Lag Time Remains with Newer Real-Time Continuous Glucose Monitoring Technology During Aerobic Exercise in Adults Living with Type 1 Diabetes

Metabolically healthy obese vs. Metabolic syndrome - The crosslink between nutritional exposure to bisphenols and physical exercise

Obesity has become a worldwide pandemic as well as a major contributing factor to the increasing rate of type 2 diabetes (T2D). However, there is an intriguing variance demonstrated by a subset of obesity defined as metabolically healthy obesity (MHO). MHO individuals are less prone to develop obesity-related metabolic complications, such as metabolic syndrome (MetS) and further T2D. The exact reason why an MHO person does not present the cluster of risk factors associated with insulin resistance is unknown due to the challenge to mimic MHO in experimental settings. However, MHO individuals present lower sedentary behaviors in comparison to individuals with MetS, which might indicate that an adaptation to skeletal muscle, such as increased insulin sensitivity and glucose transporter (GLUT4), could play a major role in their healthy characteristics. The hypothesis invoked in this paper is that lower exposure to bisphenol together with increased levels of physical exercise underlie the physiological aspects behind MHO characteristics. Evidence suggests that exposure to "obseogens," such as bisphenol A (BPA), appears to impair insulin secretion and insulin response in cells containing GLUT4. Epidemiological studies have associated higher levels of BPA, as well as bisphenol S and F, in children with a risk for MetS development. Therefore, the combination between low bisphenol exposure and increased physical exercise may not necessarily affect body weight, but it could modify several metabolic pathways inhibiting insulin resistance, which characterize the heathy status of the MHO. If confirmed, this hypothesis could lead to therapeutic approaches to reverse MetS and inhibit T2D onset.

Diabetes education in pediatrics: How to survive diabetes

Diabetes mellitus is the most common abnormal carbohydrate metabolism disorder affecting millions of people worldwide. It is characterized by hyperglycemia as a result of ß-cell destruction or dysfunction by both genetic and environmental factors. Over time chronic hyperglycemia leads to microvascular (i.e., retinopathy, nephropathy and neuropathy) and macrovascular (i.e., ischemic heart disease, peripheral vascular disease, and cerebrovascular disease) complications of diabetes. Diabetes complication trials showed the importance of achieving near-normal glycemic control to prevent and/or reduce diabetes-related morbidity and mortality. There is a staggering rate of increased incidence of diabetes in youth, raising concerns for future generations' health, quality of life and its enormous economic burden. Despite advancements in the technology, diabetes management remains cumbersome. Training individuals with diabetes to gain life-long survival skills requires a comprehensive and ongoing diabetes education by a multidisciplinary team. Diabetes education and training start at the time of diagnosis of diabetes and should be continuous throughout the course of disease. The goal is to empower the individuals and families to gain diabetes self-management skills. Diabetes education must be individualized depending on the individual's age, education, family dynamics, and support. In this article, we review the history of diabetes, etiopathogenesis and clinical presentation of both type 1 and type 2 diabetes in children as well as adolescents. We then focus on diabetes management with education methods and materials.

Individualizing Time-in-Range Goals in Management of Diabetes Mellitus and Role of Insulin: Clinical Insights From a Multinational Panel

Diabetes mellitus is a global health concern associated with significant morbidity and mortality. Inadequate control of diabetes leads to chronic complications and higher mortality rates, which emphasizes the importance of achieving glycemic targets. Although glycated hemoglobin (HbA_1c) is the gold standard for measuring glycemic control, it has several limitations. Therefore, in recent years, along with the emergence of continuous glucose monitoring (CGM) technology, glycemic control modalities have moved beyond HbA_1c. They encompass modern glucometrics, such as glycemic variability (GV) and time-in-range (TIR). The key advantage of these newer metrics over HbA_1c is that they allow personalized diabetes management with person-centric glycemic control. Basal insulin analogues, especially second-generation basal insulins with properties such as longer duration of action and low risk of hypoglycemia, have demonstrated clinical benefits by reducing GV and improving TIR. Therefore, for more effective and accurate diabetes management, the development of an integrated approach with second-generation basal insulin and glucometrics involving GV and TIR is the need of the hour. With this objective, a multinational group of endocrinologists and diabetologists reviewed the existing recommendations on TIR, provided their clinical insights into the individualization of TIR targets, and elucidated on the role of the second-generation basal insulin analogues in addressing TIR.

A Comprehensive Review of Continuous Glucose Monitoring Accuracy during Exercise Periods

Continuous Glucose Monitoring (CGM) has been a springboard of new diabetes management technologies such as integrated sensor-pump systems, the artificial pancreas, and more recently, smart pens. It also allows patients to make better informed decisions compared to a few measurements per day from a glucometer. However, CGM accuracy is reportedly affected during exercise periods, which can impact the effectiveness of CGM-based treatments. In this review, several studies that used CGM during exercise periods are scrutinized. An extensive literature review of clinical trials including exercise and CGM in type 1 diabetes was conducted. The gathered data were critically analysed, especially the Mean Absolute Relative Difference (MARD), as the main metric of glucose accuracy. Most papers did not provide accuracy metrics that differentiated between exercise and rest (non-exercise) periods, which hindered comparative data analysis. Nevertheless, the statistic results confirmed that CGM during exercise periods is less accurate.

Time in range centered diabetes care

Optimal glycemic control remains challenging and elusive for many people with diabetes. With the comprehensive clinical evidence on safety and efficiency in large populations, and with broader reimbursement, the adoption of continuous glucose monitoring (CGM) is rapidly increasing. Standardized visual reporting and interpretation of CGM data and clear and understandable clinical targets will help professionals and individuals with diabetes use diabetes technology more efficiently, and finally improve long-term outcomes with less everyday disease burden. For the majority of people with type 1 or type 2 diabetes, time in range (between 70 and 180 mg/dL, or 3.9 and 10 mmol/L) target of more than 70% is recommended, with each incremental increase of 5% towards this target being clinically meaningful. At the same time, the goal is to minimize glycemic excursions: a recommended target for a time below range (< 70 mg/dL or < 3.9 mmol/L) is less than 4%, and time above range (> 180 mg/dL or 10 mmol/L) less than 25%, with less stringent goals for older individuals or those at increased risk. These targets should be individualized: the personal use of CGM with the standardized data presentation provides all necessary means to accurately tailor diabetes management to the needs of each individual with diabetes.

A thermal activated and differential self-calibrated flexible epidermal biomicrofluidic device for wearable accurate blood glucose monitoring

This paper reports a flexible electronics-based epidermal biomicrofluidics technique for clinical continuous blood glucose monitoring, overcoming the drawback of the present wearables, unreliable measurements. A thermal activation method is proposed to improve the efficiency of transdermal interstitial fluid (ISF) extraction, enabling extraction with a low current density to notably reduce skin irritation. An Na⁺ sensor and a correction model are proposed to eliminate the effect of individual differences, which leads to fluctuations in the amount of ISF extraction. An electrochemical sensor with a 3D nanostructured working electrode surface is designed to enable precise in situ glucose measurement. A differential structure is proposed to eliminate the effect of passive perspiration, which leads to inaccurate blood glucose prediction. Fabrications of the epidermal biomicrofluidic device including formation of flexible electrodes, nanomaterial modification, and enzyme immobilization are fully realized by inkjet printing to enable facile manufacturing with low cost, which benefits practical production.

Reproducibility of Glucose Fluctuations Induced by Moderate Intensity Cycling Exercise in Persons with Type 1 Diabetes

AIMS

The purpose was to assess the reproducibility of glucose changes during three sessions of standardized moderate intensity continuous training of cycling on an individual level in people with type 1 diabetes.

METHODS

Twelve adults (six females) with type 1 diabetes performed three test sessions on an ergometer bicycle (30 min, 67% of predicted heart rate) on three different days. The participants were 36.5 (26.6-45.5) (median, IQR) years old, and their HbA1c was 65 ± 15 mmol/mol (mean ± SD). Two hours before the tests, the participants had a standard meal. Interstitial glucose (IG) and capillary glucose (CG) were measured using an iPro2 Medtronic continuous glucose monitor and the Bayer Contour XT-device, respectively. Prior to the test sessions, resting heart rate was measured using a digital blood pressure monitor to estimate the desired intensity of the exercise.

RESULTS

The average within-participant relationship between the average slope in glucose during sessions 2 and 1 was in IG -0.29 (95% CI -1.11; 0.58) and in CG -0.04 (-0.68; 0.77). Between sessions 3 and 2, IG is 0.18 (-0.27; 0.64) and in CG 0.13 (-0.25; 0.55). Between sessions 3 and 1, IG was 0.06 (-0.57; 0.71) and in CG 0.06 (-0.39; 0.52). The results indicate low reproducibility at participant levels and remained unchanged after adjustment for baseline glucose values.

CONCLUSION

On an individual level, the glucose declines during three standardized sessions of PA were not associated with identical responses of the measured IG and CG levels. An overall anticipated decline of glucose concentrations was found in the moderate intensity cycling sessions. This highlights the importance of regular CG measurements during and after physical activity and awareness towards potential exercise-induced hypoglycemia in persons with type 1 diabetes.

Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA)

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (i.e. before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes. Graphical abstract.

Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA)

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (ie, before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes.

Hypoglycaemia and its management in primary care setting

Hypoglycaemia is common in patients with type 1 diabetes and type 2 diabetes and constitutes a major limiting factor in achieving glycaemic control among people with diabetes. While hypoglycaemia is defined as a blood glucose level under 70 mg/dL (3.9 mmol/L), symptoms may occur at higher blood glucose levels in individuals with poor glycaemic control. Severe hypoglycaemia is defined as an episode requiring the assistance of another person to actively administer carbohydrate, glucagon, or take other corrective actions to assure neurologic recovery. Hypoglycaemia is the most important safety outcome in clinical studies of glucose lowering agents. The American Diabetes Association Standards of Medical Care recommends that a management protocol for hypoglycaemia should be designed and implemented by every hospital, along with a clear prevention and treatment plan. A tailored approach, using clinical and pathophysiologic disease stratification, can help individualize glycaemic goals and promote new therapies to improve quality of life of patients. Data from recent large clinical trials reported low risk of hypoglycaemic events with the use of newer anti-diabetic drugs. Increased hypoglycaemia risk is observed with the use of insulin and/or sulphonylureas. Vulnerable patients with T2D at dual risk of severe hypoglycaemia and cardiovascular outcomes show features of "frailty." Many of such patients may be better treated by the use of GLP-1 receptor agonists or SGLT2 inhibitors rather than insulin. Continuous glucose monitoring (CGM) should be considered for all individuals with increased risk for hypoglycaemia, impaired hypoglycaemia awareness, frequent nocturnal hypoglycaemia and with history of severe hypoglycaemia. Patients with impaired awareness of hypoglycaemia benefit from real-time CGM. The diabetes educator is an invaluable resource and can devote the time needed to thoroughly educate the individual to reduce the risk of hypoglycaemia and integrate the information within the entire construct of diabetes self-management. Conversations about hypoglycaemia facilitated by a healthcare professional may reduce the burden and fear of hypoglycaemia among patients with diabetes and their family members. Optimizing insulin doses and carbohydrate intake, in addition to a short warm up before or after the physical activity sessions may help avoiding hypoglycaemia. Several therapeutic considerations are important to reduce hypoglycaemia risk during pregnancy including administration of rapid-acting insulin analogues rather than human insulin, pre-conception initiation of insulin analogues, and immediate postpartum insulin dose reduction.

The Changing Landscape of Glycemic Targets: Focus on Continuous Glucose Monitoring

Continuous glucose monitoring (CGM) provides comprehensive assessment of daily glucose measurements for patients with diabetes and can reveal high and low blood glucose values that may occur even when a patient's A1C is adequately controlled. Among the measures captured by CGM, the percentage of time in the target glycemic range, or "time in range" (typically 70-180 mg/dL), has emerged as one of the strongest indicators of good glycemic control. This review examines the shift to using CGM to assess glycemic control and guide diabetes treatment decisions, with a focus on time in range as the key metric of glycemic control.

Accuracy of the Dexcom G6 Glucose Sensor during Aerobic, Resistance, and Interval Exercise in Adults with Type 1 Diabetes

The accuracy of continuous glucose monitoring (CGM) sensors may be significantly impacted by exercise. We evaluated the impact of three different types of exercise on the accuracy of the Dexcom G6 sensor. Twenty-four adults with type 1 diabetes on multiple daily injections wore a G6 sensor. Participants were randomized to aerobic, resistance, or high intensity interval training (HIIT) exercise. Each participant completed two in-clinic 30-min exercise sessions. The sensors were applied on average 5.3 days prior to the in-clinic visits (range 0.6–9.9). Capillary blood glucose (CBG) measurements with a Contour Next meter were performed before and after exercise as well as every 10 min during exercise. No CGM calibrations were performed. The median absolute relative difference (MARD) and median relative difference (MRD) of the CGM as compared with the reference CBG did not differ significantly from the start of exercise to the end exercise across all exercise types (ranges for aerobic MARD: 8.9 to 13.9% and MRD: −6.4 to 0.5%, resistance MARD: 7.7 to 14.5% and MRD: −8.3 to −2.9%, HIIT MARD: 12.1 to 16.8% and MRD: −14.3 to −9.1%). The accuracy of the no-calibration Dexcom G6 CGM was not significantly impacted by aerobic, resistance, or HIIT exercise.

Performance of the Eversense versus the Free Style Libre Flash glucose monitor during exercise and normal daily activities in subjects with type 1 diabetes mellitus

INTRODUCTION

Accurate blood glucose measurements are important in persons with diabetes during normal daily activities (NDA), even more so during exercise. We aimed to investigate the performance of fluorescence sensor-based and glucose oxidase-based interstitial glucose measurement during (intensive) exercise and NDA.

RESEARCH DESIGN AND METHODS

Prospective, observational study in 23 persons with type 1 diabetes when mountain biking for 6 days, followed by 6 days of NDA. Readings of the Eversense (fluorescence-based continuous glucose monitoring (CGM); subcutaneously implanted) and of the Free Style Libre (FSL; glucose oxidase-based flash glucose monitoring (FGM); transcutaneously placed) were compared with capillary glucose levels (Free Style Libre Precision NeoPro strip (FSLCstrip)).

RESULTS

Mean average differences (MAD) and mean average relative differences (MARD) were significantly different when comparing exercise with NDA (reference FSLCstrip); Eversense MAD 25±19 vs 17±6 mg/dL (p<0.001); MARD 17±6 vs 13%±6% (p<0.01) and FSL MAD 32±17 vs 18±8 mg/dL (p<0.01); MARD 20±7 vs 12%±5% (p<0.001).When analyzing the data according to the Integrated Continuous Glucose Monitoring Approvals (class II-510(K) guidelines), the overall performance of interstitial glucose readings within 20% of the FSLCstrip during exercise compared with NDA was 69% vs 81% for the Eversense and 59% vs 83% for the FSL, respectively. Within 15% of the FSLCstrip was 59% vs 70% for the Eversense and 46% vs 71% for the FSL.

CONCLUSIONS

During exercise, both fluorescence and glucose oxidase-based interstitial glucose measurements (using Eversense and FSL sensors) were less accurate compared with measurements during NDA. Even when acknowledging the beneficial effects of CGM or FGM, users should be aware of the risk of diminished accuracy of interstitial glucose readings during (intensive) exercise.

Photostable and Proteolysis-Resistant Förster Resonance Energy Transfer-Based Calcium Biosensor

Molecular sensors from protein engineering offer new methods to sensitively bind to and detect target analytes for a wide range of applications. For example, these sensors can be integrated into probes for implantation, and then yield new and valuable physiological information. Here, a new Förster resonance energy transfer (FRET)-based sensor is integrated with an optical fiber to yield a device measuring free Ca²⁺. This membrane encapsulated optical fiber (MEOF) device is composed of a sensor matrix that fills poly(tetrafluoroethylene) (PTFE) with an engineered troponin C (TnC) protein fused to a pair of FRET fluorophores. The FRET efficiency is modulated upon Ca²⁺ ion binding. The probe further comprises a second, size-excluding filter membrane that is synthesized by filling the pores of a PTFE matrix with a poly(ethylene glycol) dimethacrylate (PEGDMA) hydrogel; this design ensures protection from circulating proteases and the foreign body response. The two membranes are stacked and placed on a thin, silica optical fiber for optical excitation and detection. Results show the biosensor responds to changes in Ca²⁺ concentration within minutes with a sensitivity ranging from 0.01 to 10 mM Ca²⁺, allowing discrimination of hyper- and hypocalcemia. Furthermore, the system reversibly binds Ca²⁺ to allow continuous monitoring. This work paves the way for the use of engineered structure-switching proteins for continuous optical monitoring in a large number of applications.

Diabetes Technology and Exercise

Advances in technologies such as glucose monitors, exercise wearables, closed-loop systems, and various smartphone applications are helping many people with diabetes to be more physically active. These technologies are designed to overcome the challenges associated with exercise duration, mode, relative intensity, and absolute intensity, all of which affect glucose homeostasis in people living with diabetes. At present, optimal use of these technologies depends largely on motivation, competence, and adherence to daily diabetes care requirements. This article discusses recent technologies designed to help patients with diabetes to be more physically active, while also trying to improve glucose control around exercise.

Evolution of Diabetes Technology

Technological innovations have fundamentally changed diabetes care. Insulin pump use and continuous glucose monitoring are associated with improved glycemic control along with a better quality of life; automated insulin-dosing advisors facilitate and improve decision making. Glucose-responsive automated insulin delivery enables the highest targets for time in range, lowest rate and duration of hypoglycemia, and favorable quality of life. Clear targets for time in ranges and a standard visualization of the data will help the diabetes technology to be used more efficiently. Decision support systems within and integrated cloud environment will further simplify, unify, and improve modern routine diabetes care.

Benefits and limitations of continuous glucose monitoring in type 1 diabetes

Introduction: Type 1 diabetes (T1D) is a chronic condition characterized by a complete deficiency in insulin production. Optimal management requires constant knowledge of glucose levels for safe and effective insulin administration. Self-monitoring of blood glucose (SMBG) using capillary blood glucose meters is cumbersome and provides limited information to guide management. Continuous glucose monitoring (CGM) technology addresses many of these gaps, but itself has limitations which have prevented people with diabetes and their clinicians from fully embracing this technology. This review covers the benefits and limitations of CGM use, and looks toward future application of this technology in the management of T1D.Areas covered: Impact of CGM on physical and psychosocial outcomes in people with T1D. Barriers to CGM uptake. Integration with insulin pumps and other technologies. Opportunities for future application.Expert opinion: CGM technology will be utilized by the majority of people with T1D and increasing numbers of people with type 2 diabetes due to improved insurance coverage and easier-to-use systems. Its use as part of artificial pancreas systems will add further utility, as it will help to protect from both hypoglycemia and hyperglycemia. People with diabetes will spend more time in range and experience fewer acute and chronic complications.

Monitoring of Pediatric Type 1 Diabetes

Regular self-monitoring of blood glucose levels, and ketones when indicated, is an essential component of type 1 diabetes (T1D) management. Although fingerstick blood glucose monitoring has been the standard of care for decades, ongoing rapid technological developments have resulted in increasingly widespread use of continuous glucose monitoring (CGM). This article reviews recommendations for self-monitoring of glucose and ketones in pediatric T1D with particular emphasis on CGM and factors that impact the accuracy and real-world use of this technology.

Performance of the Freestyle Libre flash glucose monitoring (flash GM) system in individuals with type 1 diabetes: A secondary outcome analysis of a randomized crossover trial

AIMS

The efficacy of flash glucose monitoring (flash GM) systems has been demonstrated by improvements in glycaemia; however, during high rates of glucose flux, the performance of continuous glucose monitoring systems was impaired, as detailed in previous studies. This study aimed to determine the performance of the flash GM system during daily-life glycaemic challenges such as carbohydrate-rich meals, bolus insulin-induced glycaemic disturbances and acute physical exercise in individuals with type 1 diabetes.

MATERIALS AND METHODS

This study comprised four randomized trial visits with alternating pre- and post-exercise bolus insulin doses. Throughout the four 14-hour inpatient phases, 19 participants received three carbohydrate-rich meals and performed moderate-intensity exercise. Venous blood glucose and capillary blood glucose during exercise was compared to interstitial glucose concentrations. Flash GM accuracy was assessed by median absolute relative difference (MARD) (interquartile range [IQR]) using the Bland-Altman method and Clark error grid, as well as according to guidelines for integrated CGM approvals (Class II-510(K)).

RESULTS

The overall MARD (IQR) during inpatient phases was 14.3% (6.9%-22.8%), during hypoglycaemia (≤3.9 mmol/L) was 31.6% (16.2%-46.8%), during euglycaemia (4.0 mmol/L - 9.9 mmol/L) was 16.0% (8.5%-24.0%) and during hyperglycaemia (≥10 mmol/L) was 9.4% (5.1%-15.7%). Overall Bland-Altman analysis showed a bias (95% LoA) of 1.26 mmol/L (-1.67 to 4.19 mmol/L). The overall MARD during acute exercise was 29.8% (17.5%-39.8%), during hypoglycaemia was 45.1% (35.2%-51.1%), during euglycaemia was 30.7% (18.7%-39.2%) and during hyperglycaemia was 16.3% (10.0%-22.8%).

CONCLUSION

Flash GM interstitial glucose readings were not sufficiently accurate within the hypoglycaemic range and during acute exercise and require confirmatory blood glucose measurements.

MiniMed 670G hybrid closed loop artificial pancreas system for the treatment of type 1 diabetes mellitus: overview of its safety and efficacy

Introduction: Automated insulin delivery for people with type 1 diabetes has been a major goal in the diabetes technology field for many years. While a fully automated system has not yet been accomplished, the MiniMed™ 670G artificial pancreas (AP) system is the first commercially available insulin pump that automates basal insulin delivery, while still requiring user input for insulin boluses. Determining the safety and efficacy of this system is essential to the development of future devices striving for more automation. Areas Covered: This review will provide an overview of how the MiniMed 670G system works including its safety and efficacy, how it compares to similar devices, and anticipated future advances in diabetes technology currently under development. Expert Opinion: The ultimate goal of advanced diabetes technologies is to reduce the burden and amount of management required of patients with diabetes. In addition to reducing patient workload, achieving better glucose control and improving hemoglobin A1c (HbA1c) values are essential for reducing the threat of diabetes-related complications further down the road. Current devices come close to reaching these goals, but understanding the unmet needs of patients with diabetes will allow future technologies to achieve these goals more quickly.

Enhanced Accuracy of Continuous Glucose Monitoring during Exercise through Physical Activity Tracking Integration

Current Continuous Glucose Monitors (CGM) exhibit increased estimation error during periods of aerobic physical activity. The use of readily-available exercise monitoring devices opens new possibilities for accuracy enhancement during these periods. The viability of an array of physical activity signals provided by three different wearable devices was considered. Linear regression models were used in this work to evaluate the correction capabilities of each of the wearable signals and propose a model for CGM correction during exercise. A simple two-input model can reduce CGM error during physical activity (17.46% vs. 13.8%, p < 0.005) to the magnitude of the baseline error level (13.61%). The CGM error is not worsened in periods without physical activity. The signals identified as optimal inputs for the model are "Mets" (Metabolic Equivalent of Tasks) from the Fitbit Charge HR device, which is a normalized measurement of energy expenditure, and the skin temperature reading provided by the Microsoft Band 2 device. A simpler one-input model using only "Mets" is also viable for a more immediate implementation of this correction into market devices.