Emerging Diabetes Technologies: Continuous Glucose Monitors/Artificial Pancreases

Effect of introduction of intermittently scanned continuous glucose monitoring on glycaemic control in individuals living with type 2 diabetes mellitus treated with non-insulin therapies-A randomised controlled trial

AIMS

This pilot randomised controlled trial aimed to evaluate the effect of introducing isCGM on glycaemic control and diabetes distress in individuals with T2DM receiving non-insulin therapies.

MATERIALS AND METHODS

Forty adults with T2DM were randomised to either receive FreeStyle Libre 2 (Libre 2), an isCGM system, or FreeStyle Libre Pro iQ (Libre Pro) also known as 'blinded' CGM. Participants were followed for 12 weeks. The primary outcome was a fall in haemoglobin A1c (HbA1c) of ≥5.5 mmol/mol. Diabetes distress was assessed using the two-item diabetes distress scale (DDS2).

RESULTS

The median age was 59.5 years; 57.5% were male. Of the Libre 2 users, 53% achieved a ≥5.5 mmol/mol reduction in HbA1c compared to 35% in the Libre pro group (p = 0.34). Compared to Libre Pro, the use of Libre 2 was associated with an improved time in range at 12 weeks of 18 percentage points (confidence interval 2-35, p = 0.028). Participants in the Libre 2 group exhibited a non-significant reduction in HbA1c levels of 8 mmol/mol compared to the Libre Pro group after 12 weeks. However, no significant differences were observed in other CGM metrics or diabetes distress between the study groups.

CONCLUSIONS

The use of isCGM in individuals living with T2DM on non-insulin therapy showed promise in improving glycaemic control, as evidenced by increased TIR, albeit without a significant reduction in HbA1c or impact on diabetes distress, suggesting this could be potentially beneficial in individuals with T2DM.

A Performance-Based Adaptation Index for Automated Insulin Delivery Systems

BACKGROUND

Automated insulin delivery (AID) algorithms can benefit from tuning of their aggressiveness to meet individual needs, as insulin requirements vary among and within users. We introduce the Performance-Based Adaptation Index (PAI), a tool designed to enable automatic adjustment of an AID system aggressiveness based on continuous glucose monitoring (CGM) metrics.

METHODS

PAI integrates two CGM-based metrics-one for hypoglycemia and another for hyperglycemia exposure-over a previous time window into a single index (α θ ). We propose two methods to compute α θ : one based on time in range (TIR, 70-180 mg/dL), and the other on glycemic risk indices. Using α θ , we developed a multiplicative strategy to adjust the AID system's aggressiveness, accounting for situations where α θ cannot be reliably calculated. The feasibility of this method was assessed in-silico using the UVA/Padova Type 1 Diabetes Simulator and our full closed-loop algorithm (UVA-model predictive control (MPC)) across five scenarios: optimal tuning (baseline), conservative and aggressive tunings, and temporary and permanent changes in insulin needs. Glycemic outcomes were evaluated from the simulated glucose traces.

RESULTS

Negligible performance variations were observed in the baseline scenario. For the conservative scenario, adjusting α θ improved TIR (35.1% vs 71.8%) and increased total daily insulin (32.1 U vs 41.2 U). Conversely, for the aggressive scenario, it reduced hypoglycemia exposure (TBR: 2.6% vs 1.4%) and overall insulin usage (45.6 U vs 43.0 U).

CONCLUSION

In-silico results demonstrated the safety and efficacy of using PAI to automatically tune the UVA-MPC controller, achieving TIR values above 70% under fully closed-loop conditions and across various physiological states. Clinical validation of these results is warranted.

Severe Diabetic Ketoacidosis in Children with Type 1 Diabetes: Ongoing Challenges in Care

Diabetic ketoacidosis is the most common acute complication in children and adolescents with type 1 diabetes, and contributes significantly to morbidity, mortality, and healthcare burden. This review aims to explore the multifaceted aspects of severe diabetic ketoacidosis in pediatric age, including its epidemiology, pathogenesis, risk factors, complications and emphasizing advances in prevention strategies. Incidence rates vary due to influences from geographic, socioeconomic, cultural and demographic factors. Pathogenesis is linked to insulin deficiency and an excess of counter-regulatory hormones, which disrupt glucose, protein, and lipid metabolism, causing hyperglycemia, ketosis, acidosis, dehydration, and electrolyte imbalances. According to the International Society for Pediatric and Adolescent Diabetes guidelines, severe diabetic ketoacidosis is characterized by a pH < 7.1 or bicarbonate < 5 mmol/L. This condition can lead to a wide range of life-threatening complications, including cerebral edema that represents the leading cause of death. Several prevention strategies, including awareness campaigns, early diagnosis of diabetes, regular monitoring and management, effective insulin therapy, education, access to healthcare and technological assistance, may contribute to reduce the risk of severe diabetic ketoacidosis episodes in children and adolescents.

International Society for Pediatric and Adolescent Diabetes Clinical Practice Consensus Guidelines 2024: Glycemic Targets

The International Society for Pediatric and Adolescent Diabetes (ISPAD) guidelines represent a rich repository that serves as the only comprehensive set of clinical recommendations for children, adolescents, and young adults living with diabetes worldwide. This chapter builds on the 2022 ISPAD guidelines, and updates recommendations on the glycemic targets for children and adolescents living with diabetes. A new target for hemoglobin A1c (HbA1c) of ≤6.5% (48 mmol/mol) is recommended for those who have access to advanced diabetes technologies like continuous glucose monitoring and automated insulin delivery. This target should be encouraged for all children and adolescents living with diabetes when safely achievable. In other settings, the HbA1c target is ≤7.0% (53 mmol/mol). The International Society for Pediatric and Adolescent Diabetes (ISPAD) guidelines represent a rich repository that serves as the only comprehensive set of clinical recommendations for children, adolescents, and young adults living with diabetes worldwide. This chapter builds on the 2022 ISPAD guidelines, and updates recommendations on the glycemic targets for children and adolescents living with diabetes. A new target for hemoglobin A1c (HbA1c) of ≤6.5% (48 mmol/mol) is recommended for those who have access to advanced diabetes technologies like continuous glucose monitoring and automated insulin delivery. This target should be encouraged for all children and adolescents living with diabetes when safely achievable. In other settings, the HbA1c target is ≤7.0% (53 mmol/mol).

The effect of telehealth on clinical outcomes in patients with hypertension and diabetes: A meta-analysis of 106,261 patients

INTRODUCTION

Telemedicine, propelled by recent technological advancements, has transformed healthcare delivery, notably benefiting patients with chronic non-communicable diseases (NCDs) such as systemic arterial hypertension and diabetes mellitus. This meta-analysis of randomized clinical trials aimed to assess the efficacy of telehealth-based interventions on disease control rates and clinical parameters among NCD patients, including systolic and diastolic blood pressure (SBP and DBP), fasting blood glucose (FBG), and glycated hemoglobin (HbA1c) levels.

METHODS

We conducted searches in PubMed, Scopus, Web of Science, and the Cochrane Database for interventional studies that compared tele-monitoring with usual care in patients with hypertension and type 2 diabetes mellitus. Odds ratios with 95% confidence intervals (CIs) were computed.

RESULTS

Our meta-analysis included 75 studies, encompassing a total of 106,261 patients, with 50,074 (47.12%) receiving usual care and 56,187 (52.88%) receiving tele-monitoring care. The telemedicine group was associated with a statistically significant reduction in SBP (mean difference (MD) -4.927 mmHg; 95% CI -6.193 to -3.660; p < 0.001; I² = 90%), DBP (MD -2.019 mmHg; 95% CI -2.679 to -1.359; p < 0.001; I² = 54%), FBG (MD -0.405 mmol/L; 95% CI -0.597 to -0.213; p < 0.001; I² = 32%), and HbA1c (MD -0.418%; 95% CI -0.525 to -0.312; p < 0.001; I² = 76%).

CONCLUSIONS

Our meta-analysis shows that telehealth technologies notably enhance blood pressure and blood glucose control. This supports integrating telemedicine into clinical protocols as a valuable complementary tool for managing hypertension and diabetes mellitus comprehensively.

Continuous Glucose Monitoring-New Diagnostic Tool in Complex Pathophysiological Disorder of Glucose Metabolism in Children and Adolescents with Obesity

Obesity is one of the leading causes of chronic diseases, and its prevalence is still rising in children and adolescent populations. Chronic cardiovascular complications result in metabolic syndrome (MS) and type 2 diabetes mellitus. Key factors in the development of MS are insulin resistance and low-grade inflammation. The disorder of glucose and insulin metabolism has not been fully elucidated so far, and an oral glucose tolerance test (OGTT) has been the only tool used to look into the complex metabolism disorder in children and adolescents with obesity. Continuous glucose monitoring (CGM) has become commercially available for over two decades and is primarily used to manage type 1 diabetes mellitus in pediatric populations. This review aims to present the current knowledge about the use of CGM in children and adolescent populations with obesity. CGM systems have the potential to serve as valuable tools in everyday clinical practices, not only in the better diagnosis of chronic complications associated with obesity, but CGM can also assist in interventions to make better adjustments to nutritional and therapeutic approaches based on real-time glucose monitoring data. Despite these promising benefits, further research is needed to fully understand the role of CGM in metabolic disorders in pediatric populations with obesity, which will additionally strengthen the importance of CGM systems in everyday clinical practices.

Can Digital Technology Revolutionize Continuous Education in Diabetes Care?

Rapid technological advancements, such as artificial intelligence, wearable technologies, and telehealth with remote monitoring, are transforming continuous education for health care providers (HCPs) in diabetes management. These technologies improve patient care and necessitate innovative educational approaches to prepare HCPs for clinical integration. Digital education offers real-time, scalable, and cost-effective solutions, especially in areas with health care workforce shortages. However, the effect of digital education on HCPs' knowledge, skills, attitudes, and patient outcomes remains under-researched and necessitates further study. As technologies advance, achieving precision in diabetes continuous education becomes feasible. The 2024 ADA Standards of Care emphasize early adoption of advanced technologies and proficiency among HCPs. This commentary explores transformative trends, discussing limitations and proposing solutions to revolutionize continuous education in diabetes care.

Advancements in Insulin Pumps: A Comprehensive Exploration of Insulin Pump Systems, Technologies, and Future Directions

Insulin pumps have transformed the way diabetes is managed by providing a more accurate and individualized method of delivering insulin, in contrast to conventional injection routines. This research explores the progression of insulin pumps, following their advancement from initial ideas to advanced contemporary systems. The report proceeds to categorize insulin pumps according to their delivery systems, specifically differentiating between conventional, patch, and implantable pumps. Every category is thoroughly examined, emphasizing its unique characteristics and capabilities. A comparative examination of commercially available pumps is provided to enhance informed decision making. This section provides a thorough analysis of important specifications among various brands and models. Considered factors include basal rate and bolus dosage capabilities, reservoir size, user interface, and compatibility with other diabetes care tools, such as continuous glucose monitoring (CGM) devices and so on. This review seeks to empower healthcare professionals and patients with the essential information to improve diabetes treatment via individualized pump therapy options. It provides a complete assessment of the development, categorization, and full specification comparisons of insulin pumps.

Predicting stress levels using physiological data: Real-time stress prediction models utilizing wearable devices

Stress has emerged as a prominent and multifaceted health concern in contemporary society, manifesting detrimental effects on individuals' physical and mental health and well-being. The ability to accurately predict stress levels in real time holds significant promise for facilitating timely interventions and personalized stress management strategies. The increasing incidence of stress-related physical and mental health issues highlights the importance of thoroughly understanding stress prediction mechanisms. Given that stress is a contributing factor to a wide array of mental and physical health problems, objectively assessing stress is crucial for behavioral and physiological studies. While numerous studies have assessed stress levels in controlled environments, the objective evaluation of stress in everyday settings still needs to be explored, primarily due to contextual factors and limitations in self-report adherence. This short review explored the emerging field of real-time stress prediction, focusing on utilizing physiological data collected by wearable devices. Stress was examined from a comprehensive standpoint, acknowledging its effects on both physical and mental well-being. The review synthesized existing research on the development and application of stress prediction models, underscoring advancements, challenges, and future directions in this rapidly evolving domain. Emphasis was placed on examining and critically evaluating the existing research and literature on stress prediction, physiological data analysis, and wearable devices for stress monitoring. The synthesis of findings aimed to contribute to a better understanding of the potential of wearable technology in objectively assessing and predicting stress levels in real time, thereby informing the design of effective interventions and personalized stress management approaches.

Blood glucose monitoring devices for type 1 diabetes: a journey from the food and drug administration approval to market availability

Blood glucose monitoring constitutes a pivotal element in the clinical management of Type 1 diabetes (T1D), a globally escalating metabolic disorder. Continuous glucose monitoring (CGM) devices have demonstrated efficacy in optimizing glycemic control, mitigating adverse health outcomes, and augmenting the overall quality of life for individuals afflicted with T1D. Recent progress in the field encompasses the refinement of electrochemical sensors, which enhances the effectiveness of blood glucose monitoring. This progress empowers patients to assume greater control over their health, alleviating the burdens associated with their condition, and contributing to the overall alleviation of the healthcare system. The introduction of novel medical devices, whether derived from existing prototypes or originating as innovative creations, necessitates adherence to a rigorous approval process regulated by the Food and Drug Administration (FDA). Diverse device classifications, stratified by their associated risks, dictate distinct approval pathways, each characterized by varying timelines. This review underscores recent advancements in blood glucose monitoring devices primarily based on electrochemical sensors and elucidates their regulatory journey towards FDA approval. The advent of innovative, non-invasive blood glucose monitoring devices holds promise for maintaining stringent glycemic control, thereby preventing T1D-associated comorbidities, and extending the life expectancy of affected individuals.

Need for an Artificial Intelligence-based Diabetes Care Management System in India and the United States

Objective

Diabetes mellitus is an important chronic disease that is prevalent around the world. Different countries and diverse cultures use varying approaches to dealing with this chronic condition. Also, with the advancement of computation and automated decision-making, many tools and technologies are now available to patients suffering from this disease. In this work, the investigators attempt to analyze approaches taken towards managing this illness in India and the United States.

Methods

In this work, the investigators have used available literature and data to compare the use of artificial intelligence in diabetes management.

Findings

The article provides key insights to comparison of diabetes management in terms of the nature of the healthcare system, availability, electronic health records, cultural factors, data privacy, affordability, and other important variables. Interestingly, variables such as quality of electronic health records, and cultural factors are key impediments in implementing an efficiency-driven management system for dealing with this chronic disease.

Conclusion

The article adds to the body of knowledge associated with the management of this disease, establishing a critical need for using artificial intelligence in diabetes care management.

Transform diabetes care with precision medicine

Background and Aims

Diabetes is a global concern. This article took a closer look at diabetes and precision medicine.

Methods

A literature search of studies related to the use of precision medicine in diabetes care was conducted in various databases (PubMed, Google Scholar, and Scopus).

Results

Precision medicine encompasses the integration of a wide array of personal data, including clinical, lifestyle, genetic, and various biomarker information. Its goal is to facilitate tailored treatment approaches using contemporary diagnostic and therapeutic techniques that specifically target patients based on their genetic makeup, molecular markers, phenotypic traits, or psychosocial characteristics. This article not only highlights significant advancements but also addresses key challenges, particularly focusing on the technologies that contribute to the realization of personalized and precise diabetes care.

Conclusion

For the successful implementation of precision diabetes medicine, collaboration and coordination among multiple stakeholders are crucial.