Affiliation(s)
- Michael C Riddell
- School of Kinesiology and Health Science, Muscle Health Research Centre, York University, Toronto, Canada
| | - Dorsa Shakeri
- School of Kinesiology and Health Science, Muscle Health Research Centre, York University, Toronto, Canada
| | - Sam N Scott
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Bern University Hospital, University of Bern, Bern, Switzerland
- Team Novo Nordisk Professional Cycling Team, Atlanta, Georgia, USA
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38
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MXene nanoflakes decorating ZnO tetrapods for enhanced performance of skin-attachable stretchable enzymatic electrochemical glucose sensor. Biosens Bioelectron 2022; 207:114141. [PMID: 35298947 DOI: 10.1016/j.bios.2022.114141] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/24/2022] [Accepted: 02/27/2022] [Indexed: 12/15/2022]
Abstract
Continuous painless glucose monitoring is the greatest desire of more than 422 million diabetics worldwide. Therefore, new non-invasive and convenient approaches to glucose monitoring are more in demand than other tests for microanalytical diagnostic tools. Besides, blood glucose detection can be replaced by continuous glucose monitoring of other human biological fluids (e.g. sweat) collected non-invasively. In this study, a skin-attachable and stretchable electrochemical enzymatic sensor based on ZnO tetrapods (TPs) and a new class of 2D materials - transition metal carbides, known as MXene, was developed and their electroanalytical behavior was tailored for continuous detection glucose in sweat. The high specific area of ZnO TPs and superior electrical conductivity of MXene (Ti3C2Tx) nanoflakes enabled to produce enzymatic electrochemical glucose biosensor with enhanced sensitivity in sweat sample (29 μA mM-1 cm-2), low limit of detection (LOD ≈ 17 μM), broad linear detection range (LDR = 0.05-0.7 mM) that satisfices glucose detection application in human sweat, and advanced mechanical stability (up to 30% stretching) of the template. The developed skin-attachable stretchable electrochemical electrodes allowed to monitor the level of glucose in sweat while sugar uptake and during physical activity. Continuous in vivo monitoring of glucose in sweat obtained during 60 min correlated well with data collected by a conventional amperometric blood glucometer in vitro mode. Our findings demonstrate the high potential of developed ZnO/MXene skin-attachable stretchable sensors for biomedical applications on a daily basis.
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39
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Marks BE, Williams KM, Sherwood JS, Putman MS. Practical aspects of diabetes technology use: Continuous glucose monitors, insulin pumps, and automated insulin delivery systems. J Clin Transl Endocrinol 2022; 27:100282. [PMID: 34917483 PMCID: PMC8666668 DOI: 10.1016/j.jcte.2021.100282] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 11/01/2021] [Accepted: 11/27/2021] [Indexed: 02/06/2023] Open
Abstract
There have been tremendous advances in diabetes technology in the last decade. Continuous glucose monitors (CGM), insulin pumps, and automated insulin delivery (AID) systems aim to improve glycemic control while simultaneously decreasing the burden of diabetes management. Although diabetes technologies have been shown to decrease both hypoglycemia and hyperglycemia and to improve health-related quality of life in individuals with type 1 diabetes, the impact of these devices in individuals with cystic fibrosis-related diabetes (CFRD) is less clear. There are unique aspects of CFRD, including the different underlying pathophysiology and unique lived health care experience and comorbidities, that likely affect the use, efficacy, and uptake of diabetes technology in this population. Small studies suggest that CGM is accurate and may be helpful in guiding insulin therapy for individuals with CFRD. Insulin pump use has been linked to improvements in lean body mass and hemoglobin A1c among adults with CFRD. A recent pilot study highlighted the promise of AID systems in this population. This article provides an overview of practical aspects of diabetes technology use and device limitations that clinicians must be aware of in caring for individuals with CF and CFRD. Cost and limited insurance coverage remain significant barriers to wider implementation of diabetes technology use among patients with CFRD. Future studies exploring strategies to improve patient and CF provider education about these devices and studies showing the effectiveness of these technologies on health and patient-reported outcomes may lead to improved insurance coverage and increased rates of uptake and sustained use of these technologies in the CFRD community.
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Affiliation(s)
- Brynn E. Marks
- Division of Endocrinology and Diabetes, Children’s National Hospital, 111 Michigan Ave, NW, Washington, DC 20010, USA
| | - Kristen M. Williams
- Division of Pediatric Endocrinology, Diabetes, and Metabolism, Columbia University Irving Medical Center, 1150 St Nicholas Avenue, New York, NY 10032, United States
| | - Jordan S. Sherwood
- Diabetes Research Center, Division of Pediatric Endocrinology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, United States
| | - Melissa S. Putman
- Division of Endocrinology, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Diabetes Research Center, Division of Endocrinology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, United States
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40
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Zaharieva DP, Riddell MC. Advances in Exercise and Nutrition as Therapy in Diabetes. Diabetes Technol Ther 2022; 24:S129-S142. [PMID: 35475701 DOI: 10.1089/dia.2022.2508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Dessi P Zaharieva
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Michael C Riddell
- School of Kinesiology and Health Science, Faculty of Health, Muscle Health Research Centre, York University, Toronto, Ontario, Canada
- LMC Diabetes & Endocrinology, Toronto, Ontario, Canada
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41
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Moser O, Sternad C, Eckstein ML, Szadkowska A, Michalak A, Mader JK, Ziko H, Elsayed H, Aberer F, Sola-Gazagnes A, Larger E, Fadini GP, Bonora BM, Bruttomesso D, Boscari F, Freckmann G, Pleus S, Christiansen SC, Sourij H. Performance of intermittently scanned continuous glucose monitoring systems in people with type 1 diabetes: A pooled analysis. Diabetes Obes Metab 2022; 24:522-529. [PMID: 34866293 DOI: 10.1111/dom.14609] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 11/10/2021] [Accepted: 12/01/2021] [Indexed: 12/30/2022]
Abstract
AIMS To conduct a pooled analysis to assess the performance of intermittently scanned continuous glucose monitoring (isCGM) in association with the rate of change in sensor glucose in a cohort of children, adolescents, and adults with type 1 diabetes. MATERIAL AND METHODS In this pooled analysis, isCGM system accuracy was assessed depending on the rate of change in sensor glucose. Clinical studies that have been investigating isCGM accuracy against blood glucose, accompanied with collection time points were included in this analysis. isCGM performance was assessed by means of median absolute relative difference (MedARD), Parkes error grid (PEG) and Bland-Altman plot analyses. RESULTS Twelve studies comprising 311 participants were included, with a total of 15 837 paired measurements. The overall MedARD (interquartile range) was 12.7% (5.9-23.5) and MedARD differed significantly based on the rate of change in glucose (P < 0.001). An absolute difference of -22 mg/dL (-1.2 mmol/L) (95% limits of agreement [LoA] 60 mg/dL (3.3 mmol/L), -103 mg/dL (-5.7 mmol/L)) was found when glucose was rapidly increasing (isCGM glucose minus reference blood glucose), while a -32 mg/dL (1.8 mmol/L) (95% LoA 116 mg/dL (6.4 mmol/L), -51 mg/dL (-2.8 mmol/L)) absolute difference was observed in periods of rapidly decreasing glucose. CONCLUSIONS The performance of isCGM was good when compared to reference blood glucose measurements. The rate of change in glucose for both increasing and decreasing glucose levels diminished isCGM performance, showing lower accuracy during high rates of glucose change.
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Affiliation(s)
- Othmar Moser
- Division of Exercise Physiology and Metabolism, Institute of Sport Science, University of Bayreuth, Bayreuth, Germany
- Interdisciplinary Metabolic Medicine Trials Unit, Medical University of Graz, Graz
| | - Christoph Sternad
- Interdisciplinary Metabolic Medicine Trials Unit, Medical University of Graz, Graz
| | - Max L Eckstein
- Division of Exercise Physiology and Metabolism, Institute of Sport Science, University of Bayreuth, Bayreuth, Germany
| | - Agnieszka Szadkowska
- Department of Pediatrics, Diabetology, Endocrinology & Nephrology, Medical University of Lodz, Łódź, Poland
| | - Arkadiusz Michalak
- Department of Biostatistics and Translational Medicine, Medical University of Lodz, Łódź, Poland
| | - Julia K Mader
- Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria
| | - Haris Ziko
- Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria
| | - Hesham Elsayed
- Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria
| | - Felix Aberer
- Division of Exercise Physiology and Metabolism, Institute of Sport Science, University of Bayreuth, Bayreuth, Germany
- Interdisciplinary Metabolic Medicine Trials Unit, Medical University of Graz, Graz
| | - Agnes Sola-Gazagnes
- Department of Diabetology, Cochin Hospital, APHP Centre-Université de Paris, Paris, France
| | - Etienne Larger
- Department of Diabetology, Cochin Hospital, APHP Centre-Université de Paris, Paris, France
- Université de Paris, Paris, France
| | | | | | | | | | - Guido Freckmann
- 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
| | - Sverre C Christiansen
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, St. Olav's University Hospital, Trondheim, Norway
| | - Harald Sourij
- Interdisciplinary Metabolic Medicine Trials Unit, Medical University of Graz, Graz
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Pujalte G, Alhumaidi HM, Ligaray KPL, Vomer RP, Israni K, Abadin AA, Meek SE. Considerations in the Care of Athletes With Type 1 Diabetes Mellitus. Cureus 2022; 14:e22447. [PMID: 35345701 PMCID: PMC8942069 DOI: 10.7759/cureus.22447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/21/2022] [Indexed: 11/12/2022] Open
Abstract
Type 1 diabetes mellitus is an autoimmune disease caused by affected individuals’ autoimmune response to their own pancreatic beta-cell. It affects millions of people worldwide. Exercise has numerous health and social benefits for patients with type 1 diabetes mellitus; however, careful management of blood glucose is crucial to minimize the risk of hypoglycemia and hyperglycemia. Anaerobic and aerobic exercises cause different glycemic responses during and after exercise, each of which will affect athletes’ ability to reach their target blood glucose ranges. The optimization of the patient’s macronutrient consumption, especially carbohydrates, the dosage of basal and short-acting insulin, and the frequent monitoring of blood glucose, will enable athletes to perform at peak levels while reducing their risk of dysglycemia. Despite best efforts, hypoglycemia can occur. Recognition of symptoms and rapid treatment with either fast-acting carbohydrates or glucagon is important. Continuous glucose monitoring devices have become more widely used in preventing hypoglycemia.
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Shang T, Zhang JY, Thomas A, Arnold MA, Vetter BN, Heinemann L, Klonoff DC. Products for Monitoring Glucose Levels in the Human Body With Noninvasive Optical, Noninvasive Fluid Sampling, or Minimally Invasive Technologies. J Diabetes Sci Technol 2022; 16:168-214. [PMID: 34120487 PMCID: PMC8721558 DOI: 10.1177/19322968211007212] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [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 Conventional home blood glucose measurements require a sample of blood that is obtained by puncturing the skin at the fingertip. To avoid the pain associated with this procedure, there is high demand for medical products that allow glucose monitoring without blood sampling. In this review article, all such products are presented. METHODS In order to identify such products, four different sources were used: (1) PubMed, (2) Google Patents, (3) Diabetes Technology Meeting Startup Showcase participants, and (4) experts in the field of glucose monitoring. The information obtained were filtered by using two inclusion criteria: (1) regulatory clearance, and/or (2) significant coverage in Google News starting in the year 2016, unless the article indicated that the product had been discontinued. The identified bloodless monitoring products were classified into three categories: (1) noninvasive optical, (2) noninvasive fluid sampling, and (3) minimally invasive devices. RESULTS In total, 28 noninvasive optical, 6 noninvasive fluid sampling, and 31 minimally invasive glucose monitoring products were identified. Subsequently, these products were characterized according to their regulatory, technological, and consumer features. Products with regulatory clearance are described in greater detail according to their advantages and disadvantages, and with design images. CONCLUSIONS Based on favorable technological features, consumer features, and other advantages, several bloodless products are commercially available and promise to enhance diabetes management. Paths for future products are discussed with an emphasis on understanding existing barriers related to both technical and non-technical issues.
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Affiliation(s)
- Trisha Shang
- Diabetes Technology Society, Burlingame, California, USA
| | | | - Andreas Thomas
- AGDT (Working group of Diabetes Technology), Germany, Ulm, Germany
| | - Mark A. Arnold
- University of Iowa, Department of Chemistry, Iowa City, Iowa, USA
| | | | | | - David C. Klonoff
- Mills-Peninsula Medical Center, San Mateo, California, USA
- David C. Klonoff, MD, FACP, FRCP (Edin), Fellow AIMBE, Mills-Peninsula Medical Center, 100 South San Mateo Drive, Room 5147, San Mateo, California 94401, USA.
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44
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Biester T, Tauschmann M, Chobot A, Kordonouri O, Danne T, Kapellen T, Dovc K. The automated pancreas: A review of technologies and clinical practice. Diabetes Obes Metab 2022; 24 Suppl 1:43-57. [PMID: 34658126 DOI: 10.1111/dom.14576] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 10/07/2021] [Accepted: 10/07/2021] [Indexed: 12/12/2022]
Abstract
Insulin pumps and glucose sensors are effective in improving diabetes therapy and reducing acute complications. The combination of both devices using an algorithm-driven interoperable controller makes automated insulin delivery (AID) systems possible. Many AID systems have been tested in clinical trials and have proven safety and effectiveness. However, currently, none of these systems are available for routine use in children younger than 6 years in Europe. For continued use, both users and prescribers must have sound knowledge of the features of the individual AID systems. Presently, all systems require various user interactions (e.g. meal announcements) because fully automated systems are not yet developed. Open-source systems are non-regulated variants to circumvent existing regulatory conditions. There are risks here for both users and prescribers. To evaluate AID therapy, the metric data of the glucose sensors, 'time in target range' and 'glucose management index', are novel recognized and suitable parameters allowing a consultation based on real glucose and insulin pump download data from the daily life of people with diabetes. Read out via cloud-based software or automatic download of such individual treatment data provides the ideal technical basis for shared decision-making through telemedicine, which must be further evaluated for general use.
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Affiliation(s)
- Torben Biester
- AUF DER BULT, Diabetes Center for Children and Adolescents, Hannover, Germany
| | - Martin Tauschmann
- Department of Pediatric and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Agata Chobot
- Department of Pediatrics, Institute of Medical Sciences, University of Opole, Opole, Poland
| | - Olga Kordonouri
- AUF DER BULT, Diabetes Center for Children and Adolescents, Hannover, Germany
| | - Thomas Danne
- AUF DER BULT, Diabetes Center for Children and Adolescents, Hannover, Germany
| | - Thomas Kapellen
- Department of Pediatrics, MEDIAN Clinic for Children 'Am Nicolausholz' Bad Kösen, Naumburg, Germany
| | - Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children's Hospital, Ljubljana, Slovenia and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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Rilstone S, Spurway P, Oliver N, Hill NE. Nutritional support for a person with type 1 diabetes undertaking endurance swimming. Front Endocrinol (Lausanne) 2022; 13:1038294. [PMID: 36425473 PMCID: PMC9679002 DOI: 10.3389/fendo.2022.1038294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 10/17/2022] [Indexed: 11/11/2022] Open
Abstract
Long distance and open water swimming have increased in popularity over recent years. Swimming a long distance in lakes, rivers and the sea present numerous challenges, including cold water exposure and maintaining adequate nutritional intake to fuel exercising muscles. Guidelines exist outlining issues to consider and potential solutions to overcome the difficulties in feeding athletes. Exercising with type 1 diabetes adds further complexity, mostly around matching insulin to the recommended high carbohydrate intake, but also because of the way in which higher circulating insulin levels affect glucose utilisation and fat oxidation. This paper describes the nutritional considerations for people with type 1 diabetes intending to undertake long distance open water events, and insulin management suggestions to trial alongside. In addition, we include personal testimony from a swimmer with type 1 diabetes describing the challenges and considerations he faced when undertaking marathon swimming.
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Affiliation(s)
- Siân Rilstone
- Department of Nutrition & Dietetics, Imperial College Healthcare National Health Service (NHS) Trust, London, United Kingdom
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
- *Correspondence: Siân Rilstone,
| | | | - Nick Oliver
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - Neil E. Hill
- Department of Endocrinology & Diabetes, Imperial College Healthcare NHS Trust, London, United Kingdom
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Elbarbary N, Moser O, Al yaarubi S, Alsaffar H, Al Shaikh A, Ajjan RA, Deeb A. Use of continuous glucose monitoring trend arrows in the younger population with type 1 diabetes. Diab Vasc Dis Res 2021; 18:14791641211062155. [PMID: 34898300 PMCID: PMC8671682 DOI: 10.1177/14791641211062155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Early control of glycaemia is key to reduce vascular complications in individuals with Type 1 diabetes. Therefore, encouraging children and adolescents with T1DM to take responsibility for controlling glucose levels is an important yet a challenging task. The rapid expansion of continuous glucose monitoring (CGM) systems has allowed for more comprehensive analysis of glycaemia in T1D. Moreover, CGM devices have the ability to calculate rate of change in glucose levels and display the information as trend arrows. In turn, this can help to take evasive actions to return glucose levels to near physiological glycaemia, which can be highly motivating for young people with T1DM. In the absence of standardised, evidence-based guidance, this consensus document, generated by experts from the Arab Society of Paediatric Endocrinology and Diabetes and international advisors, summarises recent literature on the use of trend arrows in young people with T1DM. The use of trend arrows in different CGM systems is reviewed and their clinical significance is highlighted. Adjusting insulin doses according to trend arrows is discussed while also addressing special situations, such as exercise, fasting, nocturnal hypoglycaemia and menstruation. Adequate understanding of trend arrows should facilitate optimisation of glycaemic control in the T1D population.
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Affiliation(s)
- Nancy Elbarbary
- Diabetes Unit, Department of Pediatrics, Faculty of Medicine, Ain Shams University, Cairo, Egypt
- Nancy Elbarbary, Professor of Pediatrics, Department of Pediatrics, Diabetes Unit, Faculty of Medicine, Ain Shams University, 25 Ahmed Fuad St. Saint Fatima, Heliopolis, Cairo 11361, Egypt.
| | - Othmar Moser
- Division Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, Bayreuth, Germany
- Trials Unit for Interdisciplinary Metabolic Medicine, Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Saif Al yaarubi
- Pediatric Endocrine Department, Sultan Qaboos University Hospital, College of Medicine, Seeb, Oman
| | - Hussain Alsaffar
- Paediatric Endocrine and Diabetics Unit, Department of Child Health, Sultan Qaboos University Hospital, Muscat, Oman
| | - Adnan Al Shaikh
- Pediatric Department, King Abdulaziz Medical City, King Saud Bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Jeddah, Saudi Arabia
| | - Ramzi A Ajjan
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Asma Deeb
- Paediatric Endocrinology Department, Sheikh Shakhbout Medical City and Khalifa University Abu Dhabi, Abu Dhabi, UAE
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Physical Activity, Dietary Patterns, and Glycemic Management in Active Individuals with Type 1 Diabetes: An Online Survey. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18179332. [PMID: 34501920 PMCID: PMC8431360 DOI: 10.3390/ijerph18179332] [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: 06/11/2021] [Revised: 08/18/2021] [Accepted: 08/31/2021] [Indexed: 12/19/2022]
Abstract
Individuals with type 1 diabetes (T1D) are able to balance their blood glucose levels while engaging in a wide variety of physical activities and sports. However, insulin use forces them to contend with many daily training and performance challenges involved with fine-tuning medication dosing, physical activity levels, and dietary patterns to optimize their participation and performance. The aim of this study was to ascertain which variables related to the diabetes management of physically active individuals with T1D have the greatest impact on overall blood glucose levels (reported as A1C) in a real-world setting. A total of 220 individuals with T1D completed an online survey to self-report information about their glycemic management, physical activity patterns, carbohydrate and dietary intake, use of diabetes technologies, and other variables that impact diabetes management and health. In analyzing many variables affecting glycemic management, the primary significant finding was that A1C values in lower, recommended ranges (<7%) were significantly predicted by a very-low carbohydrate intake dietary pattern, whereas the use of continuous glucose monitoring (CGM) devices had the greatest predictive ability when A1C was above recommended (≥7%). Various aspects of physical activity participation (including type, weekly time, frequency, and intensity) were not significantly associated with A1C for participants in this survey. In conclusion, when individuals with T1D are already physically active, dietary changes and more frequent monitoring of glucose may be most capable of further enhancing glycemic management.
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Mahmoudi Z, Del Favero S, Jacob P, Choudhary P. Toward an Optimal Definition of Hypoglycemia with Continuous Glucose Monitoring. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 209:106303. [PMID: 34380077 DOI: 10.1016/j.cmpb.2021.106303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 07/17/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND OBJECTIVE As continuous glucose monitoring (CGM) becomes common in research and clinical practice, there is a need to understand how CGM-based hypoglycemia relates to hypoglycemia episodes defined conventionally as patient reported hypoglycemia (PRH). Data show that CGM identify many episodes of low interstitial glucose (LIG) that are not experienced by patients, and so the aim of this study is to use different PRH simulations to optimize CGM parameters of threshold (h) and duration (d) to provide the best PRH detection performance. METHODS The algorithm uses particle Markov chain Monte Carlo optimization to identify the optimal h and d which maximize an objective function for detecting PRH. We tested our algorithm by creating three different cases of PRH simulations. RESULTS We added three types of simulated PRH events to 10 weeks of anonymized CGM data from 96 type 1 diabetes people to see if the algorithm can detect the optimal parameters set out in the simulations. In simulation 1, we changed the locations of PRHs with respect to LIG episodes in the CGM signal to simulate random optimal LIG parameters for every individual. In simulation 2, the PRHs are CGM glucose <3.9 mmol/L followed by at least 20 min of rise > 0.11 mmol/L/min. Simulation 3 is like simulation 2 but with glucose threshold of 3.0 mmol/L. The median [interquartile range] of deviation between the optimized (found by the algorithm) and the optimal (known) h and d are -0.07% [-0.4, 1.9] and -1.3% [-5.9, 6.8], respectively across the subjects for simulation 1. The mean [min max] of the optimized LIG parameters are h = 3.8 [3.7, 3.8] mmol/L and d = 12 [10, 14] min for simulation 2 and they are h = 3.0 [2.9, 3] mmol/L and d = 10 [8, 14] min for simulation 3 across a 10-fold cross validation. CONCLUSIONS This work demonstrates the feasibility of the algorithm to find the best-fit definition of CGM-based hypoglycemia for PRH detection. In a prospective clinical study collecting CGM and PRH, the current algorithm will be used to optimize the definition of hypoglycemia with respect to PRH with the ambition of using the resulted definition as a surrogate for PRH in clinical practice.
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Affiliation(s)
- Zeinab Mahmoudi
- Department of Diabetes, School of Life Course Sciences, King's College London, UK; DTx, Scientific Modelling, Novo Nordisk A/S, Denmark
| | - Simone Del Favero
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Peter Jacob
- Department of Diabetes, School of Life Course Sciences, King's College London, UK
| | - Pratik Choudhary
- Department of Diabetes, School of Life Course Sciences, King's College London, UK; Department of Diabetes, University of Leicester, UK.
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Ando M, Tsuchiya M, Itai S, Murayama T, Kurashina Y, Heo YJ, Onoe H. Janus Hydrogel Microbeads for Glucose Sensing with pH Calibration. SENSORS (BASEL, SWITZERLAND) 2021; 21:4829. [PMID: 34300568 PMCID: PMC8309740 DOI: 10.3390/s21144829] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/04/2021] [Accepted: 07/05/2021] [Indexed: 11/17/2022]
Abstract
We present fluorescent Janus hydrogel microbeads for continuous glucose sensing with pH calibration. The Janus hydrogel microbeads, that consist of fluorescent glucose and pH sensors, were fabricated with a UV-assisted centrifugal microfluidic device. The microbead can calibrate the pH values of its surroundings and enables accurate measurements of glucose within various pH conditions. As a proof of concept, we succeeded in obtaining the accurate value of glucose concentration in a body-fluid-like sample solution. We believe that our fluorescent microbeads, with pH calibration capability, could be applied to fully implantable sensors for continuous glucose monitoring.
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Affiliation(s)
- Maru Ando
- Westminster School, London SW1P 3PB, UK;
| | - Mio Tsuchiya
- Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Kanagawa 223-8522, Japan; (M.T.); (S.I.); (T.M.); (Y.K.)
| | - Shun Itai
- Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Kanagawa 223-8522, Japan; (M.T.); (S.I.); (T.M.); (Y.K.)
| | - Tomomi Murayama
- Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Kanagawa 223-8522, Japan; (M.T.); (S.I.); (T.M.); (Y.K.)
| | - Yuta Kurashina
- Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Kanagawa 223-8522, Japan; (M.T.); (S.I.); (T.M.); (Y.K.)
- Department of Materials Science and Engineering, School of Materials and Chemical Technology, Tokyo Institute of Technology, Yokohama 226-8503, Japan
| | - Yun Jung Heo
- Department of Mechanical Engineering, Collage of Engineering, Kyung Hee University, Yongin 17104, Korea;
- Integrated Education Institute for Frontier Science & Technology (BK21 Four), Kyung Hee University, Yongin 17104, Korea
| | - Hiroaki Onoe
- Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, Kanagawa 223-8522, Japan; (M.T.); (S.I.); (T.M.); (Y.K.)
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Grunberger G, Sherr J, Allende M, Blevins T, Bode B, Handelsman Y, Hellman R, Lajara R, Roberts VL, Rodbard D, Stec C, Unger J. American Association of Clinical Endocrinology Clinical Practice Guideline: The Use of Advanced Technology in the Management of Persons With Diabetes Mellitus. Endocr Pract 2021; 27:505-537. [PMID: 34116789 DOI: 10.1016/j.eprac.2021.04.008] [Citation(s) in RCA: 126] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 04/16/2021] [Accepted: 04/19/2021] [Indexed: 02/08/2023]
Abstract
OBJECTIVE To provide evidence-based recommendations regarding the use of advanced technology in the management of persons with diabetes mellitus to clinicians, diabetes-care teams, health care professionals, and other stakeholders. METHODS The American Association of Clinical Endocrinology (AACE) conducted literature searches for relevant articles published from 2012 to 2021. A task force of medical experts developed evidence-based guideline recommendations based on a review of clinical evidence, expertise, and informal consensus, according to established AACE protocol for guideline development. MAIN OUTCOME MEASURES Primary outcomes of interest included hemoglobin A1C, rates and severity of hypoglycemia, time in range, time above range, and time below range. RESULTS This guideline includes 37 evidence-based clinical practice recommendations for advanced diabetes technology and contains 357 citations that inform the evidence base. RECOMMENDATIONS Evidence-based recommendations were developed regarding the efficacy and safety of devices for the management of persons with diabetes mellitus, metrics used to aide with the assessment of advanced diabetes technology, and standards for the implementation of this technology. CONCLUSIONS Advanced diabetes technology can assist persons with diabetes to safely and effectively achieve glycemic targets, improve quality of life, add greater convenience, potentially reduce burden of care, and offer a personalized approach to self-management. Furthermore, diabetes technology can improve the efficiency and effectiveness of clinical decision-making. Successful integration of these technologies into care requires knowledge about the functionality of devices in this rapidly changing field. This information will allow health care professionals to provide necessary education and training to persons accessing these treatments and have the required expertise to interpret data and make appropriate treatment adjustments.
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Affiliation(s)
| | - Jennifer Sherr
- Yale University School of Medicine, New Haven, Connecticut
| | - Myriam Allende
- University of Puerto Rico School of Medicine, San Juan, Puerto Rico
| | | | - Bruce Bode
- Atlanta Diabetes Associates, Atlanta, Georgia
| | | | - Richard Hellman
- University of Missouri-Kansas City School of Medicine, Kansas City, Missouri
| | | | | | - David Rodbard
- Biomedical Informatics Consultants, LLC, Potomac, Maryland
| | - Carla Stec
- American Association of Clinical Endocrinology, Jacksonville, Florida
| | - Jeff Unger
- Unger Primary Care Concierge Medical Group, Rancho Cucamonga, California
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