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

Automated insulin delivery in children with type 1 diabetes during physical activity: a meta-analysis

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.

Ultra-stable insulin-glucagon fusion protein exploits an endogenous hepatic switch to mitigate hypoglycemic risk

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.

Noninvasive Real-Time Glucose Monitoring Is in the Near Future

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.

Factory-Calibrated Continuous Glucose Monitoring System Accuracy During Exercise in Adolescents With Type 1 Diabetes Mellitus

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.

Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge

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.

Lab on skin: real-time metabolite monitoring with polyphenol film based subdermal wearable patches

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.

Estimating Glycemia From HbA1c and CGM: Analysis of Accuracy and Sources of Discrepancy

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.

Detection of Hypoglycemia and Hyperglycemia Using Noninvasive Wearable Sensors: Electrocardiograms and Accelerometry

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.

Exercising Safely with the MiniMed™ 780G Automated Insulin Delivery System

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.

Continuous glucose monitoring for automatic real-time assessment of eating events and nutrition: a scoping review

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.

Neural Networks With Gated Recurrent Units Reduce Glucose Forecasting Error Due to Changes in Sensor Location

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.

(Hybrid) Closed-Loop Systems: From Announced to Unannounced Exercise

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.

Factory-Calibrated Continuous Glucose Monitoring Systems in Type 1 Diabetes: Accuracy during In-Clinic Exercise and Home Use

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.

Comparative Analysis of Predictive Interstitial Glucose Level Classification Models

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.

Continuous Glucose Monitoring (CGM) in Sports-A Comparison between a CGM Device and Lab-Based Glucose Analyser under Resting and Exercising Conditions in Athletes

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.

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

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).

Clinical Considerations and Practical Advice for People Living With Type 2 Diabetes Who Undertake Regular Exercise or Aim to Exercise Competitively

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.

Practical Aspects and Exercise Safety Benefits of Automated Insulin Delivery Systems in Type 1 Diabetes

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.

Physical Activity Management for Youth With Type 1 Diabetes: Supporting Active and Inactive Children

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.

Noninvasive Continuous Glucose Monitoring With a Novel Wearable Dial Resonating Sensor: A Clinical Proof-of-Concept Study

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.

CGM accuracy: Contrasting CE marking with the governmental controls of the USA (FDA) and Australia (TGA): A narrative review

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.

Use of Continuous Glucose Monitors to Manage Type 1 Diabetes Mellitus: Progress, Challenges, and Recommendations

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.

Unmanned Aerial Vehicle Mediated Drug Delivery for First Aid

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.

The Effect of Starting Blood Glucose Levels on Serum Electrolyte Concentrations during and after Exercise in Type 1 Diabetes

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.

Distributed Assessment of Virtual Insulin-Pump Settings Using SmartCGMS and DMMS.R for Diabetes Treatment

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.

Flash glucose monitoring system in special situations

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.

Accuracy of CGM Systems During Continuous and Interval Exercise in Adults with Type 1 Diabetes

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.

Rossitto J, Ray K, A. Dufurrena Q, Blue RS. Blood Glucose Alterations and Continuous Glucose Monitoring in Centrifuge-Simulated Spaceflight

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.

Monitoring of paediatric type 1 diabetes

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.

The Potential of Current Noninvasive Wearable Technology for the Monitoring of Physiological Signals in the Management of Type 1 Diabetes: Literature Survey

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.

Where can you wear your Libre? Using the FreeStyle Libre continuous glucose monitor on alternative sites

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.

A Brief Review on the Evolution of Technology in Exercise and Sport in Type 1 Diabetes: Past, Present, and Future

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.

MXene nanoflakes decorating ZnO tetrapods for enhanced performance of skin-attachable stretchable enzymatic electrochemical glucose sensor

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.

Practical aspects of diabetes technology use: Continuous glucose monitors, insulin pumps, and automated insulin delivery systems

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.

Performance of intermittently scanned continuous glucose monitoring systems in people with type 1 diabetes: A pooled analysis

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.

Considerations in the Care of Athletes With Type 1 Diabetes Mellitus

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.

Products for Monitoring Glucose Levels in the Human Body With Noninvasive Optical, Noninvasive Fluid Sampling, or Minimally Invasive Technologies

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.

The automated pancreas: A review of technologies and clinical practice

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.

Nutritional support for a person with type 1 diabetes undertaking endurance swimming

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.

Use of continuous glucose monitoring trend arrows in the younger population with type 1 diabetes

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.

Physical Activity, Dietary Patterns, and Glycemic Management in Active Individuals with Type 1 Diabetes: An Online Survey

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.

Toward an Optimal Definition of Hypoglycemia with Continuous Glucose Monitoring

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.

Janus Hydrogel Microbeads for Glucose Sensing with pH Calibration

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.

American Association of Clinical Endocrinology Clinical Practice Guideline: The Use of Advanced Technology in the Management of Persons With Diabetes Mellitus

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.

Time in Range for Closed-Loop Systems versus Standard of Care during Physical Exercise in People with Type 1 Diabetes: A Systematic Review and Meta-Analysis

The aim of this systematic review and meta-analysis was to compare time in range (TIR) (70–180 mg/dL (3.9–10.0 mmol/L)) between fully closed-loop systems (CLS) and standard of care (including hybrid systems) during physical exercise in people with type 1 diabetes (T1D). A systematic literature search was conducted in EMBASE, PubMed, Cochrane Central Register of Controlled Trials, and ISI Web of Science from January 1950 until January 2020. Randomized controlled trials including studies with different CLS were compared against standard of care in people with T1D. The meta-analysis was performed using the random effects model and restricted maximum likelihood estimation method. Six randomized controlled trials involving 153 participants with T1D of all age groups were included. Due to crossover test designs, studies were included repeatedly (a–d) if CLS or physical exercise interventions were different. Applying this methodology increased the comparisons to a total number of 266 participants. TIR was higher with an absolute mean difference (AMD) of 6.18%, 95% CI: 1.99 to 10.38% in favor of CLS. In a subgroup analysis, the AMD was 9.46%, 95% CI: 2.48% to 16.45% in children and adolescents while the AMD for adults was 1.07% 95% CI: −0.81% to 2.96% in favor of CLS. In this systematic review and meta-analysis CLS moderately improved TIR in comparison to standard of care during physical exercise in people with T1D. This effect was particularly pronounced for children and adolescents showing that the use of CLS improved TIR significantly compared to standard of care.

Review: Glucose-sensitive insulin

BACKGROUND

Hypoglycemia, the condition of low blood sugar, is a common occurance in people with diabetes using insulin therapy. Protecting against hypoglycaemia by engineering an insulin preparation that can auto-adjust its biological activity to fluctuating blood glucose levels has been pursued since the 1970s, but despite numerous publications, no system that works well enough for practical use has reached clinical practise.

SCOPE OF REVIEW

This review will summarise and scrutinise known approaches for producing glucose-sensitive insulin therapies. Notably, systems described in patent applications will be extensively covered, which has not been the case for earlier reviews of this area.

MAJOR CONCLUSIONS

The vast majority of published systems are not suitable for product development, but a few glucose-sensitive insulin concepts have recently reached clinical trials, and there is hope that glucose-sensitive insulin will become available to people with diabetes in the near future.

Flash Continuous Glucose Monitoring: A Practical Guide and Call to Action for Pharmacists

Despite advances in diabetes technology, the proportion of patients with type 2 diabetes achieving recommended glycemic goals remains suboptimal. There is a growing interest in flash continuous glucose monitoring (CGM) among patients, pharmacists and providers. Pharmacists are well positioned to collaborate with patients and providers in ambulatory care or community-based settings to allow a greater number of patients with diabetes to harness the benefits of flash CGM. The purpose of this narrative review is to provide pharmacists with a background on flash CGM technology, review the data supporting pharmacist-driven flash CGM services, and address common questions that arise in pharmacy practice surrounding flash CGM.