Hypoglycemia in diabetes

The Glycemic Impact of Protein Ingestion in People With Type 1 Diabetes

In individuals with type 1 diabetes, carbohydrate is commonly recognized as the primary macronutrient influencing postprandial glucose levels. Accumulating evidence indicates that protein ingestion also contributes to the increment in postprandial glucose levels, despite endocrine and metabolic responses different from those with carbohydrate ingestion. However, findings regarding protein ingestion's glycemic effect in people with type 1 diabetes are equivocal, with the magnitude of glycemic response seemingly dependent on the rate of absorption and composition of protein ingested. Therefore, the aim of this article is to outline the physiological mechanisms by which ingested protein influences blood glucose regulation in individuals with type 1 diabetes and provide clinical implications on use of dietary protein in the context of glycemic management. Specifically, protein ingestion raises plasma amino acid levels, which directly or indirectly (via gut hormones) stimulates glucagon secretion. Together with the increase in gluconeogenic precursors and an absent endogenous insulin response in individuals with type 1 diabetes, this provides a synergistic physiological environment for increased endogenous glucose production and subsequently increasing circulating glucose levels for several hours. While there is a dearth of well-controlled studies in this area, we provide clinical implications and directions for future research regarding the potential for using ingestion of fast-absorbing protein (such as whey protein) as a tool to prevent and mitigate overnight- and exercise-induced hypoglycemia in people with type 1 diabetes.

An electrochromism-equipped enzymatic biofuel cell system combined with hollow microneedle array for self-powered glucose sensing in interstitial fluid

A disposable, self-powered enzymatic biofuel cell (BFC) sensor integrated with a hollow microneedle array (HMNA) for glucose monitoring in interstitial fluid (ISF) is reported. The HMNA enables painless and minimally invasive ISF extraction. The BFC uses dehydrogenase (GDH) in conjunction with NAD+, diaphorase (DI), and vitamin K3 (VK3) serving as electron transfer mediators as the anode catalyst and Prussian blue (PB) as the electrochromic cathode. Glucose oxidation at the anode generates electrons that cause PB to change the color at the cathode, allowing for visual glucose concentration determination. The open-circuit potential (OCP) of the sensor is 0.14 V, with a maximum power density of 0.07 µW·cm-2, at a glucose concentration of 14 mM. The sensor shows good performance in glucose sensing with a linear relationship between the R/B ratio and glucose concentrations ranging from 0 to 14 mM. This disposable device offers a promising approach for non-invasive and self-powered glucose sensing.

Supporting islet function in a PVDF membrane based macroencapsulation delivery device by solvent non-solvent casting using PVP

Type 1 diabetic (T1D) patients are life-long dependent on insulin therapy to keep their blood glucose levels under control. An alternative cell-based therapy for exogenous insulin injections is clinical islet transplantation (CIT). Currently the widespread application of CIT is limited, due to risks associated with the life-long use of immunosuppressive drugs to prevent rejection of donor cells. An immunoprotective macroencapsulation device can protect allogeneic islet cells against the host immune system and allow exploring extrahepatic transplantation sites. We report on the characterization and creation of porous polyvinylidene fluoride (PVDF) membrane-based devices intended for islet and beta-cell transplantation. We hypothesize that by incorporating polyvinyl-pyrrolidone (PVP) into a PVDF solution the permeability of PVDF membranes for insulin and glucose can be improved by solvent-non solvent casting to create submicrometer porous films. We show that the use of water-soluble PVP, can significantly increase glucose diffusion through these membranes while still having the ability to block immune cells from migrating through these membranes. Human donor islets loaded into devices made from these thin PVDF/PVP membranes showed a 92 ±  4% viability after 8 days similar to their free-floating counterparts. The glucose responsiveness of human donor islets encapsulated inside PVDF/PVP membrane-based devices was significantly improved compared to islets seeded in devices made from PVDF membranes without PVP, with a stimulation index of 3.2 for PVDF/PVP devices and 1.3 for PVDF-alone devices at day 8. Our data show that by addition of PVP as pore forming agent during membrane fabrication at a specific ratio the diffusion characteristics can be tuned such that human islet function in these closed macrodevices, can be kept at the same level as non-encapsulated islets, while the membrane can still serve as a protective barrier preventing the entry of primary human macrophages and damaging beta cells.

Self-reported hypoglycemia and associated factors among patients living with T1D s at University of Gondar Comprehensive Specialized Hospital, Northwest, Ethiopia: a cross-sectional study

Background

Hypoglycemia is a major public health problem that negatively influences blood glucose control in the treatment of type 1 diabetes. It has more severe clinical and economic effects in patients living with T1D patients. However, real-world clinical evidence of reported hypoglycemia is limited. Thus, the purpose of the study was to determine the prevalence of self-reported hypoglycemia and its associated factors among patients living with T1Dat the University of Gondar Comprehensive Specialized Hospital (UOGCSH).

Methods

A prospective hospital-based cross-sectional study was conducted among patients living with T1D attending the ambulatory clinic of UOGCSH from November 1, 2021, to April 30, 2022. To select the study participants, a convenient sampling technique was used. Multivariable binary logistic regression was used to identify predictors of self-reported hypoglycemia. A P-value < 0.05 was considered statistically significant and reported as a 95% Confidence Interval (CI).

Results

A total of 216 patients living with T1D (mean age: 50.91 ± 18.98 years) were included. The mean duration of DM diagnosis and insulin use were 9.41 ± 8.00 and 7.10 ± 6.00 years, respectively. Self-reported hypoglycemia was prevalent among 86.6% (95% CI: 82.1-91.0) of the study participants, with 69% experiencing non-severe and 31% experiencing severe hypoglycemia. More than half of the patients, 122 (56.5%), reported experiencing four or more (≥ 4) episodes of hypoglycemia. Knowledge of insulin self-administration, specifically a low level of knowledge (AOR=4.87; 95% CI: 1.55-15.26), was significantly associated with self-reported hypoglycemia. The majority of patients living with T1D, 155 (71.8%), had impaired awareness of hypoglycemia.

Conclusion

Self-reported hypoglycemia was considerably high among Patients living with T1D. Knowledge of insulin self-administration, specifically at a low level, was associated with an increased risk of reported hypoglycemia. Thus, continued health education of Patients living with T1D regarding insulin self-administration and awareness of hypoglycemia symptoms is necessary to prevent further complications.

A Five-Year Journey to Diagnosis: Resolving Persistent Hypoglycemia Through Successful Insulinoma Resection-A Case Report

Insulinoma is a rare functional pancreatic neuroendocrine tumor with an annual prevalence of 0.5-5 cases per million. It is characterized by excessive insulin secretion, leading to recurrent hypoglycemia, often diagnosed through Whipple's triad: hypoglycemic symptoms, documented low plasma glucose, and symptom resolution after glucose administration. Approximately 90% of insulinomas are sporadic, while 10% are associated with multiple endocrine neoplasia type 1. Diagnosis is frequently delayed due to nonspecific symptoms and misattributions to neurological or psychiatric conditions. Biochemical confirmation through a supervised fasting test and advanced imaging modalities, including CT, MRI, and endoscopic ultrasound (EUS), is essential for identifying and localizing the tumor. We report the case of a 52-year-old male who presented with a 5-year history of recurrent fasting and postprandial hypoglycemic episodes, including adrenergic and neuroglycopenic symptoms such as palpitations, diaphoresis, dizziness, and episodes of altered sensorium. Initial evaluations misattributed his symptoms to neurological and cardiac disorders, delaying diagnosis. Upon presentation, Whipple's triad was confirmed, and biochemical testing revealed hyperinsulinemic hypoglycemia (plasma glucose: 27 mg/dL, serum insulin: 45.83 mIU/L, C-peptide: 7.03 ng/mL). Imaging identified a 3 × 3 cm hypervascular lesion in the pancreatic tail. The patient underwent distal pancreatectomy, and histopathological analysis confirmed a grade 1 neuroendocrine tumor. Postoperative outcomes were favorable, with complete resolution of symptoms and normalization of glucose and insulin levels. Follow-up showed no recurrence of hypoglycemia. This case underscores the challenges in diagnosing insulinoma due to nonspecific symptoms and highlights the importance of Whipple's triad, biochemical tests, and imaging in timely diagnosis. Surgical resection remains the definitive treatment, with excellent long-term outcomes when performed promptly.

Developing and standardizing a tool to assess the health education needs of diabetic patients at Jazan Armed Forces Hospital

BACKGROUND

Determining the health educational needs of people living with diabetes is essential in developing patient-centered, structured health education programs that aim to improve the outcome of diabetes care.

OBJECTIVES

To develop a tool for the identification of the health education needs of individuals living with diabetes in the Jazan Armed Forces Hospital (JAFH) and to standardize the questionnaire through the assessment of its reliability and validity.

METHODS

A cross-sectional design was used in the present work, which included 303 participants living with diabetes. The researchers and an expert panel in family medicine and endocrinology created a comprehensive and mutually exhaustive questionnaire covering every potential area of health education needs. It included a 15-item section with questions on a 5-point Likert scale for determining the participants' needs for health education. Cronbach's alpha was used to determine the Likert scale's reliability. Exploratory factor analysis was used to determine the Likert scale's construct validity.

RESULTS

The total number of males was 123 (40.6%) and that of females was 180 (59.4%). Their mean ages were 55.9 ± 12.9, ranging from 18 to 94 years. The reliability of the 15-item Likert scale was 83%, and it increased to 90% when the redundant items (n = 5) were eliminated. The test had an 86% test-retest reliability when repeated. Also, the final 10-item Likert scale has significant face, content, and construct validity. Two components with eigenvalues over 1 (generic knowledge about diabetes, and diabetes and travel) could be extracted out of the 10-item Likert scale.

CONCLUSION

The final 10-item Likert scale offers a good degree of validity and reliability for determining the health education needs of individuals living with diabetes. The two Likert scale components (general information on diabetes, and diabetes and travel) and their contributing items were identified from the questionnaire, which is standardized and helpful in both practice and research, in order to ascertain patients' needs and develop structured health education programs. The component "General information about diabetes" exhibited significant associations with the following items: diabetes risk factors and prevention; common oral agents for treating hypoglycemia; HbA1c (glycosylated hemoglobin) and normal blood glucose levels; and acute problems related to diabetes, such as hypoglycemia and diabetic ketoacidosis. On the other hand, diabetes and fasting; chronic complications of diabetes; and the significance of the yearly eye screening were the Likert scale items that contributed more to Component 2 (diabetes and travel).

Glucagon-like peptide-1 and impaired counterregulatory responses to hypoglycemia in type 1 diabetes

This letter comments on a study by Jin et al, published recently in the World Journal of Diabetes. Hypoglycemia is a significant complication of diabetes, with primary defense mechanisms involving the stimulation of glucagon secretion in α-cells and the inhibition of insulin secretion in pancreatic β-cells, which are often compromised in type 1 diabetes mellitus (T1DM) and advanced type 2 diabetes mellitus. Recurrent hypoglycemia predisposes the development of impaired hypoglycemia awareness, a condition underpinned by complex pathophysiological processes, encompassing central nervous system adaptations and several hormonal interactions, including a potential role for glucagon-like peptide-1 (GLP-1) in paracrine and endocrine vias. Experimental evidence indicates that GLP-1 may impair hypoglycemic counterregulation by disrupting the sympathoadrenal system and promoting somatostatin release in pancreatic δ-cells, which inhibits glucagon secretion from neighboring α-cells. However, current trials evaluating GLP-1 receptor agonists (GLP-1 RAs) in T1DM patients have shown promising benefits in reducing insulin requirements and body weight, without increasing the risk of hypoglycemia. Further research is essential to elucidate the specific roles of GLP-1 and GLP-1 RAs in modulating glucagon secretion and the sympathetic-adrenal reflex, and their impact on hypoglycemia unawareness in T1DM patients.

Pharmacotherapy of type 1 diabetes - part 1: yesterday

INTRODUCTION

Type 1 diabetes is a unique autoimmune attack on the β cell of the pancreatic islet resulting in progressive destruction of these cells and as a result the ability of the body to maintain insulin production. The consequences of insulin deficiency are very severe, and the disease was fatal prior to the ability to extract insulin from animal pancreas in 1921. We review progress in the treatment of childhood type 1 diabetes over the past 100 years.

AREAS COVERED

We used PubMed and standard search engines to search for the evolution of diagnosis and treatment of type 1 diabetes.

EXPERT OPINION

Insulin replacement proved lifesaving for children afflicted with type 1 diabetes. However, it was observed that these children suffered from microvascular and large vessel disease. The Diabetes Control and Complications Trial (DCCT) with its extension Epidemiology of Diabetes Interventions and Complications Trial (EDIC) proved that control of blood glucose as close to normal as possible could prevent these diabetes-related conditions. Many formuations of insulin with varying onset and duration of action have been developed; yet normalization of glucose levels is difficult due to hypoglycemic events. There is continued progress toward that goal.

Exploring the potential of deep learning models integrating transformer and LSTM in predicting blood glucose levels for T1D patients

Objective

Diabetes mellitus is a chronic condition that requires constant blood glucose monitoring to prevent serious health risks. Accurate blood glucose prediction is essential for managing glucose fluctuations and reducing the risk of hypo- and hyperglycemic events. However, existing models often face limitations in prediction horizon and accuracy. This study aims to develop a hybrid deep learning model combining Transformer and Long Short-Term Memory (LSTM) networks to improve prediction accuracy and extend the prediction horizon, using personalized patient information and continuous glucose monitoring data to support better real-time diabetes management.

Methods

In this study, we propose a hybrid deep learning model combining Transformer and LSTM networks to predict blood glucose levels for up to 120 min. The Transformer Encoder captures long-range dependencies, while the LSTM models short-term patterns. To improve feature extraction, we integrate Bidirectional LSTM and Transformer Encoder layers at multiple stages. We also use positional encoding, dropout layers, and a sliding window technique to reduce noise and manage temporal dependencies. Richer features, including meal composition and insulin dosage, are incorporated to enhance prediction accuracy. The model's performance is validated using real-world clinical data and error grid analysis.

Results

On clinical data, the model achieved root mean square error/mean absolute error of 10.157/6.377 (30-min), 10.645/6.417 (60-min), 13.537/7.283 (90-min), and 13.986/6.986 (120-min). On simulated data, the results were 1.793/1.376 (15-min), 2.049/1.311 (30-min), and 3.477/1.668 (60-min). Clark Grid Analysis showed that over 96% of predictions fell within the clinical safety zone up to 120 min, confirming its clinical feasibility.

Conclusion

This study demonstrates that the combined Transformer and LSTM model can effectively predict blood glucose concentration in type 1 diabetes patients with high accuracy and clinical applicability. The model provides a promising solution for personalized blood glucose management, contributing to the advancement of artificial intelligence technology in diabetes care.

Intraoperative hypoglycemia among adults with intraoperative glucose measurements: a cross-sectional multicentre retrospective cohort study

PURPOSE

Intraoperative hypoglycemia is presumed to be rare, but generalizable multicentre incidence and risk factor data for adult patients are lacking. We used a multicentre registry to characterize adults with intraoperative hypoglycemia and hypothesized that intraoperative insulin administration would be associated with hypoglycemia.

METHODS

We conducted a cross-sectional retrospective multicentre cohort study. We searched the Multicenter Perioperative Outcomes Group registry to identify adult patients with intraoperative hypoglycemia (glucose < 3.3 mmol·L-1 [< 60 mg·dL-1]) from 1 January 2015 to 31 December 2019. We evaluated characteristics of patients with intraoperative glucose measurements and with intraoperative hypoglycemia.

RESULTS

Of 516,045 patients with intraoperative glucose measurements, 3,900 (0.76%) had intraoperative hypoglycemia. Diabetes mellitus and chronic kidney disease were more common in the cohort with intraoperative hypoglycemia. The odds of intraoperative hypoglycemia were higher for the youngest age category (18-30 yr) compared with the odds for every age category above 40 yr (odds ratio [OR], 1.57-3.18; P < 0.001), and were higher for underweight or normal weight patients compared with patients with obesity (OR, 1.48-2.53; P < 0.001). Parenteral nutrition was associated with lower odds of hypoglycemia (OR, 0.23; 95% confidence interval [CI], 0.11 to 0.47; P < 0.001). Intraoperative insulin use was not associated with hypoglycemia (OR, 0.996; 95% CI, 0.91 to 1.09; P = 0.93).

CONCLUSION

In this large cross-sectional retrospective multicentre cohort study, intraoperative hypoglycemia was a rare event. Intraoperative insulin use was not associated with hypoglycemia.

Association of Glycemic Variability with Outcomes in Non-diabetic Sepsis Patients: A Prospective Observational Study

Background

Glycemic variability (GV) is the third domain of sepsis-induced dysglycemia, after hyperglycemia and hypoglycemia, potentially leading to adverse outcomes. This study analyzed the association of GV with in-hospital mortality and length of stay (LOS) in non-diabetic sepsis patients.

Materials and methods

In this prospective observational study, non-diabetic sepsis patients were followed till day 14 of hospital stay, and blood glucose levels were assessed by finger-prick method (seven times per day) daily; clinico-laboratory and GV parameters [standard deviation (SD), coefficient of variation (CV), mean amplitude of glycemic excursion (MAGE)] were assessed on days 1, 3, 5, 7, 10, and 14 of admission.

Results

Two hundred thirteen patients were screened and 80 (mean age 45.6 ± 15.37 years; 50% men) were included in the final analysis. Patients with in-hospital mortality had significantly higher GV when compared to patients without in-hospital mortality [SD: 37.57 vs 25.21, adjusted odds ratio (aOR) 1.13, 95% confidence interval (CI) 1.02-1.24, p = 0.013; CV: 24.91 vs 16.88, aOR 1.19, 95% CI: 1.03-1.38, p = 0.016; MAGE: 73.13 vs 48.03, aOR 1.05, 95% CI: 1.01-1.11, p = 0.014], independent of illness severity (APACHE II), mean blood glucose and hypoglycemia on multivariate regression analysis. There was no significant correlation between GV and LOS. Multivariate analysis showed a significant independent association between CV and ventilator requirement (aOR 1.15, 95% CI: 1.03-1.29, p = 0.017) and between SD and need for renal replacement therapy (aOR 1.04, 95% CI: 1-1.09, p = 0.044).

Conclusion

This study demonstrated that GV is independently associated with increased in-hospital mortality in non-diabetic sepsis patients. Further studies are required to investigate whether targeting lower GV in septic patients would translate to better outcomes.

Clinical significance

Glycemic variability in sepsis is controversial, with discordant results and a paucity of studies on the Indian population in the literature. Despite blood sugar monitoring being routinely done in sepsis patients, GV is rarely measured and the results of our study indicate that it may be worthwhile to estimate GV in sepsis. This may aid in identifying a subset of patients with increased mortality risk, who may benefit from intensive glucose monitoring and modification of insulin regimen.

How to cite this article

Prakash P, Sethi P, Vikram N, Khan M, Gupta Y, Jadon RS, et al. Association of Glycemic Variability with Outcomes in Non-diabetic Sepsis Patients: A Prospective Observational Study. Indian J Crit Care Med 2025;29(1):27-35.

Effects of Diabetes and Hyperlipidemia in Physiological Conditions - A Review

BACKGROUND

Diabetes mellitus (DM) is an autoimmune manifestation defined by persistent hyperglycemia and alterations in protein, fatty substances, and carbohydrate metabolism as an effect of problems with the secretion of insulin action or both. Manifestations include thirst, blurred eyesight, weight loss, and ketoacidosis, which can majorly lead to coma. There are different types of diabetes according to class or by cellular level. They are interrelated with hyperlipidemia as they are involved in the metabolism and regulation of physiological factors. Most parameters are seen at cellular or humoral levels, yet the underlying concern remains the same.

OBJECTIVE

To create a systematic correlation between the disease and locate the exact mechanism and receptors responsible for it. So, this article covers a proper way to resolve the conditions and their manifestation through literacy and diagrammatic.

CONCLUSION

Hence, this will be an insight for many scholars to understand the exact mechanism involved in the process.

Role of intestinal glucagon-like peptide-1 in impaired counter-regulatory responses to hypoglycemia

Patients with type 1 diabetes mellitus (T1DM) experience multiple episodes of hypoglycemia, resulting in dysfunctional counter-regulatory responses with time. The recent experimental study by Jin et al explored the role of intestinal glucagon-like peptide-1 (GLP-1) in impaired counter-regulatory responses to hypoglycemia. They identified intestinal GLP-1 along with GLP-1 receptor (GLP-1R) as the new key players linked with impaired counter-regulatory responses to hypoglycemia in type 1 diabetic mice. They also demonstrated that excessive expression of GLP-1 and GLP-1R was associated with attenuated sympathoadrenal responses and decreased glucagon secretion. The study has enormous clinical relevance as defective counter regulation and hypoglycemia unawareness negatively impacts the intensive glycemic management approach in this group of patients. However, the physiological processes must be validated in dedicated human studies to comprehensively understand the pathophysiology of this complex relationship, and to clarify the true extent of impaired hypoglycemia counter regulation by intestinal GLP-1. For now, following the results of the index study and other similar studies, GLP-1 analogues usage in T1DM must be carefully monitored, as there is an inherent risk of worsening the already impaired counter-regulatory responses in these patients. Further studies in the future could identify other key players involved in this clinically relevant interaction.

Development and Validation of a Nocturnal Hypoglycaemia Risk Model for Patients With Type 2 Diabetes Mellitus

AIM

To develop and test different machine learning algorithms for predicting nocturnal hypoglycaemia in patients with type 2 diabetes mellitus.

DESIGN

A retrospective study.

METHODS

We collected data from dynamic blood glucose monitoring of patients with T2DM admitted to the Department of Endocrinology and Metabolism at a hospital in Shanghai, China, from November 2020 to January 2022. Patients undergone the continuous glucose monitoring (CGM) for ≥ 24 h were included in this study. Logistic regression, random forest and light gradient boosting machine algorithms were employed, and the models were validated and compared using AUC, accuracy, specificity, recall rate, precision, F1 score and the Kolmogorov-Smirnov test.

RESULTS

A total of 4015 continuous glucose-monitoring data points from 440 patients were included, and 28 variables were selected to build the risk prediction model. The 440 patients had an average age of 62.7 years. Approximately 48.2% of the patients were female and 51.8% were male. Nocturnal hypoglycaemia appeared in 573 (14.30%) of 4015 continuous glucose monitoring data. The light gradient boosting machine model demonstrated the highest predictive performances: AUC (0.869), specificity (0.802), accuracy (0.801), precision (0.409), recall rate (0.797), F1 score (0.255) and Kolmogorov (0.603). The selected predictive factors included time below the target glucose range, duration of diabetes, insulin use before bed and dynamic blood glucose monitoring parameters from the previous day.

PATIENT OR PUBLIC CONTRIBUTION

No Patient or Public Contribution.

Integrating network pharmacology and experimental validation to decipher the pharmacological mechanism of DXXK in treating diabetic kidney injury

Diabetes mellitus (DM) is a chronic metabolic disease that is highly susceptible to kidney injury. Di'ao XinXueKang capsules (DXXK) is a novel Chinese herbal medicine that has been used in clinical trials for the therapy of DM and kidney disease, but the underlying pharmacological mechanism remains unclear. This study aims to integrate network pharmacology, molecular docking and in vivo experiments to explore the potential mechanisms of DXXK in the treatment of diabetic kidney injury. The chemical constituents of DXXK were extracted from the ETCM and Batman-TCM databases, and then evaluated for their pharmacological activity via the Swiss ADME platform. Multiple disease databases were searched and integrated for DM-related targets. Overlapping targets were then collected to construct a protein-protein interaction (PPI) network. KEGG and GO enrichment analyses were performed based on the Metascape database, and molecular docking was performed using AutoDock Vina software. The main components in DXXK were analyzed by HPLC. The results of network pharmacology and molecular docking were validated in an animal model of DM induced by the combination of a high-fat diet (HFD) and streptozotocin (STZ). We screened and obtained 7 ingredients and identified dioscin, protodioscin, and pseudoprotodioscin as the major components of DXXK by HPLC. A total of 2,216 DM-related pathogenic genes were obtained from DrugBank, GeneCards, OMIM, and DisGeNET databases. KEGG and GO enrichment analyses indicated that the TGF-beta signaling pathway is a critical pathway associated with DM therapy. Molecular docking revealed that the ingredients in DXXK bind to the pivotal targets TGFβ1, Smad2, and Smad3. In diabetic mice, we found that DXXK alleviated diabetic symptoms, lowered blood glucose, improved insulin tolerance, and modulated lipid metabolism. Furthermore, DXXK attenuated renal lesions and fibrosis by downregulating TGFβ1, Smad2, and Smad3. Collectively, our results suggest that DXXK has the potential to regulate glucolipid metabolism in DM, and it may serve as a viable therapeutic option for renoprotection by inhibiting of the TGF-β1/Smad2/3 pathway.

Machine Learning-Based Plasma Metabolomics in Liraglutide-Treated Type 2 Diabetes Mellitus Patients and Diet-Induced Obese Mice

Liraglutide, a glucagon-like peptide-1 receptor agonist, is effective in the treatment of type 2 diabetes mellitus (T2DM) and obesity. Despite its benefits, including improved glycemic control and weight loss, the common metabolic changes induced by liraglutide and correlations between those in rodents and humans remain unknown. Here, we used advanced machine learning techniques to analyze the plasma metabolomic data in diet-induced obese (DIO) mice and patients with T2DM treated with liraglutide. Among the machine learning models, Support Vector Machine was the most suitable for DIO mice, and Gradient Boosting was the most suitable for patients with T2DM. Through the cross-evaluation of machine learning models, we found that liraglutide promotes metabolic shifts and interspecies correlations in these shifts between DIO mice and patients with T2DM. Our comparative analysis helped identify metabolic correlations influenced by liraglutide between humans and rodents and may guide future therapeutic strategies for T2DM and obesity.

The Intersection between Frailty, Diabetes, and Hypertension: The Critical Role of Community Geriatricians and Pharmacists in Deprescribing

Background: Frailty is a clinical syndrome prevalent among the elderly, characterised by a decline in physiological reserves and increased susceptibility to stressors, resulting in higher morbidity and mortality. Diabetes and hypertension are common in frail older individuals, often leading to polypharmacy. In this narrative review, we aimed to evaluate the relationship between frailty, diabetes, and hypertension and to identify effective management strategies and future research directions. Methods: This narrative review was conducted using the Scopus, Medline, PubMed, Cochrane Library, and Google Scholar databases. Results: Frailty significantly impacts the management and prognosis of diabetes and hypertension, which, in turn, affects the progression of frailty. Managing these conditions often involves multiple drugs to achieve strict glycaemic control and blood pressure targets, leading to polypharmacy and associated morbidities, including orthostatic hypotension, falls, fractures, hypoglycaemia, and reduced medication adherence. Identifying frailty and implementing strategies like deprescribing can mitigate the adverse effects of polypharmacy and improve outcomes and quality of life. Despite the availability of effective tools for identifying frailty, many frail individuals continue to be exposed to complex treatment regimens for diabetes and hypertension, leading to increased hospital admissions, morbidity, and mortality. Conclusions: Managing diabetes and hypertension in the frail ageing population requires a multidisciplinary approach involving hospital and community geriatricians and pharmacists. This is important due to the lack of sufficient clinical trials dedicated to diabetes and hypertension in the context of frailty. Future large population studies are needed to assess the best approaches for managing diabetes and hypertension in frail individuals.

Associations Between Hypoglycemia Awareness Status and Symptoms of Hypoglycemia Among Adults with Type 1 or Insulin-Treated Type 2 Diabetes Using the Hypo-METRICS Smartphone Application

Introduction: This study examined associations between hypoglycemia awareness status and hypoglycemia symptoms reported in real-time using the novel Hypoglycaemia-MEasurement, ThResholds and ImpaCtS (Hypo-METRICS) smartphone application (app) among adults with insulin-treated type 1 (T1D) or type 2 diabetes (T2D). Methods: Adults who experienced at least one hypoglycemic episode in the previous 3 months were recruited to the Hypo-METRICS study. They prospectively reported hypoglycemia episodes using the app for 10 weeks. Any of eight hypoglycemia symptoms were considered present if intensity was rated between "A little bit" to "Very much" and absent if rated "Not at all." Associations between hypoglycemia awareness (as defined by Gold score) and hypoglycemia symptoms were modeled using mixed-effects binary logistic regression, adjusting for glucose monitoring method and diabetes duration. Results: Of 531 participants (48% T1D, 52% T2D), 45% were women, 91% white, and 59% used Flash or continuous glucose monitoring. Impaired awareness of hypoglycemia (IAH) was associated with lower odds of reporting autonomic symptoms than normal awareness of hypoglycemia (NAH) (T1D odds ratio [OR] 0.43 [95% confidence interval {CI} 0.25-0.73], P = 0.002); T2D OR 0.51 [95% CI 0.26-0.99], P = 0.048), with no differences in neuroglycopenic symptoms. In T1D, relative to NAH, IAH was associated with higher odds of reporting autonomic symptoms at a glucose concentration <54 than >70 mg/dL (OR 2.18 [95% CI 1.21-3.94], P = 0.010). Conclusion: The Hypo-METRICS app is sensitive to differences in hypoglycemia symptoms according to hypoglycemia awareness in both diabetes types. Given its high ecological validity and low recall bias, the app may be a useful tool in research and clinical settings. The clinical trial registration number is NCT04304963.

Differential associations of risk factors with severe and non-severe hypoglycaemia: the Hypoglycaemia Assessment Tool prospective observational study in people with insulin-treated type 1 diabetes and type 2 diabetes

AIM

To assess the differential association of risk factors with severe and non-severe hypoglycaemia.

MATERIALS AND METHODS

The Hypoglycaemia Assessment Tool study evaluated the risk of hypoglycaemia over a 4-week period in patients with type 1 diabetes (T1D) and type 2 diabetes (T2D) on insulin in 24 countries. Negative binomial regressions were applied to examine the associations of several risk factors with severe and non-severe hypoglycaemia.

RESULTS

The median age was 41 years in 5949 patients with T1D and 62 years in 12 914 patients with T2D. The 4-week rates of non-severe hypoglycaemic were 5.57 and 1.40 episodes per person in T1D and T2D, respectively; the corresponding rates for severe hypoglycaemia were 0.94 and 0.30. The excess risk was 42% higher for severe than non-severe hypoglycaemia in females versus males with T2D; 27% higher in patients with T2D with versus without a continuous glucose monitoring (CGM); and 47% lower in patients with T1D with versus without an insulin pump. The excess risk also differed across geographical areas and was marginally lower for severe than non-severe hypoglycaemia for higher values of HbA1c in patients with T2D. Associations with severity of hypoglycaemia were not different for age, diabetes and insulin therapy duration, previous hypoglycaemic episodes and insulin regimen.

CONCLUSIONS

The risk of severe versus non-severe hypoglycaemia differs in patients with T1D and T2D; sex, the use of a CGM and insulin pump, and geographical areas were differently associated with one type of hypoglycaemia than the other.

A self-powered and supercapacitive microneedle continuous glucose monitoring system with a wide range of glucose detection capabilities

Continuous detection of sudden changes in blood glucose is essential for individuals with diabetes who have difficulty in maintaining optimal control of their blood glucose levels. Hypoglycemic shock or a hyperglycemic crisis are likely to occurs in patients with diabetes and poses a significant threat to their lives. Currently, commercial continuous glucose monitoring (CGM) has limits in the glucose concentration detection range, which is 40-500 mg/dL, making it difficult to prevent the risk of hyperglycemic shock. In addition, current CGMs are invasive, cause pain and irritation during usage, and expensive. In this research, we overcome these limitations by introducing a novel mechanism to detect glucose concentration using supercapacitors. The developed CGM, which is self-powered and minimally invasive due to the use of microneedles, can detect a wider range of glucose concentrations than commercial sensors. In addition, efficacy and stability were proven through in vitro and in vivo experiments. Thus, this self-powered, microneedle and supercapacitive-type CGM can potentially prevent both hypoglycemic and complications of hyperglycemia without pain and with less power consumption than current commercial sensors.

Effect of recurrent severe insulin-induced hypoglycemia on the cognitive function and brain oxidative status in the rats

BACKGROUND

Episodes of recurrent or severe hypoglycemia can occur in patients with diabetes mellitus, insulinoma, neonatal hypoglycemia, and medication errors. However, little is known about the short-term and long-term effects of repeated episodes of acute severe hypoglycemia on the brain, particularly in relation to hippocampal damage and cognitive dysfunction.

METHODS

Thirty-six wistar rats were randomly assigned to either the experimental or control group. The rats were exposed to severe hypoglycemia, and assessments were conducted to evaluate oxidative stress in brain tissue, cognitive function using the Morris water maze test, as well as histopathology and immunohistochemistry studies. The clinical and histopathological evaluations were conducted in the short-term and long-term.

RESULTS

The mortality rate attributed to hypoglycemia was 34%, occurring either during hypoglycemia or within 24 h after induction. Out of the 14 rats monitored for 7 to 90 days following severe/recurrent hypoglycemia, all exhibited clinical symptoms, which mostly resolved within three days after the last hypoglycemic episode, except for three rats. Despite the decrease in catalase activity in the brain, the total antioxidant capacity following severe insulin-induced hypoglycemia increased. The histopathology findings revealed that the severity of the hippocampal damage was higher compared to the brain cortex 90 days after hypoglycemia. Memory impairments with neuron loss particularly pronounced in the dentate gyrus region of the hippocampus were observed in the rats with severe hypoglycemia. Additionally, there was an increase in reactive astrocytes indicated by GFAP immunoreactivity in the brain cortex and hippocampus.

CONCLUSION

Recurrent episodes of severe hypoglycemia can lead to high mortality rates, memory impairments, and severe histopathological changes in the brain. While many histopathological and clinical changes improved after three months, it seems that the vulnerability of the hippocampus and the development of sustained changes in the hippocampus were greater and more severe compared to the brain cortex following severe and recurrent hypoglycemia. Furthermore, it does not appear that oxidative stress plays a central role in neuronal damage following severe insulin-induced hypoglycemia. Further research is necessary to assess the consequences of repeated hypoglycemic episodes on sustained damage across various brain regions.

Development and Validation of a Machine Learning Model to Predict Weekly Risk of Hypoglycemia in Patients with Type 1 Diabetes Based on Continuous Glucose Monitoring

Aim: The aim of this study was to develop and validate a prediction model based on continuous glucose monitoring (CGM) data to identify a week-to-week risk profile of excessive hypoglycemia. Methods: We analyzed, trained, and internally tested two prediction models using CGM data from 205 type 1 diabetes patients with long-term CGM monitoring. A binary classification approach (XGBoost) combined with feature engineering deployed on the CGM signals was utilized to predict excessive hypoglycemia risk defined by two targets (time below range [TBR] >4% and the upper TBR 90th percentile limit) of TBR the following week. The models were validated in two independent cohorts with a total of 253 additional patients. Results: A total of 61,470 weeks of CGM data were included in the analysis. The XGBoost models had an area under the receiver operating characteristic curve (ROC-AUC) of 0.83-0.87 (95% confidence interval; 0.83-0.88) in the test dataset. The external validation showed ROC-AUCs of 0.81-0.90. The most discriminative features included the low blood glucose index, the glycemic risk assessment diabetes equation (GRADE), hypoglycemia, the TBR, waveform length, the coefficient of variation and mean glucose during the previous week. This highlights that the pattern of hypoglycemia combined with glucose variability during the past week contains information on the risk of future hypoglycemia. Conclusion: Prediction models based on real-world CGM data can be used to predict the risk of hypoglycemia in the forthcoming week. The models showed good performance in both the internal and external validation cohorts.

Safety of User-Initiated Intensification of Insulin Delivery Using Cambridge Hybrid Closed-Loop Algorithm

OBJECTIVE

Many hybrid closed-loop (HCL) systems struggle to manage unusually high glucose levels as experienced with intercurrent illness or pre-menstrually. Manual correction boluses may be needed, increasing hypoglycemia risk with overcorrection. The Cambridge HCL system includes a user-initiated algorithm intensification mode ("Boost"), activation of which increases automated insulin delivery by approximately 35%, while remaining glucose-responsive. In this analysis, we assessed the safety of "Boost" mode.

METHODS

We retrospectively analyzed data from closed-loop studies involving young children (1-7 years, n = 24), children and adolescents (10-17 years, n = 19), adults (≥24 years, n = 13), and older adults (≥60 years, n = 20) with type 1 diabetes. Outcomes were calculated per participant for days with ≥30 minutes of "Boost" use versus days with no "Boost" use. Participants with <10 "Boost" days were excluded. The main outcome was time spent in hypoglycemia <70 and <54 mg/dL.

RESULTS

Eight weeks of data for 76 participants were analyzed. There was no difference in time spent <70 and <54 mg/dL between "Boost" days and "non-Boost" days; mean difference: -0.10% (95% confidence interval [CI] -0.28 to 0.07; P = .249) time <70 mg/dL, and 0.03 (-0.04 to 0.09; P = .416) time < 54 mg/dL. Time in significant hyperglycemia >300 mg/dL was 1.39 percentage points (1.01 to 1.77; P < .001) higher on "Boost" days, with higher mean glucose and lower time in target range (P < .001).

CONCLUSIONS

Use of an algorithm intensification mode in HCL therapy is safe across all age groups with type 1 diabetes. The higher time in hyperglycemia observed on "Boost" days suggests that users are more likely to use algorithm intensification on days with extreme hyperglycemic excursions.

A strategy based on integer programming for optimal dosing and timing of preventive hypoglycemic treatments in type 1 diabetes management

BACKGROUND AND OBJECTIVES

One of the major problems related to type 1 diabetes (T1D) management is hypoglycemia, a condition characterized by low blood glucose levels and responsible for reduced quality of life and increased mortality. Fast-acting carbohydrates, also known as hypoglycemic treatments (HT), can counteract this event. In the literature, dosage and timing of HT are usually based on heuristic rules. In the present work, we propose an algorithm for mitigating hypoglycemia by suggesting preventive HT consumption, with dosages and timing determined by solving an optimization problem.

METHODS

By leveraging integer programming and linear inequality constraints, the algorithm can bind the amount of suggested carbohydrates to standardized quantities (i.e., those available in "off-the-shelf" HT) and the minimal distance between consecutive suggestions (to reduce the nuisance for patients).

RESULTS

The proposed method was tested in silico and compared with competitor algorithms using the UVa/Padova T1D simulator. At the cost of a slight increase of HT consumed per day, the proposed algorithm produces the lowest median and interquartile range of the time spent in hypoglycemia, with a statistically significant improvement over most competitor algorithms. Also, the average number of hypoglycemic events per day is reduced to 0 in median.

CONCLUSIONS

Thanks to its positive performances and reduced computational burden, the proposed algorithm could be a candidate tool for integration in a DSS aimed at improving T1D management.

Sequential Dearomatization/Rearrangement of Quinazoline-Derived Azomethine Imines for the Synthesis of Nitrogen-Rich Three-Dimensional Cage-Like Molecules

A sequential dearomatization/rearrangement reaction between quinazoline-derived azomethine imines and crotonate sulfonium salts has been developed to provide a series of three-dimensional cage-like molecules. The reaction involves two dearomatizations, two cyclizations, and two C-C bond and three C-N bond formations in one step. The new transformation has a broad substrate scope, does not require any added reagents, and proceeds under room temperature in a short time. A mechanistic rationale for the sequential dearomatization/rearrangement is also presented. Furthermore, the synthetic compounds are evaluated for their glucose control effect. Compounds 3aa and 3aj were found to be hyperglycemic, which might be lead compounds for treating hypoglycemia.

Counterregulatory hormone and symptom responses to hypoglycaemia in people with type 1 diabetes, insulin-treated type 2 diabetes or without diabetes: the Hypo-RESOLVE hypoglycaemic clamp study

AIM

The sympathetic nervous and hormonal counterregulatory responses to hypoglycaemia differ between people with type 1 and type 2 diabetes and may change along the course of diabetes, but have not been directly compared. We aimed to compare counterregulatory hormone and symptom responses to hypoglycaemia between people with type 1 diabetes, insulin-treated type 2 diabetes and controls without diabetes, using a standardised hyperinsulinaemic-hypoglycaemic clamp.

MATERIALS

We included 47 people with type 1 diabetes, 15 with insulin-treated type 2 diabetes, and 32 controls without diabetes. Controls were matched according to age and sex to the people with type 1 diabetes or with type 2 diabetes. All participants underwent a hyperinsulinaemic-euglycaemic-(5.2 ± 0.4 mmol/L)-hypoglycaemic-(2.8 ± 0.13 mmol/L)-clamp.

RESULTS

The glucagon response was lower in people with type 1 diabetes (9.4 ± 0.8 pmol/L, 8.0 [7.0-10.0]) compared to type 2 diabetes (23.7 ± 3.7 pmol/L, 18.0 [12.0-28.0], p < 0.001) and controls (30.6 ± 4.7, 25.5 [17.8-35.8] pmol/L, p < 0.001). The adrenaline response was lower in type 1 diabetes (1.7 ± 0.2, 1.6 [1.3-5.2] nmol/L) compared to type 2 diabetes (3.4 ± 0.7, 2.6 [1.3-5.2] nmol/L, p = 0.001) and controls (2.7 ± 0.4, 2.8 [1.4-3.9] nmol/L, p = 0.012). Growth hormone was lower in people with type 2 diabetes than in type 1 diabetes, at baseline (3.4 ± 1.6 vs 7.7 ± 1.3 mU/L, p = 0.042) and during hypoglycaemia (24.7 ± 7.1 vs 62.4 ± 5.8 mU/L, p = 0.001). People with 1 diabetes had lower overall symptom responses than people with type 2 diabetes (45.3 ± 2.7 vs 58.7 ± 6.4, p = 0.018), driven by a lower neuroglycopenic score (27.4 ± 1.8 vs 36.7 ± 4.2, p = 0.012).

CONCLUSION

Acute counterregulatory hormone and symptom responses to experimental hypoglycaemia are lower in people with type 1 diabetes than in those with long-standing insulin-treated type 2 diabetes and controls.

Medical, pharmaceutical, and nutritional applications of 3D-printing technology in diabetes

AIMS

Despite numerous studies covering the various features of three-dimensional printing (3D printing) technology, and its applications in food science and disease treatment, no study has yet been conducted to investigate applying 3D printing in diabetes. Therefore, the present study centers on the utilization and impact of 3D printing technology in relation to the nutritional, pharmaceutical, and medicinal facets of diabetes management. It highlights the latest advancements, and challenges in this field.

METHODS

In this review, the articles focusing on the application and effect of 3D printing technology on medical, pharmaceutical, and nutritional aspects of diabetes management were collected from different databases.

RESULT

High precision of 3D printing in the placement of cells led to accurate anatomic control, and the possibility of bio-printing pancreas and β-cells. Transdermal drug delivery via 3D-printed microneedle (MN) patches was beneficial for the management of diabetes disease. 3D printing supported personalized medicine for Diabetes Mellitus (DM). For instance, it made it possible for pharmaceutical companies to manufacture unique doses of medications for every diabetic patient. Moreover, 3D printing allowed the food industry to produce high-fiber and sugar-free products for the individuals with DM.

CONCLUSIONS

In summary, applying 3D printing technology for diabetes management is in its early stages, and needs to be matured and developed to be safely used for humans. However, its rapid progress in recent years showed a bright future for the treatment of diabetes.

Hypoglycemia Unawareness-A Review on Pathophysiology and Clinical Implications

Hypoglycemia is a particular problem in people with diabetes while it can also occur in other clinical circumstances. Hypoglycemia unawareness describes a condition in which autonomic and neuroglycopenic symptoms of hypoglycemia decrease and hence are hardly perceivable. A failure to recognize hypoglycemia in time can lead to unconsciousness, seizure, and even death. The risk factors include intensive glycemic control, prior episodes of severe hypoglycemia, long duration of diabetes, alcohol consumption, exercise, renal failure, and sepsis. The pathophysiological mechanisms are manifold, but mainly concern altered brain glucose sensing, cerebral adaptations, and an impaired hormonal counterregulation with an attenuated release of glucagon, epinephrine, growth hormone, and other hormones, as well as impaired autonomous and neuroglycopenic symptoms. Physiologically, this counterregulatory response causes blood glucose levels to rise. The impaired hormonal counterregulatory response to recurrent hypoglycemia can lead to a vicious cycle of frequent and poorly recognized hypoglycemic episodes. There is a shift in glycemic threshold to trigger hormonal counterregulation, resulting in hypoglycemia-associated autonomic failure and leading to the clinical syndrome of hypoglycemia unawareness. This clinical syndrome represents a particularly great challenge in diabetes treatment and, thus, prevention of hypoglycemia is crucial in diabetes management. This mini-review provides an overview of hypoglycemia and the associated severe complication of impaired hypoglycemia awareness and its symptoms, pathophysiology, risk factors, consequences, as well as therapeutic strategies.

Role of the Adrenal Medulla in Hypoglycaemia-Associated Autonomic Failure-A Diabetic Perspective

Hypoglycaemia-associated autonomic failure (HAAF) is characterised by an impairment in adrenal medullary and neurogenic symptom responses following episodes of recurrent hypoglycaemia. Here, we review the status quo of research related to the regulatory mechanisms of the adrenal medulla in its response to single and recurrent hypoglycaemia in both diabetic and non-diabetic subjects with particular focus given to catecholamine synthesis, enzymatic activity, and the impact of adrenal medullary peptides. Short-term post-transcriptional modifications, particularly phosphorylation at specific residues of tyrosine hydroxylase (TH), play a key role in the regulation of catecholamine synthesis. While the effects of recurrent hypoglycaemia on catecholamine synthetic enzymes remain inconsistent, long-term changes in TH protein expression suggest species-specific responses. Adrenomedullary peptides such as neuropeptide Y (NPY), galanin, and proenkephalin exhibit altered gene and protein expression in response to hypoglycaemia, suggesting a potential role in the modulation of catecholamine secretion. Of note is NPY, since its antagonism has been shown to prevent reductions in TH protein expression. This review highlights the need for further investigation into the molecular mechanisms involved in the adrenal medullary response to hypoglycaemia. Despite advancements in our understanding of HAAF in non-diabetic rodents, a reliable diabetic rodent model of HAAF remains a challenge.

Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial

BACKGROUND

Hypoglycemia is a frequent and acute complication in type 1 diabetes mellitus (T1DM) and is associated with a higher risk of car mishaps. Currently, hypoglycemia can be detected and signaled through flash glucose monitoring or continuous glucose monitoring devices, which require manual and visual interaction, thereby removing the focus of attention from the driving task. Hypoglycemia causes a decrease in attention, thereby challenging the safety of using such devices behind the wheel. Here, we present an investigation of a hands-free technology-a voice warning that can potentially be delivered via an in-vehicle voice assistant.

OBJECTIVE

This study aims to investigate the feasibility of an in-vehicle voice warning for hypoglycemia, evaluating both its effectiveness and user perception.

METHODS

We designed a voice warning and evaluated it in 3 studies. In all studies, participants received a voice warning while driving. Study 0 (n=10) assessed the feasibility of using a voice warning with healthy participants driving in a simulator. Study 1 (n=18) assessed the voice warning in participants with T1DM. Study 2 (n=20) assessed the voice warning in participants with T1DM undergoing hypoglycemia while driving in a real car. We measured participants' self-reported perception of the voice warning (with a user experience scale in study 0 and with acceptance, alliance, and trust scales in studies 1 and 2) and compliance behavior (whether they stopped the car and reaction time). In addition, we assessed technology affinity and collected the participants' verbal feedback.

RESULTS

Technology affinity was similar across studies and approximately 70% of the maximal value. Perception measure of the voice warning was approximately 62% to 78% in the simulated driving and 34% to 56% in real-world driving. Perception correlated with technology affinity on specific constructs (eg, Affinity for Technology Interaction score and intention to use, optimism and performance expectancy, behavioral intention, Session Alliance Inventory score, innovativeness and hedonic motivation, and negative correlations between discomfort and behavioral intention and discomfort and competence trust; all P<.05). Compliance was 100% in all studies, whereas reaction time was higher in study 1 (mean 23, SD 5.2 seconds) than in study 0 (mean 12.6, SD 5.7 seconds) and study 2 (mean 14.6, SD 4.3 seconds). Finally, verbal feedback showed that the participants preferred the voice warning to be less verbose and interactive.

CONCLUSIONS

This is the first study to investigate the feasibility of an in-vehicle voice warning for hypoglycemia. Drivers find such an implementation useful and effective in a simulated environment, but improvements are needed in the real-world driving context. This study is a kickoff for the use of in-vehicle voice assistants for digital health interventions.

A Propolis-Derived Small Molecule Tectochrysin Ameliorates Type 2 Diabetes in Mice by Activating Insulin Receptor β

SCOPE

Propolis has been found to decrease glucose levels and increase insulin sensitivity in type 2 diabetes. However, the active ingredient responsible for these effects and its regulating mechanism are not fully understood.

METHODS AND RESULTS

To address this, molecular docking screening is used to screen the effective hypoglycemic ingredient in propolis and found that tectochrysin (TEC) has a high affinity to the insulin receptor (IR), highlighting its potential for glycemic control. In vivo tests show that TEC decreases glucose levels and enhances insulin sensitivity in db/db mice. By hyperinsulinemic euglycemic clamp test, this study further finds that TEC promotes glucose uptake in adipose tissue and skeletal muscle, as well as inhibits hepatic gluconeogenesis. Moreover, it finds that TEC promotes glucose uptake and adipocytes differentiation in 3T3-L1 cells like insulin, suggesting that TEC exerts an insulin mimetic effect. Mechanistically, pharmacology inhibition of IRβ abolishes the effects of TEC on glucose uptake and the phosphorylation of IR. The study further demonstrates that TEC binds to and activates IRβ by targeting its E1077 and M1079.

CONCLUSION

Therefore, this study sheds light on the mechanism underlying propolis' potential for ameliorating type 2 diabetes, offering a natural food-derived compound as a promising therapeutic option.

Evaluation of plasma cortisol during fasting test in patients with endogenous hyperinsulinemic hypoglycemia. Fifteen years experience

BACKGROUND

Endogenous hyperinsulinemic hypoglycemia (EHH) is a rare clinical condition. The aim of this study was to evaluate baseline plasma cortisol concentration and its concentration during hypoglycemic crisis in fasting tests (FT) performed in our center. Secondarily, the aim was to establish the relationship between baseline cortisol and the time of evolution of EHH.

MATERIAL AND METHODS

A retrospective, observational, descriptive study was carried out which included patients with hypoglycemic disorder with positive FT.

RESULTS

Of a total of 21 patients, 16 presented insulinoma, 1 nesidioblastosis, 2 malignant insulinoma and 2 EHH without pathological diagnosis. The time from the onset of symptoms to diagnosis was 2 years (Q1=1.5-Q2=5.5). The comparison between median baseline cortisol (BC)=11.8 mcg/dl (nmol/L 340.68) (Q1=9-Q3=14.1) and median cortisol during hypoglycemic episode (HC)=11.6 mcg/dl (nmol/L: 303.44) (Q1=7.8-Q3=16.1) showed no differences (Z=-0.08; P>.05). When correlating BC with HC, no significant relationship was observed (r=0.16; P>.05). When correlating the glycemic value in the crisis and the HC, a slight negative trend was found (r=-0.53; P=.01). In addition, we found that recurrent hypoglycemic disorder is associated with lower baseline cortisol values ​​the longer the time of its evolution.

CONCLUSION

We confirmed that cortisol values ​​remain low during hypoglycemic episodes, reinforcing the hypothesis of lack of response of this counterregulatory hormone in cases of recurrent hypoglycemia.

Individualized Models for Glucose Prediction in Type 1 Diabetes: Comparing Black-Box Approaches to a Physiological White-Box One

OBJECTIVE

Accurate blood glucose (BG) prediction are key in next-generation tools for type 1 diabetes (T1D) management, such as improved decision support systems and advanced closed-loop control. Glucose prediction algorithms commonly rely on black-box models. Large physiological models, successfully adopted for simulation, were little explored for glucose prediction, mostly because their parameters are hard to individualize. In this work, we develop a BG prediction algorithm based on a personalized physiological model inspired by the UVA/Padova T1D Simulator. Then we compare white-box and advanced black-box personalized prediction techniques.

METHODS

A personalized nonlinear physiological model is identified from patient data through a Bayesian approach based on Markov Chain Monte Carlo technique. The individualized model was integrated within a particle filter (PF) to predict future BG concentrations. The black-box methodologies considered are non-parametric models estimated via gaussian regression (NP), three deep learning methods: long-short-term-memory (LSTM), gated recurrent unit (GRU), temporal convolutional networks (TCN), and a recursive autoregressive with exogenous input model (rARX). BG forecasting performances are assessed for several prediction horizons (PH) on 12 individuals with T1D, monitored in free-living conditions under open-loop therapy for 10 weeks.

RESULTS

NP models provide the most effective BG predictions by achieving a root mean square error (RMSE), RMSE = 18.99 mg/dL, RMSE = 25.72 mg/dL and RMSE = 31.60 mg/dL, significantly outperforming: LSTM, GRU (for PH = 30 minutes), TCN, rARX, and the proposed physiological model for PH=30, 45 and 60 minutes.

CONCLUSIONS

Black-box strategies remain preferable for glucose prediction even when compared to a white-box model with sound physiological structure and individualized parameters.

Effects of Medications on Heat Loss Capacity in Chronic Disease Patients: Health Implications Amidst Global Warming

Pharmacological agents used to treat or manage diseases can modify the level of heat strain experienced by chronically ill and elderly patients via different mechanistic pathways. Human thermoregulation is a crucial homeostatic process that maintains body temperature within a narrow range during heat stress through dry (i.e., increasing skin blood flow) and evaporative (i.e., sweating) heat loss, as well as active inhibition of thermogenesis, which is crucial to avoid overheating. Medications can independently and synergistically interact with aging and chronic disease to alter homeostatic responses to rising body temperature during heat stress. This review focuses on the physiologic changes, with specific emphasis on thermolytic processes, associated with medication use during heat stress. The review begins by providing readers with a background of the global chronic disease burden. Human thermoregulation and aging effects are then summarized to give an understanding of the unique physiologic changes faced by older adults. The effects of common chronic diseases on temperature regulation are outlined in the main sections. Physiologic impacts of common medications used to treat these diseases are reviewed in detail, with emphasis on the mechanisms by which these medications alter thermolysis during heat stress. The review concludes by providing perspectives on the need to understand the effects of medication use in hot environments, as well as a summary table of all clinical considerations and research needs of the medications included in this review. SIGNIFICANCE STATEMENT: Long-term medications modulate thermoregulatory function, resulting in excess physiological strain and predisposing patients to adverse health outcomes during prolonged exposures to extreme heat during rest and physical work (e.g., exercise). Understanding the medication-specific mechanisms of altered thermoregulation has importance in both clinical and research settings, paving the way for work toward refining current medication prescription recommendations and formulating mitigation strategies for adverse drug effects in the heat in chronically ill patients.

Case report: Fatal insulin overdose in a dog with type 1 diabetes mellitus-characteristics and successful management

Administering more than 10 times the therapeutic dose of insulin is extremely rare in diabetic dogs and is life threatening with hypoglycemia and seizures if not accompanied by appropriate treatment. A 15-year-old, castrated male miniature poodle dog managed for diabetes presented with depression, disorientation, ataxia, and cluster seizures. The dog had been administered 11.1 U/kg of neutral protamine hegadorn (NPH) insulin (10 times the prescribed dose) 3 h before the onset of symptoms. Blood analysis revealed hypoglycemia, with a circulating glucose level of <50 mg/dL. To treat the hypoglycemia-induced seizures, dextrose was repeatedly administered intravenously. Repeated generalized seizures were treated with anticonvulsants and intermittent mannitol. Since refractory hypoglycemia persisted 24 h after the insulin overdose, it was decided to proceed with glucagon treatment (15-30 ng/kg/min titrated to the blood glucose level after a loading dose of 50 ng/kg intravenous bolus infusion). After 37 h of glucagon treatment, blood glucose levels stabilized. After entering a hyperglycemic state, NPH insulin was administered to manage insulin-dependent diabetes mellitus. This is the first case documented of successful treatment with glucagon, anticonvulsants and intermittent mannitol for refractory hypoglycemia and seizure caused by fatal insulin overdose. Thus, it has great clinical value in veterinary medicine.

Rational Design and Efficacy of Glucose-Responsive Insulin Therapeutics and Insulin Delivery Systems by Computation Using Connected Human and Rodent Models

Glucose-responsive insulins (GRIs) use plasma glucose levels in a diabetic patient to activate a specifically designed insulin analogue to a more potent state in real time. Alternatively, some GRI concepts use glucose-mediated release or injection of insulin into the bloodstream. GRIs hold promise to exhibit much improved pharmacological control of the plasma glucose concentration, particularly for the problem of therapeutically induced hypoglycemia. Several innovative GRI schemes are introduced into the literature, but there remains a dearth of quantitative analysis to aid the development and optimization of these constructs into effective therapeutics. This work evaluates several classes of GRIs that are proposed using a pharmacokinetic model as previously described, PAMERAH, simulating the glucoregulatory system of humans and rodents. GRI concepts are grouped into three mechanistic classes: 1) intrinsic GRIs, 2) glucose-responsive particles, and 3) glucose-responsive devices. Each class is analyzed for optimal designs that maintain glucose levels within the euglycemic range. These derived GRI parameter spaces are then compared between rodents and humans, providing the differences in clinical translation success for each candidate. This work demonstrates a computational framework to evaluate the potential clinical translatability of existing glucose-responsive systems, providing a useful approach for future GRI development.

Diabetes among Muslims during Ramadan: A narrative review

Fasting during the month of Ramadan is one of the five fundamental principles of Islam, and it is obligatory for healthy Muslim adults and adolescents. During the fasting month, Muslims usually have two meals a day, suhur (before dawn) and iftar (after dusk). However, diabetic patients may face difficulties when fasting, so it is important for medical staff to educate them on safe fasting practices. Prolonged strict fasting can increase the risk of hypoglycemia and diabetic ketoacidosis, but with proper knowledge, careful planning, and medication adjustment, diabetic Muslim patients can fast during Ramadan. For this review, a literature search was conducted using PubMed and Google Scholar until May 2023. Articles other than the English language were excluded. Current strategies for managing blood sugar levels during Ramadan include a combination of patient education on nutrition, regular monitoring of blood glucose, medications, and insulin therapy. Insulin therapy can be continued during fasting if properly titrated to the patients' needs, and finger prick blood sugar levels should be assessed regularly. If certain symptoms such as hypoglycemia, hyperglycemia, dehydration, or acute illness occur, or blood glucose levels become too high (> 300 mg/dL) or too low (< 70 mg/dL), the fast should be broken. New insulin formulations such as pegylated insulin and medications like tirzepatide, a dual agonist of gastric-inhibitory peptideand glucagonlike-peptide 1 receptors, have shown promise in managing blood sugar levels during Ramadan. Non-insulin-dependent medications like sodium-glucose-cotransporter-2 inhibitors, including the Food and Drug Administration-approved ertugliflozin, are also being used to provide additional cardiovascular benefits in patients with type 2 diabetes.

Efficacy of Fasting in Type 1 and Type 2 Diabetes Mellitus: A Narrative Review

Over the last decade, studies suggested that dietary behavior modification, including fasting, can improve metabolic and cardiovascular markers as well as body composition. Given the increasing prevalence of people with type 1 (T1DM) and type 2 diabetes mellitus (T2DM) and the increasing obesity (also in combination with diabetes), nutritional therapies are gaining importance, besides pharmaceutical interventions. Fasting has demonstrated beneficial effects for both healthy individuals and those with metabolic diseases, leading to increased research interest in its impact on glycemia and associated short- and long-term complications. Therefore, this review aimed to investigate whether fasting can be used safely and effectively in addition to medications to support the therapy in T1DM and T2DM. A literature search on fasting and its interaction with diabetes was conducted via PubMed in September 2022. Fasting has the potential to minimize the risk of hypoglycemia in T1DM, lower glycaemic variability, and improve fat metabolism in T1DM and T2DM. It also increases insulin sensitivity, reduces endogenous glucose production in diabetes, lowers body weight, and improves body composition. To conclude, fasting is efficient for therapy management for both people with T1DM and T2DM and can be safely performed, when necessary, with the support of health care professionals.

Hypoglycaemia frequency and physiological response after double or triple doses of once-weekly insulin icodec vs once-daily insulin glargine U100 in type 2 diabetes: a randomised crossover trial

AIMS/HYPOTHESIS

This study compared the frequency of hypoglycaemia, time to hypoglycaemia and recovery from hypoglycaemia after double or triple doses of once-weekly insulin icodec vs once-daily insulin glargine U100. Furthermore, the symptomatic and counterregulatory responses to hypoglycaemia were compared between icodec and glargine U100 treatment.

METHODS

In a randomised, single-centre (Department of Internal Medicine, Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria), open-label, two-period crossover trial, individuals with type 2 diabetes (age 18-72 years, BMI 18.5-37.9 kg/m2, HbA1c ≤75 mmol/mol [≤9.0%]) treated with basal insulin with or without oral glucose-lowering drugs received once-weekly icodec (for 6 weeks) and once-daily glargine U100 (for 11 days). Total weekly doses were equimolar based on individual titration of daily glargine U100 during the run-in period (target fasting plasma glucose [PG]: 4.4-7.2 mmol/l). Randomisation was carried out by assigning a randomisation number to each participant in ascending order, which encoded to one of two treatment sequences via a randomisation list prepared prior to the start of the trial. At steady state, double and triple doses of icodec and glargine U100 were administered followed by hypoglycaemia induction: first, euglycaemia was maintained at 5.5 mmol/l by variable i.v. infusion of glucose; glucose infusion was then terminated, allowing PG to decrease to no less than 2.5 mmol/l (target PGnadir). The PGnadir was maintained for 15 min. Euglycaemia was restored by constant i.v. glucose (5.5 mg kg-1 min-1). Hypoglycaemic symptoms score (HSS), counterregulatory hormones, vital signs and cognitive function were assessed at predefined PG levels towards the PGnadir.

RESULTS

Hypoglycaemia induction was initiated in 43 and 42 participants after double dose of icodec and glargine U100, respectively, and in 38 and 40 participants after triple doses, respectively. Clinically significant hypoglycaemia, defined as PGnadir <3.0 mmol/l, occurred in comparable proportions of individuals treated with icodec vs glargine U100 after double (17 [39.5%] vs 15 [35.7%]; p=0.63) and triple (20 [52.6%] vs 28 [70.0%]; p=0.14) doses. No statistically significant treatment differences were observed in the time to decline from PG values of 5.5 mmol/l to 3.0 mmol/l (2.9-4.5 h after double dose and 2.2-2.4 h after triple dose of the insulin products). The proportion of participants with PGnadir ≤2.5 mmol/l was comparable between treatments after double dose (2 [4.7%] for icodec vs 3 [7.1%] for glargine U100; p=0.63) but higher for glargine U100 after triple dose (1 [2.6%] vs 10 [25.0%]; p=0.03). Recovery from hypoglycaemia by constant i.v. glucose infusion took <30 min for all treatments. Analyses of the physiological response to hypoglycaemia only included data from participants with PGnadir <3.0 mmol/l and/or the presence of hypoglycaemic symptoms; in total 20 (46.5%) and 19 (45.2%) individuals were included after a double dose of icodec and glargine U100, respectively, and 20 (52.6%) and 29 (72.5%) individuals were included after a triple dose of icodec and glargine U100, respectively. All counterregulatory hormones (glucagon, adrenaline [epinephrine], noradrenaline [norepinephrine], cortisol and growth hormone) increased during hypoglycaemia induction with both insulin products at both doses. Following triple doses, the hormone response was greater with icodec vs glargine U100 for adrenaline at PG3.0 mmol/l (treatment ratio 2.54 [95% CI 1.69, 3.82]; p<0.001), and cortisol at PG3.0 mmol/l (treatment ratio 1.64 [95% CI 1.13, 2.38]; p=0.01) and PGnadir (treatment ratio 1.80 [95% CI 1.09, 2.97]; p=0.02). There were no statistically significant treatment differences in the HSS, vital signs and cognitive function.

CONCLUSIONS/INTERPRETATION

Double or triple doses of once-weekly icodec lead to a similar risk of hypoglycaemia compared with double or triple doses of once-daily glargine U100. During hypoglycaemia, comparable symptomatic and moderately greater endocrine responses are elicited by icodec vs glargine U100.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03945656.

FUNDING

This study was funded by Novo Nordisk A/S.

Assessing Parental Competence and Self-Ratings in Management of Pediatric Type 1 Diabetes and Emergency Glucagon Administration-An Exploratory Observational Study

BACKGROUND

Parents of pediatric patients with type I diabetes require competence in hypoglycemia management and skills in glucagon administration to deal with potentially life-threatening severe hypoglycemia. We aimed to compare parents' subjective self-ratings to an objective expert assessment of competences and skills in dealing with severe hypoglycemia.

METHODS

We interviewed 140 participants to assess their subjective self-ratings. The objective expert assessments used a standardized clinical case scenario of severe hypoglycemia and a practical demonstration of glucagon administration.

RESULTS

The participants self-rated their competence in hypoglycemia management as good (5) or very good (6), and their skills in administering glucagon as acceptable (3) [Scale: very poor (1) to very good (6)]. In the standardized clinical case scenario, 1.4% (2/140) of participants named all relevant steps of severe hypoglycemia management. In the practical demonstration of glucagon administration, 92.9% (130/140) of participants committed at least one drug handling error; 52.1% (73/140) committed at least one drug handling error rated with high clinical risk.

CONCLUSIONS

We found discrepancies regarding participants' subjective self-ratings compared to their performance in the respective objective expert assessments. These discrepancies indicate a lack of error awareness and the need for intervention studies to improve competence in hypoglycemia management and glucagon administration.

Accelerated absorption of regular insulin administered via a vascularizing permeable microchamber implanted subcutaneously in diabetic Rattus norvegicus

In Type 1 diabetes patients, even ultra-rapid acting insulins injected subcutaneously reach peak concentrations in 45 minutes or longer. The lag time between dosing and peak concentration, as well as intra- and inter-subject variability, render prandial glucose control and dose consistency difficult. We postulated that insulin absorption from subcutaneously implantable vascularizing microchambers would be significantly faster than conventional subcutaneous injection. Male athymic nude R. norvegicus rendered diabetic with streptozotocin were implanted with vascularizing microchambers (single chamber; 1.5 cm2 surface area per side; nominal volume, 22.5 μl). Plasma insulin was assayed after a single dose (1.5 U/kg) of diluted insulin human (Humulin®R U-100), injected subcutaneously or via microchamber. Microchambers were also implanted in additional animals and retrieved at intervals for histologic assessment of vascularity. Following conventional subcutaneous injection, the mean peak insulin concentration was 22.7 (SD 14.2) minutes. By contrast, when identical doses of insulin were injected via subcutaneous microchamber 28 days after implantation, the mean peak insulin time was shortened to 7.50 (SD 4.52) minutes. Peak insulin concentrations were similar by either route; however, inter-subject variability was reduced when insulin was administered via microchamber. Histologic examination of tissue surrounding microchambers showed mature vascularization on days 21 and 40 post-implantation. Implantable vascularizing microchambers of similar design may prove clinically useful for insulin dosing, either intermittently by needle, or continuously by pump including in "closed loop" systems, such as the artificial pancreas.

Pancreatic β-cell heterogeneity in adult human islets and stem cell-derived islets

Recent studies reported that pancreatic β-cells are heterogeneous in terms of their transcriptional profiles and their abilities for insulin secretion. Sub-populations of pancreatic β-cells have been identified based on the functionality and expression of specific surface markers. Under diabetes condition, β-cell identity is altered leading to different β-cell sub-populations. Furthermore, cell-cell contact between β-cells and other endocrine cells within the islet play an important role in regulating insulin secretion. This highlights the significance of generating a cell product derived from stem cells containing β-cells along with other major islet cells for treating patients with diabetes, instead of transplanting a purified population of β-cells. Another key question is how close in terms of heterogeneity are the islet cells derived from stem cells? In this review, we summarize the heterogeneity in islet cells of the adult pancreas and those generated from stem cells. In addition, we highlight the significance of this heterogeneity in health and disease conditions and how this can be used to design a stem cell-derived product for diabetes cell therapy.

In vivo antidiabetic effects of phenolic compounds of spinach, mustard, and cabbage leaves in mice

Leafy vegetables are considered to have health-promoting potentials, mainly attributed to bioactive phenolic compounds. The antidiabetic effects of spinach, mustard, and cabbage were studied by feeding their phenolic-rich aqueous extracts to alloxan-induced diabetic mice. The antioxidant, biochemical, histopathological, and hematological indices of the control, diabetic, and treated mice were studied. Phenolic compounds present in the extracts were identified and quantified using HPLC-DAD. Results showed ten, nineteen, and eleven phenolic compounds in spinach, mustard, and cabbage leave aqueous extracts, respectively. The body weight, tissue total glutathione (GSH) contents, fasting blood sugar, liver function tests, renal function tests, and lipid profile of the mice were affected by diabetes and were significantly improved by the extract treatments. Likewise, hematological indices and tissues histological studies also showed recovery from diabetic stress in treated mice. The study's findings highlight that the selected leafy vegetables potentially mitigate diabetic complications. Among the studied vegetables, cabbage extract was comparatively more active in ameliorating diabetic stress.

The Hypoglycemic Fear Syndrome: Understanding and Addressing This Common Clinical Problem in Adults With Diabetes

Although a broad literature on fear of hypoglycemia and its impact on people with type 1 or type 2 diabetes has accumulated over the past three decades, there has been surprisingly little guidance concerning how best to tackle this problem in clinical care. The aim of this article is to begin filling this gap by describing the "hypoglycemic fear syndrome," which we define as hypoglycemic fear that has become so overwhelming that it leads to avoidance behaviors and chronically elevated glucose levels. We begin by presenting several illustrative cases, describing the syndrome and how it is most commonly presented in clinical care, and detailing its most common precipitants. We then offer practical, evidence-based strategies for clinical intervention, based on the literature and our clinical experience.

Development of an artificial intelligence system to identify hypoglycaemia via ECG in adults with type 1 diabetes: protocol for data collection under controlled and free-living conditions

INTRODUCTION

Hypoglycaemia is a harmful potential complication in people with type 1 diabetes mellitus (T1DM) and can be exacerbated in patients receiving treatment, such as insulin therapies, by the very interventions aiming to achieve optimal blood glucose levels. Symptoms can vary greatly, including, but not limited to, trembling, palpitations, sweating, dry mouth, confusion, seizures, coma, brain damage or even death if untreated. A pilot study with healthy (euglycaemic) participants previously demonstrated that hypoglycaemia can be detected non-invasively with artificial intelligence (AI) using physiological signals obtained from wearable sensors. This protocol provides a methodological description of an observational study for obtaining physiological data from people with T1DM. The aim of this work is to further improve the previously developed AI model and validate its performance for glycaemic event detection in people with T1DM. Such a model could be suitable for integrating into a continuous, non-invasive, glucose monitoring system, contributing towards improving surveillance and management of blood glucose for people with diabetes.

METHODS AND ANALYSIS

This observational study aims to recruit 30 patients with T1DM from a diabetes outpatient clinic at the University Hospital Coventry and Warwickshire for a two-phase study. The first phase involves attending an inpatient protocol for up to 36 hours in a calorimetry room under controlled conditions, followed by a phase of free-living, for up to 3 days, in which participants will go about their normal daily activities unrestricted. Throughout the study, the participants will wear wearable sensors to measure and record physiological signals (eg, ECG and continuous glucose monitor). Data collected will be used to develop and validate an AI model using state-of-the-art deep learning methods.

ETHICS AND DISSEMINATION

This study has received ethical approval from National Research Ethics Service (ref: 17/NW/0277). The findings will be disseminated via peer-reviewed journals and presented at scientific conferences.

TRIAL REGISTRATION NUMBER

NCT05461144.

Recurrent hypoglycemia dampens functional regulation mediated via Neurexin-1, Neuroligin-2 and Mint-1 docking proteins: Intensified complications during diabetes

Glycemic regulation is important for maintaining critical physiological functions. Extreme variation in levels of circulating glucose are known to affect insulin secretion. Elevated insulin levels result in lowering of circulating glycemic levels culminating into hypoglycemia. Recurrence of hypoglycemia are often noted owing to fasting conditions, untimely meals, irregular dietary consumption, or as a side-effect of disease pathophysiology. Such events of hypoglycemia threaten to hamper the patterns of insulin secretion in diabetic condition. Insulin vesicle docking is a prerequisite phase which ensures anchoring of the vesicles to the β-cell membrane in order to expel the insulin cargo. Neurexin and Neuroligin are the marker docking proteins which assists in the tethering of the insulin granules to the secretory membrane. However, these cell adhesion molecules indirectly affect the glycemic levels by regulating insulin secretion. The effect of extreme levels of glycemic fluctuations on these molecules, and how it affects the docking machinery remains obscure. Our current study demonstrates down-regulated expression of Neurexin-1, Neuroligin-2 and Mint-1 molecules during hyperglycemia, hypoglycemia and diabetic hypoglycemia in rodents as well as for an in-vitro system using MIN6 cell-line. Studies with fluorescently labelled insulin revealed presence of lessened functional insulin secretory granules, concomitant with the alterations in morphology and as a result of hypoglycemia in control and diabetic condition which was found to be further deteriorating. Our studies indicate towards a feeble vesicular anchorage, which may partly be responsible for dwindled insulin secretion during diabetes. However, hypoglycemia poses as a potent diabetic complication in further deteriorating the docking machinery. To the best of our knowledge this is the first report which demonstrates the effect of hypoglycemic events in affecting insulin secretion by weakening insulin vesicular anchorage in normal and diabetic individuals.

'Didn't See the Need': Misperceptions about glucagon from the perspectives of people with diabetes and their caregivers

AIMS

Severe hypoglycaemia among people with diabetes who use insulin can be a life-threatening complication if left untreated. Although glucagon has been approved for treatment of hypoglycaemia since the 1960s, it has been underutilized. We aimed to understand the perceptions of people with diabetes and their caregivers about glucagon.

METHODS

We conducted in-depth, one-on-one telephone interviews with people with diabetes and their caregivers in the United States. The interviews included questions around general awareness of glucagon, reasons for owning or not owning glucagon, and suggestions for improving understanding of glucagon as treatment for severe hypoglycaemia. Initial synopsis and inductive codebook schema were used to analyse the responses by two independent researchers. Themes were developed from the codes, and codes were re-mapped back to the themes.

RESULTS

There were 60 dyads of people with diabetes and their caregivers (N = 120). Four themes developed from the interviews: (1) for most participants, the stated reasons for not owning or renewing a prescription for glucagon included unawareness of the medication, its advantages and its value; (2) misperceptions about glucagon occurred frequently; (3) caregivers often lacked confidence in administering reconstituted injectable glucagon; and (4) education and training from healthcare providers about glucagon would be welcomed.

CONCLUSIONS

This study emphasizes the need for healthcare providers to discuss hypoglycaemia prevention and events at each clinical visit, including the use of glucagon in the case of severe hypoglycaemia. Healthcare providers are encouraged to assess the knowledge of people with diabetes and their caregivers regarding treatment and prevention of hypoglycaemia.

Modeling the effect of glucagon on endogenous glucose production in type 1 diabetes: On the role of glucagon receptor dynamics

This paper validates a glucoregulatory model including glucagon receptors dynamics in the description of endogenous glucose production (EGP). A set of models from literature are selected for a head-to-head comparison in order to evaluate the role of glucagon receptors. Each EGP model is incorporated into an existing glucoregulatory model and validated using a set of clinical data, where both insulin and glucagon are administered. The parameters of each EGP model are identified in the same optimization problem, minimizing the root mean square error (RMSE) between the simulation and the clinical data. The results show that the RMSE for the proposed receptors-based EGP model was lower when compared to each of the considered models (Receptors approach: 7.13±1.71 mg/dl vs. 7.76±1.45 mg/dl (p=0.066), 8.45±1.38 mg/dl (p=0.011) and 8.99±1.62 mg/dl (p=0.007)). This raises the possibility of considering glucagon receptors dynamics in type 1 diabetes simulators.

Deep Multitask Learning by Stacked Long Short-Term Memory for Predicting Personalized Blood Glucose Concentration

The adverse glycemic events triggered by the inaccurate insulin infusion in Type I diabetes (T1D) can lead to fatal complications. Predicting blood glucose concentration (BGC) based on clinical health records is critical for control algorithms in the artificial pancreas (AP) and aiding in medical decision support. This paper presents a novel deep learning (DL) model incorporating multitask learning (MTL) for personalized blood glucose prediction. The network architecture consists of shared and clustered hidden layers. Two layers of stacked long short-term memory (LSTM) form the shared hidden layers that learn generalized features from all subjects. The clustered hidden layers comprise two dense layers adapting to the gender-specific variability in the data. Finally, the subject-specific dense layers offer additional fine-tuning to personalized glucose dynamics resulting in an accurate BGC prediction at the output. OhioT1DM clinical dataset is used for the training and performance evaluation of the proposed model. A detailed analytical and clinical assessment have been performed using root mean square (RMSE), mean absolute error (MAE), and Clarke error grid analysis (EGA), respectively, which demonstrates the robustness and reliability of the proposed method. Consistently leading performance has been achieved for 30- (RMSE = 16.06 $\pm$ 2.74, MAE = 10.64 $\pm$ 1.35), 60- (RMSE = 30.89 $\pm$ 4.31, MAE = 22.07 $\pm$ 2.96), 90- (RMSE = 40.51 $\pm$ 5.16, MAE = 30.16 $\pm$ 4.10), and 120-minute (RMSE = 47.39 $\pm$ 5.62, MAE = 36.36 $\pm$ 4.54) prediction horizon (PH). In addition, the EGA analysis confirms the clinical feasibility by maintaining more than 94% BGC predictions in the clinically safe zone for up to 120-minute PH. Moreover, the improvement is established by benchmarking against the state-of-the-art statistical, machine learning (ML), and deep learning (DL) methods.