Diurnal Differences in Risk of Cardiac Arrhythmias During Spontaneous Hypoglycemia in Young People With Type 1 Diabetes

Circadian (diurnal/nocturnal) pattern of cardiac arrhythmias

Circadian rhythms follow 24-hour biological cycle patterns controlled by internal biological or circadian clocks that optimize organismal homeostasis according to predictable environmental changes. These clocks are found in virtually all cells in the body, including cardiomyocytes. Triggers for and/or the occurrence of sudden cardiac death (SCD) and cardiac arrhythmias seem to follow such daily patterns. This review highlights data from studies exploring the role of day/night rhythms in the timing of arrhythmic events, studies describing the environmental, behavioral, and circadian mechanisms regulating cardiac electrophysiology focusing on the circadian pattern of arrhythmias and SCD. Mechanisms involved relate to circadian control of electrophysiological properties, vagal tone, and sleep disorders, as well as the potential interaction and synergism among these factors. By studying the diurnal variations of arrhythmias, therapy can be improved by optimally timing it to their circadian pattern and a person's internal body clock time. Potential treatment targets for arrhythmias with nocturnal onset may include upstream therapy for underlying comorbidities, type and timing of drug intake, pulmonary vein isolation, ablation of the ganglionated plexus, and autonomic nervous system control. Thus, specific history-taking, screening, and diagnostic workup are recommended to identify and characterize comorbidities and potential contributors to nocturnal arrhythmias, such as obesity, advanced age, diabetes, hypertension, and heart failure. In this direction, symptoms of sleep apnea may comprise snoring and excessive daytime sleepiness. Risk factors include obesity, decreased upper airway dimensions, and heart failure. Thus, one should have a low threshold for sleep testing to assess for sleep apnea. Sleep apnea treatment decreases ventricular arrhythmias and ameliorates some severe bradycardic episodes, often obviating the need for pacemaker implantation. Importantly, comorbidity treatment and lifestyle optimization remain crucial.

Genetic Causality between Type 1 Diabetes and Arrhythmia Identified by a Two-sample Mendelian Randomization Study

BACKGROUND

Clinical studies have shown that cardiovascular diseases in patients with type 1 diabetes (T1D) are often atypical or asymptomatic. The link between T1D and arrhythmia remains unclear. To infer causality between T1D and arrhythmia at the genetic level, we conducted a Mendelian randomization study through the genetic tools of T1D.

METHODS

In this study, we used genetic variables and summary statistics from genome-wide association studies of T1D and arrhythmia. Single nucleotide polymorphisms were selected based on the assumptions of instrumental variables. The inverse variance-weighted method was used as the primary analysis to summarize the causal effects between exposure and outcome. The weighted median and weighted mode methods were used as secondary methods. We tested for horizontal pleiotropy using the MR-Egger method and detected heterogeneity using the Q-test. A leave-one-out sensitivity analysis was performed. Scatter plots, forest plots, and funnel plots were used to visualize the results of the MR analysis.

RESULTS

In this study, we selected 28 T1D-related SNPs as instrumental variables. The IVW [odds ratio (OR) = 0.98, 95 % confidence interval (CI) = 0.97-1.00, P = 0.008], weighted median (OR = 0.98, 95 % CI = 0.96 - 0.99, P = 0.009), and weighted mode (OR = 0.98, 95 % CI = 0.96-0.99, P = 0.018) analysis methods suggested a causal effect of T1D on arrhythmia. The MR-Egger method indicated no horizontal pleiotropy (P = 0.649), and the Q-test showed no heterogeneity (IVW, P = 0.653).

CONCLUSIONS

Our MR analysis revealed a causal association between T1D and the development of arrhythmia, indicating that patients with T1D had a higher risk of arrhythmia.

Recommendations for recognizing, risk stratifying, treating, and managing children and adolescents with hypoglycemia

There has been continuous progress in diabetes management over the last few decades, not least due to the widespread dissemination of continuous glucose monitoring (CGM) and automated insulin delivery systems. These technological advances have radically changed the daily lives of people living with diabetes, improving the quality of life of both children and their families. Despite this, hypoglycemia remains the primary side-effect of insulin therapy. Based on a systematic review of the available scientific evidence, this paper aims to provide evidence-based recommendations for recognizing, risk stratifying, treating, and managing patients with hypoglycemia. The objective of these recommendations is to unify the behavior of pediatric diabetologists with respect to the timely recognition and prevention of hypoglycemic episodes and the correct treatment of hypoglycemia, especially in patients using CGM or advanced hybrid closed-loop systems. All authors have long experience in the specialty and are members of the Italian Society of Pediatric Endocrinology and Diabetology. The goal of treating hypoglycemia is to raise blood glucose above 70 mg/dL (3.9 mmol/L) and to prevent further decreases. Oral glucose at a dose of 0.3 g/kg (0.1 g/kg for children using "smart pumps" or hybrid closed loop systems in automated mode) is the preferred treatment for the conscious individual with blood glucose <70 mg/dL (3.9 mmol/L), although any form of carbohydrate (e.g., sucrose, which consists of glucose and fructose, or honey, sugary soft drinks, or fruit juice) containing glucose may be used. Using automatic insulin delivery systems, the oral glucose dose can be decreased to 0.1 g/kg. Practical flow charts are included to aid clinical decision-making. Although representing the official position of the Italian Society of Pediatric Endocrinology and Diabetology (ISPED), these guidelines are applicable to the global audience and are especially pertinent in the era of CGM and other advanced technologies.

Are the variations in ECG morphology associated to different blood glucose levels? implications for non-invasive glucose monitoring for T1D paediatric patients

AIMS

Recent clinical trials and real-world studies highlighted those variations in ECG waveforms and HRV recurrently occurred during hypoglycemic and hyperglycemic events in patients with diabetes. However, while several studies have been carried out for adult age, there is lack of evidence for paediatric patients. The main aim of the study is to identify the correlations of variations in ECG Morphology waveforms with blood glucose levels in a paediatric population.

METHODS

T1D paediatric patients who use CGM were enrolled. They wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glucose metrics, ECG parameters and HRV features were collected, and Wilcoxon rank-sum test and Spearman's correlation analysis were used to explore if different levels of blood glucose were associated to ECG morphological changes.

RESULTS

Results showed that hypoglycaemic events in paediatric patients with T1D are strongly associated with variations in ECG morphology and HRV.

CONCLUSIONS

Results showed the opportunity of using the ECG as a non-invasive adding instrument to monitor the hypoglycaemic events through the integration of the ECG continuous information with CGM data. This innovative approach represents a promising step forward in diabetes management, offering a more comprehensive and effective means of detecting and responding to critical changes in glucose levels.

Hypoglycemia and Mortality Risk in Incident Hemodialysis Patients

OBJECTIVE

Hypoglycemia is a frequent occurrence in chronic kidney disease patients due to alterations in glucose and insulin metabolism. However, there are sparse data examining the predictors and clinical implications of hypoglycemia including mortality risk among incident hemodialysis patients.

DESIGN AND METHODS

Among 58,304 incident hemodialysis patients receiving care from a large national dialysis organization over 2007-2011, we examined clinical characteristics associated with risk of hypoglycemia, defined as a blood glucose concentration <70 mg/dL, in the first year of dialysis using expanded case-mix + laboratory logistic regression models. We then examined the association between hypoglycemia during the first year of dialysis with all-cause mortality using expanded case-mix + laboratory Cox models.

RESULTS

In the first year of dialysis, hypoglycemia was observed among 16.8% of diabetic and 6.9% of nondiabetic incident hemodialysis patients. In adjusted logistic regression models, clinical characteristics associated with hypoglycemia included younger age, female sex, African-American race, presence of a central venous catheter, lower residual renal function, and longer dialysis session length. In the overall cohort, patients who experienced hypoglycemia had a higher risk of all-cause mortality risk (reference: absence of hypoglycemia): adjusted hazard ratio (95% confidence interval) 1.08 (1.04, 1.13). In stratified analyses, hypoglycemia was also associated with higher mortality risk in the diabetic and nondiabetic subgroups: adjusted hazard ratios (95% confidence interval's) 1.08 (1.04-1.13), and 1.17 (0.94-1.45), respectively.

CONCLUSIONS

Hypoglycemia was a frequent occurrence among both diabetic and nondiabetic hemodialysis patients and was associated with a higher mortality risk. Further studies are needed to identify approaches that reduce hypoglycemia risk in the hemodialysis population.

Cardiac arrhythmia and hypoglycaemia in patients receiving haemodialysis with and without diabetes (the CADDY study): protocol for a Danish multicentre cohort study

INTRODUCTION

Patients receiving haemodialysis are at increased risk of arrhythmias and sudden cardiac death, but data on arrhythmia burden and the pathophysiology remain limited. Among potential risk factors, hypoglycaemia is proposed as a possible trigger of lethal arrhythmias. The development of implantable loop recorders (ILR) and continuous glucose monitoring (CGM) enables long-term continuous ECG and glycaemic monitoring. The current article presents the protocol of a study aiming to increase the understanding of arrhythmias and risk factors in patients receiving haemodialysis. The findings will provide a detailed exploration of the burden and nature of arrhythmias in these patients including the potential association between hypoglycaemia and arrhythmias.

METHODS AND ANALYSIS

The study is an investigator-initiated, prospective, multicentre cohort study recruiting 70 patients receiving haemodialysis: 35 with diabetes and 35 without diabetes. Participants are monitored with ILRs and CGM for 18 months follow-up. Data collection further includes a monthly collection of predialysis blood samples and dialysis parameters. The primary outcome is the presence of clinically significant arrhythmias defined as a composite of bradycardia, ventricular tachycardia, or ventricular fibrillation. Secondary outcomes include the characterisation of clinically significant arrhythmias and other arrhythmias, glycaemic characteristics, and mortality. The data analyses include an assessment of the association between arrhythmias and hypoglycaemia and hyperglycaemia, baseline clinical variables, and parameters related to kidney failure and the haemodialysis procedure.

ETHICS AND DISSEMINATION

The study has been approved by the Ethics Committee of the Capital Region of Denmark (H-20069767). The findings will be presented at national and international congresses as well as in international peer-reviewed scientific journals.

TRIAL REGISTRATION NUMBER

NCT04841304.

Brain Regulation of Cardiac Function during Hypoglycemia

Hypoglycemia occurs frequently in people with type 1 and type 2 diabetes. Hypoglycemia activates the counter-regulatory response. Besides peripheral glucose sensors located in the pancreas, mouth, gastrointestinal tract, portal vein, and carotid body, many brain regions also contain glucose-sensing neurons that detect this fall in glucose. The autonomic nervous system innervates the heart, and during hypoglycemia, can cause many changes. Clinical and animal studies have revealed changes in electrocardiograms during hypoglycemia. Cardiac repolarization defects (QTc prolongation) occur during moderate levels of hypoglycemia. When hypoglycemia is severe, it can be fatal. Cardiac arrhythmias are thought to be the major mediator of sudden death due to severe hypoglycemia. Both the sympathetic and parasympathetic nervous systems of the brain have been implicated in regulating these arrhythmias. Besides cardiac arrhythmias, hypoglycemia can have profound changes in the heart and most of these changes are exacerbated in the setting of diabetes. A better understanding of how the brain regulates cardiac changes during hypoglycemia will allow for better therapeutic intervention to prevent cardiovascular death associated with hypoglycemia in people with diabetes. The aim of this paper is to provide a narrative review of what is known in the field regarding how the brain regulates the heart during hypoglycemia.

Association of hypoglycaemia with the risks of arrhythmia and mortality in individuals with diabetes - a systematic review and meta-analysis

Background

Hypoglycaemia has been linked to an increased risk of cardiac arrhythmias by causing autonomic and metabolic alterations, which may be associated with detrimental outcomes in individuals with diabetes(IWD), such as cardiovascular diseases (CVDs) and mortality, especially in multimorbid or frail people. However, such relationships in this population have not been thoroughly investigated. For this reason, we conducted a systematic review and meta-analysis.

Methods

Relevant papers published on PubMed, Embase, Cochrane, Web of Knowledge, Scopus, and CINHAL complete from inception to December 22, 2022 were routinely searched without regard for language. All of the selected articles included odds ratio, hazard ratio, or relative risk statistics, as well as data for estimating the connection of hypoglycaemia with cardiac arrhythmia, CVD-induced death, or total death in IWD. Regardless of the heterogeneity assessed by the I2 statistic, pooled relative risks (RRs) and 95% confidence intervals (CI) were obtained using random-effects models.

Results

After deleting duplicates and closely evaluating all screened citations, we chose 60 studies with totally 5,960,224 participants for this analysis. Fourteen studies were included in the arrhythmia risk analysis, and 50 in the analysis of all-cause mortality. Hypoglycaemic patients had significantly higher risks of arrhythmia occurrence (RR 1.42, 95%CI 1.21-1.68), CVD-induced death (RR 1.59, 95% CI 1.24-2.04), and all-cause mortality (RR 1.68, 95% CI 1.49-1.90) compared to euglycaemic patients with significant heterogeneity.

Conclusion

Hypoglycaemic individuals are more susceptible to develop cardiac arrhythmias and die, but evidence of potential causal linkages beyond statistical associations must await proof by additional specifically well planned research that controls for all potential remaining confounding factors.

Prevalence of Positivity for Diabetes-Associated Autoantibodies in Individuals with Type 2 Diabetes and Their Further Characterisation: Cross-sectional Study from Slovakia

BACKGROUND

Individuals initially diagnosed with type 2 diabetes (T2D) might exhibit positivity for diabetes-associated autoantibodies (DAA +). We investigated the prevalence of DAA positivity in a group of individuals with T2D who were referred to a tertiary diabetes centre within a pre-specified period of time. We aimed to identify characteristics linked with DAA positivity by comparing DAA + individuals with their DAA-negative counterparts.

METHODS

This was a cross-sectional study into which all T2D patients referred to the National Institute of Endocrinology and Diabetology, Ľubochňa, Slovakia, between 1 January and 30 June 2016 were included. Data on > 70 participants' characteristics, including antibodies against glutamic acid decarboxylase (anti-GAD₆₅), insulinoma-associated antigen IA-2 (IA-2A) and insulin (IAA), were collected.

RESULTS

Six hundred and ninety-two individuals (387, 55.6% female) with a median (range) age of 62 (24-83) years, HbA1c of 8.9 (5.0-15.7)% [74 (31-148 mmol/mol)] and diabetes duration of 13.0 (0-42) years were analysed. One hundred and forty-five (145/692, 21.0%) tested positive for at least one DAA; 136/692 (19.7%) were positive for anti-GAD₆₅, 21/692 (3.0%) were positive for IA-2A and 9/692 (1.3%) were positive for IAA. Only 84.9% of the DAA + individuals aged > 30 years at the time of diabetes diagnosis met the current diagnostic criteria for latent autoimmune diabetes of adults (LADA). DAA + differed from DAA - individuals in multiple characteristics, including the incidence of hypoglycaemia.

CONCLUSION

Several pathological processes linked with distinct types of diabetes can develop in parallel, including insulin resistance and autoimmune insulitis. In this single-centre cross-sectional study from Slovakia, we report a higher than previously published prevalence of DAA positivity in a group of individuals with a formal diagnosis of T2D.

Effects of Hypoglycemia on Cardiovascular Function in Patients with Diabetes

Hypoglycemia is common in patients with type 1 and type 2 diabetes (T1D, T2D), treated with insulin or sulfonylureas, and has multiple short- and long-term clinical implications. Whether acute or recurrent, hypoglycemia significantly affects the cardiovascular system with the potential to cause cardiovascular dysfunction. Several pathophysiological mechanisms have been proposed linking hypoglycemia to increased cardiovascular risk, including hemodynamic changes, myocardial ischemia, abnormal cardiac repolarization, cardiac arrhythmias, prothrombotic and proinflammatory effects, and induction of oxidative stress. Hypoglycemia-induced changes can promote the development of endothelial dysfunction, which is an early marker of atherosclerosis. Although data from clinical trials and real-world studies suggest an association between hypoglycemia and cardiovascular events in patients with diabetes, it remains uncertain whether this association is causal. New therapeutic agents for patients with T2D do not cause hypoglycemia and have cardioprotective benefits, whereas increasing the use of new technologies, such as continuous glucose monitoring devices and insulin pumps, has the potential to reduce hypoglycemia and its adverse cardiovascular outcomes in patients with T1D.

Hypoglycaemia in type 1 diabetes mellitus: risks and practical prevention strategies

Hypoglycaemia, which occurs when blood levels of glucose fall below what is considered a normal range, is a well-known complication of insulin therapy in individuals with type 1 diabetes mellitus. Despite advances in diabetes mellitus management, hypoglycaemia has continued to affect the majority of these individuals, leading to suboptimal care and decreased quality of life. Multiple epidemiological studies have demonstrated the risks associated with hypoglycaemic events. With this understanding, various advances have been made in therapeutics for diabetes mellitus management. Diabetes mellitus education continues to form the foundation for management and prevention of hypoglycaemia. The advent of newer diabetes mellitus technologies and newer insulins herald improvements in management strategies and hypoglycaemia prevention. Improved understanding of these newer approaches is needed to ensure delivery of safe and effective care to individuals with type 1 diabetes mellitus, leading to reductions in both the short-term and long-term morbidity and mortality associated with hypoglycaemic events.

Exercise-related hypoglycaemia induces QTc-interval prolongation in individuals with type 1 diabetes

AIMS

To investigate changes in cardiac repolarisation during exercise-related hypoglycaemia compared to hypoglycaemia induced at rest in people with type 1 diabetes.

MATERIAL AND METHODS

In a randomised crossover study, 15 men with type 1 diabetes underwent two separate hyperinsulinaemic euglycaemic-hypoglycaemic clamp experiments during Holter-ECG monitoring. One experiment included a bout of moderate-intensity cycling exercise (60 min) along with declining plasma glucose (PG; Clamp-exercise). In the other experiment, hypoglycaemia was induced with the participants at rest (Clamp-rest). We studied QTc interval, T-peak to T-end (Tpe) interval and hormonal responses during three steady-state phases: (i) baseline (PG 4.0-8.0 mmol/L); (ii) hypoglycaemic phase (PG <3.0 mmol/L); and (iii) recovery phase (PG 4.0-8.0 mmol/L).

RESULTS

Both QTc interval and Tpe interval increased significantly from baseline during the hypoglycaemic phase but with no significant difference between test days. These changes were accompanied by an increase in plasma adrenaline and a decrease in plasma potassium on both days. During the recovery phase, ΔQTc interval was longer during Clamp-rest compared to Clamp-exercise, whereas ΔTpe interval remained similar on the two test days.

CONCLUSIONS

We found that both exercise-related hypoglycaemia and hypoglycaemia induced at rest can cause QTc-interval prolongation and Tpe-interval prolongation in people with type 1 diabetes. Thus, both scenarios may increase susceptibility to ventricular arrhythmias.

Can the Use of Continuous Glucose Monitoring Improve Glycemic Control in Patients with Type 1 and 2 Diabetes Receiving Dialysis?

BACKGROUND

Hemoglobin A1c (HbA1c) is an unreliable glycemic marker in the dialysis population, and alternative methods of glycemic monitoring should be considered. Continuous glucose monitoring (CGM) measures interstitial glucose, an indirect measure of plasma glucose, and allows for estimating mean sensor glucose, glucose variability, and time in ranges. Thus, CGM provides a more nuanced picture of glycemic variables than HbA1c, which only informs about average glucose and not variation in glucose or hypoglycemia.

SUMMARY

In non-dialysis patients with type 1 and type 2 diabetes, CGM metrics are increasingly used to estimate glycemic control and are associated with improvements in glucose levels. Although a clear link has not yet been established between some CGM variables and the development of late diabetic complications, CGM use could be an important step forward in improving glycemic control in patients receiving dialysis. The ability to detect and prevent hypoglycemia while optimizing glucose levels could be particularly valuable. However, long-term CGM use has not been evaluated in the dialysis population, and the practical burden and cost associated with CGM use may be a limitation. We discuss the strengths and limitations of using CGM in the dialysis population with type 1 and type 2 diabetes.

KEY MESSAGES

CGM circumvents the pitfalls of HbA1c in dialysis patients and provides detailed measures of the mean sensor glucose, glucose variability, and time in ranges. Guidelines recommend a minimum of 50% time spent in the target range (3.9-10.0 mmol/L) and less than 1% below range (<3.9 mmol/L) for patients receiving dialysis but remain to be evaluated in the dialysis population. CGM can be a valuable tool in reducing overall glucose levels and variations while detecting hypoglycemia, but the practical burden of CGM use and cost may be a limitation.

Detecting hypoglycemia-induced electrocardiogram changes in a rodent model of type 1 diabetes using shape-based clustering

Sudden death related to hypoglycemia is thought to be due to cardiac arrhythmias. A clearer understanding of the cardiac changes associated with hypoglycemia is needed to reduce mortality. The objective of this work was to identify distinct patterns of electrocardiogram heartbeat changes that correlated with glycemic level, diabetes status, and mortality using a rodent model. Electrocardiogram and glucose measurements were collected from 54 diabetic and 37 non-diabetic rats undergoing insulin-induced hypoglycemic clamps. Shape-based unsupervised clustering was performed to identify distinct clusters of electrocardiogram heartbeats, and clustering performance was assessed using internal evaluation metrics. Clusters were evaluated by experimental conditions of diabetes status, glycemic level, and death status. Overall, shape-based unsupervised clustering identified 10 clusters of ECG heartbeats across multiple internal evaluation metrics. Several clusters demonstrating normal ECG morphology were specific to hypoglycemia conditions (Clusters 3, 5, and 8), non-diabetic rats (Cluster 4), or were generalized among all experimental conditions (Cluster 1). In contrast, clusters demonstrating QT prolongation alone or a combination of QT, PR, and QRS prolongation were specific to severe hypoglycemia experimental conditions and were stratified heartbeats by non-diabetic (Clusters 2 and 6) or diabetic status (Clusters 9 and 10). One cluster demonstrated an arrthymogenic waveform with premature ventricular contractions and was specific to heartbeats from severe hypoglycemia conditions (Cluster 7). Overall, this study provides the first data-driven characterization of ECG heartbeats in a rodent model of diabetes during hypoglycemia.

Vitamin E treatment in insulin-deficient diabetic rats reduces cardiac arrhythmias and mortality during severe hypoglycemia

In people with type 1 diabetes, hypoglycemia can induce cardiac arrhythmias. In rodent experiments, severe hypoglycemia can induce fatal cardiac arrhythmias, especially so in diabetic models. Increased oxidative stress associated with insulin-deficient diabetes was hypothesized to increase susceptibility to severe hypoglycemia-induced fatal cardiac arrhythmias. To test this hypothesis, Sprague-Dawley rats were made insulin deficient with streptozotocin and randomized into two groups: 1) control (n = 22) or 2) vitamin E treated (four doses of α-tocopherol, 400 mg/kg, n = 20). Following 1 week of treatment, rats were either tested for cardiac oxidative stress or underwent a hyperinsulinemic-severe hypoglycemic (10-15 mg/dL) clamp with electrocardiogram recording. As compared with controls, vitamin E-treated rats had threefold less cardiac oxidative stress, sixfold less mortality due to severe hypoglycemia, and sevenfold less incidence of heart block. In summary, vitamin E treatment and the associated reduction of cardiac oxidative stress in diabetic rats reduced severe hypoglycemia-induced fatal cardiac arrhythmias. These results indicate that in the setting of diabetes, pharmacological treatments that reduce oxidative stress may be an effective strategy to reduce the risk of severe hypoglycemia-induced fatal cardiac arrhythmias.NEW & NOTEWORTHY For people with type 1 diabetes, severe hypoglycemia can be fatal. We show in our animal model that insulin-deficient diabetic rats have fatal cardiac arrhythmias during severe hypoglycemia that are associated with increased cardiac oxidative stress. Importantly, treatment with vitamin E, to reduce oxidative stress, decreased fatal cardiac arrhythmias during severe hypoglycemia.

Review: experimentally induced hypoglycemia-associated autonomic failure in humans: determinants, designs and drawbacks

Context

Iatrogenic hypoglycemia remains one of the leading hindrances of optimal glycemic management in insulin-treated diabetes. Recurring hypoglycemia leads to a condition of hypoglycemia-associated autonomic failure (HAAF). HAAF refers to a combination of (i) impaired hormonal counterregulatory responses and (ii) hypoglycemia unawareness to subsequent hypoglycemia, substantially increasing the risk of severe hypoglycemia. Several studies since the 1990s have experimentally induced HAAF, yielding variable results.

Objective

The aim of this review was to assess the varying designs, clinical outcomes, potential assets, and drawbacks related to these studies.

Method

A systemic literature search was conducted on PubMed and Embase in winter 2021 to include all human studies attempting to experimentally induce HAAF. In different combinations, the search terms used were “hypoglycemia-associated autonomic failure,” “HAAF,” “hypoglycemia,” “recurring,” “recurrent,” “repeated,” “consecutive,” and “unawareness,” yielding 1565 publications. Inclusion criteria were studies that had aimed at experimentally inducing HAAF and measuring outcomes of hormonal counterregulation and awareness of hypoglycemia.

Results

The literature search yielded 27 eligible publications, of which 20 were successful in inducing HAAF while statistical significantly impairing both hormonal counterregulation and impairing awareness of hypoglycemia to subsequent hypoglycemia. Several factors were of significance as regards inducing HAAF: Foremost, the duration of antecedent hypoglycemia should be at least 90 minutes and blood glucose should be maintained below 3.4 mmol/L. Other important factors to consider are the type of participants, insulin dosage, and the risk of unintended hypoglycemia prior to the study.

Conclusion

Here we have outlined the most important factors to take into consideration when designing a study aimed at inducing HAAF, including to take into consideration other disease states susceptible to hypoglycemia, thus hopefully clarifying the field and allowing qualified studies in the future.

Severe Hypoglycemia and Incidence of QT Interval Prolongation Among Adults With Type 2 Diabetes

CONTEXT

There is a paucity of large-scale epidemiological studies on the link between severe hypoglycemia (SH) and corrected QT (QTc) interval prolongation in type 2 diabetes (T2DM).

OBJECTIVE

To evaluate the association of SH with QTc prolongation in adults with T2DM.

METHODS

Prospective cohort analysis of participants enrolled in the ACCORD (Action to Control Cardiovascular Risk in Diabetes) study without QTc prolongation at baseline. SH was assessed over a 24-month period. Incident QTc prolongation was ascertained using follow-up electrocardiograms. Modified Poisson regression was used to generate the risk ratio (RR) and 95% CI for QTc prolongation.

RESULTS

Among 8277 participants (mean age 62.6 years [SD 6.5], 38.7% women, 62.8% White), 324 had ≥1 SH episode (3.9%). Over a median of 5 years, 517 individuals developed QTc prolongation (6.3%). Participants with SH had a 66% higher risk of QTc prolongation (RR 1.66, 95% CI 1.16-2.38). The incidence of QTc prolongation was 10.3% (27/261) and 14.3% (9/63) for participants with 1 and ≥2 SH, respectively. Compared with no SH, RRs for patients with 1 and ≥2 SH episodes were 1.57 (95% CI 1.04-2.39) and 2.01 (95% CI 1.07-3.78), respectively. Age modified the association of SH with QTc prolongation (PInteraction = .008). The association remained significant among younger participants (<61.9 years [median age]: RR 2.63, 95% CI 1.49-4.64), but was nonsignificant among older participants (≥61.9 years: RR 1.37, 95% CI 0.87-2.17).

CONCLUSION

In a large population with T2DM, SH was associated with an increased risk of QTc prolongation independently of other risk factors such as cardiac autonomic neuropathy. The association was strongest among younger participants.

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

Background

Monitoring glucose and other parameters in persons with type 1 diabetes (T1D) can enhance acute glycemic management and the diagnosis of long-term complications of the disease. For most persons living with T1D, the determination of insulin delivery is based on a single measured parameter—glucose. To date, wearable sensors exist that enable the seamless, noninvasive, and low-cost monitoring of multiple physiological parameters.

Objective

The objective of this literature survey is to explore whether some of the physiological parameters that can be monitored with noninvasive, wearable sensors may be used to enhance T1D management.

Methods

A list of physiological parameters, which can be monitored by using wearable sensors available in 2020, was compiled by a thorough review of the devices available in the market. A literature survey was performed using search terms related to T1D combined with the identified physiological parameters. The selected publications were restricted to human studies, which had at least their abstracts available. The PubMed and Scopus databases were interrogated. In total, 77 articles were retained and analyzed based on the following two axes: the reported relations between these parameters and T1D, which were found by comparing persons with T1D and healthy control participants, and the potential areas for T1D enhancement via the further analysis of the found relationships in studies working within T1D cohorts.

Results

On the basis of our search methodology, 626 articles were returned, and after applying our exclusion criteria, 77 (12.3%) articles were retained. Physiological parameters with potential for monitoring by using noninvasive wearable devices in persons with T1D included those related to cardiac autonomic function, cardiorespiratory control balance and fitness, sudomotor function, and skin temperature. Cardiac autonomic function measures, particularly the indices of heart rate and heart rate variability, have been shown to be valuable in diagnosing and monitoring cardiac autonomic neuropathy and, potentially, predicting and detecting hypoglycemia. All identified physiological parameters were shown to be associated with some aspects of diabetes complications, such as retinopathy, neuropathy, and nephropathy, as well as macrovascular disease, with capacity for early risk prediction. However, although they can be monitored by available wearable sensors, most studies have yet to adopt them, as opposed to using more conventional devices.

Conclusions

Wearable sensors have the potential to augment T1D sensing with additional, informative biomarkers, which can be monitored noninvasively, seamlessly, and continuously. However, significant challenges associated with measurement accuracy, removal of noise and motion artifacts, and smart decision-making exist. Consequently, research should focus on harvesting the information hidden in the complex data generated by wearable sensors and on developing models and smart decision strategies to optimize the incorporation of these novel inputs into T1D interventions.

Glucose variability and predicted cardiovascular risk after gastrectomy

PURPOSE

To investigate the correlation between glycemic trends and cardiovascular risk after gastrectomy for gastric cancer.

METHODS

We enrolled 105 gastric cancer patients who underwent gastrectomy at our hospital between October 2017 and July 2020. Postoperative glucose concentrations, trends, and patterns were recorded using a continuous glucose monitoring (CGM) device. Cardiovascular risk was calculated using the Framingham stroke risk profile score (FSRPS), the Framingham risk score (FRS), and the Suita score. We examined the correlations between glycemic variability and cardiovascular risk scores.

RESULTS

There were significant differences in the standard deviation (SD) of glucose levels between the high and low FSRPS groups (p = 0.049), the high and low FRS groups (p = 0.011), and the high and low Suita score groups (p = 0.044). The SD of glucose levels was significantly higher in patients with diabetes mellitus (DM) (p < 0.001) and those who underwent total gastrectomy (TG) (p = 0.017). Additionally, the CGM data available for 38 patients 1 year post-gastrectomy were analyzed for glucose level dynamics, and the SD was found to be significantly higher than that at 1 month (p < 0.001).

CONCLUSION

Our findings suggest that long-term follow-up and therapeutic strategies tailored to glycemic trends may be necessary for gastric cancer patients after gastrectomy, especially those with DM and those who have undergone TG, to prevent cardiovascular events.

Hypoglycemia-Exacerbated Mitochondrial Connexin 43 Accumulation Aggravates Cardiac Dysfunction in Diabetic Cardiomyopathy

Background

Diabetic cardiomyopathy (DCM) is a complex multifaceted disease responsible for elevated heart failure (HF) morbidity and mortality in patients with diabetes mellitus (DM). Patients with DCM exhibit subclinical diastolic dysfunction, progression toward systolic impairment, and abnormal electrophysiology. Hypoglycemia events that occur spontaneously or due to excess insulin administration threaten the lives of patients with DM—with the increased risk of sudden death. However, the molecular underpinnings of this fatal disease remain to be elucidated.

Methods and Results

Here, we used the established streptozotocin-induced DCM murine model to investigate how hypoglycemia aggravates DCM progression. We confirmed connexin 43 (Cx43) dissociation from cell–cell interaction and accumulation at mitochondrial inner membrane both in the cardiomyocytes of patients with DM and DCM murine. Here, we observed that cardiac diastolic function, induced by chronic hyperglycemia, was further aggravated upon hypoglycemia challenge. Similar contractile defects were recapitulated using neonatal mouse ventricular myocytes (NMVMs) under glucose fluctuation challenges. Using immunoprecipitation mass spectrometry, we identified and validated that hypoglycemia challenge activates the mitogen-activated protein kinase kinase (MAPK kinase) (MEK)/extracellular regulated protein kinase (ERK) and inhibits phosphoinositide 3-kinase (PI3K)/Akt pathways, which results in Cx43 phosphorylation by Src protein and translocation to mitochondria in cardiomyocytes. To determine causality, we overexpressed a mitochondrial targeting Cx43 (mtCx43) using adeno-associated virus serotype 2 (AAV2)/9. At normal blood glucose levels, mtCx43 overexpression recapitulated cardiac diastolic dysfunction as well as aberrant electrophysiology in vivo. Our findings give support for therapeutic targeting of MEK/ERK/Src and PI3K/Akt/Src pathways to prevent mtCx43-driven DCM.

Conclusion

DCM presents compensatory adaptation of mild mtCx43 accumulation, yet acute hypoglycemia challenges result in further accumulation of mtCx43 through the MEK/ERK/Src and PI3K/Akt/Src pathways. We provide evidence that Cx43 mislocalization is present in hearts of patients with DM hearts, STZ-induced DCM murine model, and glucose fluctuation challenged NMVMs. Mechanistically, we demonstrated that mtCx43 is responsible for inducing aberrant contraction and disrupts electrophysiology in cardiomyocytes and our results support targeting of mtCx43 in treating DCM.

Continuous Glucose Monitoring in Adults With Type 1 Diabetes With 35 Years Duration From the DCCT/EDIC Study

OBJECTIVE

We evaluated blinded continuous glucose monitoring (CGM) profiles in a subset of adults with type 1 diabetes from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study to characterize the frequency of glycemic excursions and contributing factors.

RESEARCH DESIGN AND METHODS

CGM-derived metrics were compared for daytime and nighttime periods using blinded CGM for a minimum of 6.5 days (average 11.9 days) and correlated with HbA1c levels, routine use of diabetes devices, and other characteristics in 765 participants.

RESULTS

Participants were 58.9 ± 6.5 years of age with diabetes duration 36.8 ± 4.9 years and HbA1c 7.8 ± 1.2%; 58% used insulin pumps, and 27% used personal, unblinded CGM. Compared with daytime, nighttime mean sensor glucose was lower, percent time in range 70-180 mg/dL (TIR) was similar, and hypoglycemia was more common. Over the entire recording period, only 9% of the 765 participants achieved >70% TIR and only 28% achieved <1% of observations of <54 mg/dL. Indeed, participants with the highest percentage of hypoglycemia had the lowest HbA1c levels. However, use of insulin pumps and CGM decreased the percent time at <54 mg/dL.

CONCLUSIONS

In adults with long-standing type 1 diabetes, short-term blinded CGM profiles revealed frequent clinically significant hypoglycemia (<54 mg/dL) during the night and more time in hyperglycemia during the day. The small subset of participants using routine CGM and insulin pumps had fewer hypoglycemic and hyperglycemic excursions and lower HbA1c levels. Thus, strategies to lower meal-stimulated hyperglycemia during the day and prevent hypoglycemia at night are relevant clinical goals in older patients with type 1 diabetes.

Novel approaches to hypoglycemia and burnt-out diabetes in chronic kidney disease

PURPOSE OF REVIEW

Diabetes mellitus is a leading cause of chronic kidney disease (CKD) that confers faster kidney disease progression, higher mortality, and various metabolic derangements including hypoglycemia.

RECENT FINDINGS

Even in the absence of diabetes mellitus, growing research demonstrates that CKD patients are at heightened risk for hypoglycemia via multiple pathways. In CKD patients transitioning to end-stage renal disease (ESRD), spontaneous resolution of hyperglycemia and frequent hypoglycemia resulting in reduction and/or cessation of glucose-lowering medications are frequently observed in a phenomenon described as 'burnt-out diabetes'. In non-CKD patients, it is well established that hypoglycemia is causally associated with mortality, with pathways including arrhythmias, sudden cardiac death, stroke, and seizures. Increasing evidence shows that, in CKD and ESRD patients with and without diabetes mellitus, hypoglycemia is associated with cardiovascular complications and mortality risk.

SUMMARY

Given the high prevalence of hypoglycemia in CKD patients and the morbidity and mortality associated with this metabolic complication, a multimodal strategy is needed to prevent dysglycemia, including individualization of glycemic targets, selection of glucose-lowering medications less likely to induce hypoglycemia, medical nutrition therapy administered by trained dietitians, and accurate and precise hypoglycemia detection methods, such as self-monitored blood glucose or continuous glucose monitoring including during dialysis treatment.

Associations of hypoglycemia, glycemic variability and risk of cardiac arrhythmias in insulin-treated patients with type 2 diabetes: a prospective, observational study

Background

Insulin-treated patients with type 2 diabetes (T2D) are at risk of hypoglycemia, which is associated with an increased risk of cardiovascular disease and mortality. Using a long-term monitoring approach, we investigated the association between episodes of hypoglycemia, glycemic variability and cardiac arrhythmias in a real-life setting.

Methods

Insulin-treated patients with T2D (N = 21, [mean ± SD] age 66.8 ± 9.6 years, BMI 30.1 ± 4.5 kg/m², HbA1c 6.8 ± 0.4% [51.0 ± 4.8 mmol/mol]) were included for a one-year observational study. Patients were monitored with continuous glucose monitoring ([mean ± SD] 118 ± 6 days) and an implantable cardiac monitor (ICM) during the study period.

Results

Time spend in hypoglycemia was higher during nighttime than during daytime ([median and interquartile range] 0.7% [0.7–2.7] vs. 0.4% [0.2–0.8]). The ICMs detected 724 episodes of potentially clinically significant arrhythmias in 12 (57%) participants, with atrial fibrillation and pauses accounting for 99% of the episodes. No association between hypoglycemia and cardiac arrhythmia was found during daytime. During nighttime, subject-specific hourly incidence of cardiac arrhythmias tended to increase with the occurrence of hypoglycemia (incident rate ratio [IRR] 1.70 [95% CI 0.36–8.01]) but only slightly with increasing time in hypoglycemia (IRR 1.04 [95% CI 0.89–1.22] per 5 min). Subject-specific incidence of cardiac arrhythmias during nighttime increased with increasing glycemic variability as estimated by coefficient of variation whereas it decreased during daytime (IRR 1.33 [95% CI 1.05–1.67] and IRR 0.77 [95% CI 0.59–0.99] per 5% absolute increase, respectively).

Conclusions

Cardiac arrhythmias were common in insulin-treated patients with T2D and were associated with glycemic variability, whereas arrhythmias were not strongly associated with hypoglycemia.

Trial registration: NCT03150030, ClinicalTrials.gov, registered May 11, 2017. https://clinicaltrials.gov/ct2/show/NCT03150030

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01425-0.

Hypoglycaemia combined with mild hypokalaemia reduces the heart rate and causes abnormal pacemaker activity in a computational model of a human sinoatrial cell

Low blood glucose, hypoglycaemia, has been implicated as a possible contributing factor to sudden cardiac death (SCD) in people with diabetes but it is challenging to investigate in clinical studies. We hypothesized the effects of hypoglycaemia on the sinoatrial node (SAN) in the heart to be a candidate mechanism and adapted a computational model of the human SAN action potential developed by Fabbri et al., to investigate the effects of hypoglycaemia on the pacemaker rate. Using Latin hypercube sampling, we combined the effects of low glucose (LG) on the human ether-a-go-go-related gene channel with reduced blood potassium, hypokalaemia, and added sympathetic and parasympathetic stimulus. We showed that hypoglycaemia on its own causes a small decrease in heart rate but there was also a marked decrease in heart rate when combined with hypokalaemia. The effect of the sympathetic stimulus was diminished, causing a smaller increase in heart rate, with LG and hypokalaemia compared to normoglycaemia. By contrast, the effect of the parasympathetic stimulus was enhanced, causing a greater decrease in heart rate. We therefore demonstrate a potential mechanistic explanation for hypoglycaemia-induced bradycardia and show that sinus arrest is a plausible mechanism for SCD in people with diabetes.

Autonomic cardiac regulation during spontaneous nocturnal hypoglycemia in children with type 1 diabetes

BACKGROUND

Hypoglycemia is the most common complication in insulin treated diabetes. Though mostly mild, it can be fatal in rare cases: It is hypothesized that hypoglycemia related QTc prolongation contributes to cardiac arrhythmia.

OBJECTIVE

To evaluate influence of nocturnal hypoglycemia on QTc and heart rate variability (HRV) in children with T1D.

METHODS

Children and adolescents with T1D for at least 6 months participated in an observational study using continuous glucose monitoring (CGM) and Holter electrocardiogram for five consecutive nights. Mean QTc was calculated for episodes of nocturnal hypoglycemia (<3.7 mmol/L) and compared to periods of the same duration preceding hypoglycemia. HRV (RMSSD, low and high frequency power LF and HF) was analyzed for different 15 min intervals: before hypoglycemia, onset of hypoglycemia, before/after nadir, end of hypoglycemia and after hypoglycemia.

RESULTS

Mean QTc during hypoglycemia was significantly longer compared to euglycemia (412 ± 15 vs. 405 ± 18 ms, p = 0.005). HRV changed significantly: RMSSD (from 88 ± 57 to 73 ± 43 ms) and HF (from 54 ± 17 to 47 ± 17nu) decreased from before hypoglycemia to after nadir, while heart rate (from 69 ± 9 to 72 ± 12 bpm) and LF (from 44 ± 17 to 52 ± 21 nu) increased (p = 0.04).

CONCLUSION

A QTc lengthening effect of nocturnal hypoglycemia in children with T1D was documented. HRV changes occurred even before detection of nocturnal hypoglycemia by CGM, which may be useful for hypoglycemia prediction.

Modelling the relationship between continuously measured glucose and electrocardiographic data in adults with type 1 diabetes mellitus

INTRODUCTION

Type 1 diabetes mellitus (T1DM) is associated with earlier onset of cardiovascular disease. Recent evidence has found hyperglycaemia appears to play a greater role in this association among T1DM compared to T2DM. This study investigates the relationship between glucose and QTc (a key cardiovascular measure) using data from continuous electrocardiogram (ECG) and glucose monitors.

METHODS

Seventeen adults with T1DM were recruited at a clinical facility in Ireland. A continuous glucose monitoring system was fitted to each participant that measured glucose every 5 min for 7 days. The participants simultaneously wore a vest with sensors to measure 12-lead ECG data every 10 min for 7 days. Area under the glucose curve (AUC), proportion of time spent in hypoglycaemia and hyperglycaemia, and mean daily absolute deviation of glucose were calculated. Mixed effects ANOVA and functional regression models were fitted to the data to investigate the aggregate and time-dependent association between glucose and QTc.

RESULTS

All participants were male with an average age of 52.5 (SD 3.8) years. Those with neuropathy had a significantly higher mean QTc compared to their counterparts. Mean QTc was significantly longer during hyperglycaemia. There was a significant positive association between QTc and time spent in hyperglycaemia. A negative association was found between QTc and time spent in hypoglycaemia. A functional model suggested a positive relationship between glucose and QTc at several times during the 7-day follow-up.

CONCLUSION

This study used sensor technology to investigate, with high granularity, the temporal relationship between glucose and ECG data over one week. QTc was found to be longer on average during hyperglycaemia.

The consequences of hypoglycaemia

Hypoglycaemia (blood glucose concentration below the normal range) has been recognised as a complication of insulin treatment from the very first days of the discovery of insulin, and remains a major concern for people with diabetes, their families and healthcare professionals today. Acute hypoglycaemia stimulates a stress response that acts to restore circulating glucose, but plasma glucose concentrations can still fall too low to sustain normal brain function and cardiac rhythm. There are long-term consequences of recurrent hypoglycaemia, which are still not fully understood. This paper reviews our current understanding of the acute and cumulative consequences of hypoglycaemia in insulin-treated diabetes.

Beyond A1C-Standardization of Continuous Glucose Monitoring Reporting: Why It Is Needed and How It Continues to Evolve

Continuous glucose monitoring (CGM) systems are becoming part of standard care for type 1 diabetes, and their use is increasing for type 2 diabetes. Consensus has been reached on standardized metrics for reporting CGM data, with time in range of 70-180 mg/dL and time below 54 mg/dL recognized as the key metrics of focus for diabetes management. The ambulatory glucose profile report has emerged as the standard for visualization of CGM data and will continue to evolve to incorporate other elements such as insulin, food, and exercise data to support glycemic management.

Hypoglycaemia and Cardiovascular Disease Risk in Patients with Diabetes

Hypoglycaemia represents an important side effect of insulin therapy and insulin secretagogues. It can occur in both type 1 and type 2 diabetes mellitus patients. Also, some associations between hypoglycaemia and cardiovascular (CV) risk have been reported. Several mechanisms may be involved, including the sympathoadrenal system, hypokalaemia, endothelial dysfunction, coagulation, platelets, inflammation, atherothrombosis and impaired autonomic cardiac reflexes. This narrative review discusses the associations of hypoglycaemia with CV diseases, including coronary heart disease (CHD), cardiac arrhythmias, stroke, carotid disease and peripheral artery disease (PAD), as well as with dementia. Severe hypoglycaemia has been related to CHD, CV and all-cause mortality. Furthermore, there is evidence supporting an association between hypoglycaemia and cardiac arrhythmias, potentially predisposing to sudden death. The data linking hypoglycaemia with stroke, carotid disease and PAD is limited. Several factors may affect the hypoglycaemia-CV relationships, such as the definition of hypoglycaemia, patient characteristics, co-morbidities (including chronic kidney disease) and antidiabetic drug therapy. However, the association between hypoglycaemia and dementia is bilateral. Both the disorders are more common in the elderly; thus, glycaemic goals should be carefully selected in older patients. Further research is needed to elucidate the impact of hypoglycaemia on CV disease.

Nocturnal Hypoglycemia in Patients With Diabetes Discharged From ICUs: A Prospective Two-Center Cohort Study

OBJECTIVES

There is very limited information about glycemic control after discharge from the ICU. The aims of this study were to evaluate the prevalence of hypoglycemia in ICU survivors with type-2 diabetes and determine whether hypoglycemia is associated with cardiac arrhythmias.

DESIGN

Prospective, observational, two-center study. Participants underwent up to 5 days of simultaneous blinded continuous interstitial glucose monitoring and ambulatory 12-lead electrocardiogram monitoring immediately after ICU discharge during ward-based care. Frequency of arrhythmias, heart rate variability, and cardiac repolarization markers were compared between hypoglycemia (interstitial glucose ≤ 3.5 mmol/L) and euglycemia (5-10 mmol/L) matched for time of day.

SETTING

Mixed medical-surgical ICUs in two geographically distinct university-affiliated hospitals.

PATIENTS

Patients with type-2 diabetes who were discharged from ICU after greater than or equal to 24 hours with greater than or equal to one organ failure and were prescribed subcutaneous insulin were eligible.

MEASUREMENTS AND MAIN RESULTS

Thirty-one participants (mean ± sd, age 65 ± 13 yr, glycated hemoglobin 64 ± 22 mmol/mol) were monitored for 101 ± 32 hours post-ICU (total 3,117 hr). Hypoglycemia occurred in 12 participants (39%; 95% CI, 22-56%) and was predominantly nocturnal (40/51 hr) and asymptomatic (25/29 episodes). Participants experiencing hypoglycemia had 2.4 ± 0.7 discrete episodes lasting 45 minutes (interquartile range, 25-140 min). Glucose nadir was less than or equal to 2.2 mmol/L in 34% of episodes. The longest episode of nocturnal hypoglycemia was 585 minutes with glucose nadir less than 2.2 mmol/L. Simultaneous electrocardiogram and continuous interstitial glucose monitoring recordings were obtained during 44 hours of hypoglycemia and 991 hours of euglycemia. Hypoglycemia was associated with greater risk of bradycardia but did not affect atrial or ventricular ectopics, heart rate variability, or cardiac repolarization.

CONCLUSIONS

In ICU survivors with insulin-treated type-2 diabetes, hypoglycemia occurs frequently and is predominantly nocturnal, asymptomatic, and prolonged.

Hyperinsulinaemic hypoglycaemia in non-anaesthetized Göttingen minipigs induces a counter-regulatory endocrine response and electrocardiographic changes

The potentially fatal cardiovascular effects of hypoglycaemia are not well understood and large animal models of the counter-regulatory responses and cardiovascular consequences of insulin-induced hypoglycaemia are needed to understand the mechanisms in humans. The aim of this study was to develop a human-like minipig model of hypoglycaemia including healthy and diabetic pigs to investigate endocrine, electrocardiographic and platelet effects. Hypoglycaemia was induced using a hyperinsulinaemic, hypoglycaemic clamp and an insulin bolus protocol. Plasma glucose, glucagon, C-peptide, insulin, epinephrine and platelet aggregation responses were measured before, during and after hypoglycaemia. Continuous electrocardiographic recordings were obtained. Hypoglycaemia at a plasma glucose concentration of 0.8–1.0 mM in the clamp induced 25-fold increase in epinephrine and sixfold and threefold increase in glucagon for healthy and diabetic pigs, respectively. The hypoglycaemic clamp induced QTc-interval prolongation and increase in cardiac arrhythmias. In the bolus approach, the non-diabetic group reached plasma glucose target of 1.5 mM and QTc-interval was prolonged after insulin injection, but before glucose nadir. The diabetic group did not reach hypoglycaemic target, but still demonstrated QTc-interval prolongation. These results demonstrate effects of hyperinsulinaemic hypoglycaemia closely resembling human physiology, indicating the minipig as a translational animal model of counter-regulatory endocrine and myocardial effects of hypoglycaemia.

Cardiac arrhythmias and electrophysiologic responses during spontaneous hyperglycaemia in adults with type 1 diabetes mellitus

AIM

We examined the effect of spontaneous hyperglycaemia in adults with type 1 diabetes mellitus (T1DM) and without history of cardiovascular disease on heart rate variability (HRV), cardiac repolarisation and incidence of cardiac arrhythmias.

METHODS

Thirty-seven individuals with T1DM (age 17-50 years, 19 males, mean duration of diabetes 19.3 SD(9.6) years) underwent 96 h of simultaneous ambulatory 12-lead Holter ECG and blinded continuous interstitial glucose (IG) monitoring (CGM). HRV, QT interval and cardiac repolarisation were assessed during hyperglycaemia (IG ≥ 15 mmol/l) and compared with matched euglycaemia (IG 5-10 mmol/l) on a different day, separately during the day and night. Rates of arrhythmias were assessed by calculating incidence rate differences.

RESULTS

Simultaneous ECG and CGM data were recorded for 2395 hours. During daytime hyperglycaemia vs euglycaemia the mean QT_c interval duration was 404 SD(21)ms vs 407 SD(20)ms, P = 0.263. T-peak to T-end interval duration corrected for heart rate (T_pT_endc) shortened: 74.8 SD(16.1)ms vs 79.0 SD(14.8)ms, P = 0.033 and T-wave symmetry increased: 1.62 SD(0.33) vs 1.50 SD(0.39), P = 0.02. During night-time hyperglycaemia vs euglycaemia, the mean QT_c interval duration was 401 SD(26)ms vs 404 SD(27)ms, P = 0.13 and T_pT_end shortened: 62.4 SD(12.0)ms vs 67.1 SD(11.8)ms, P = 0.003. The number of cardiac arrhythmias was low and confined to bradycardia and isolated ectopic beats. A considerable inter-subject and diurnal variability was observed.

CONCLUSIONS

Hyperglycaemia in individuals with T1DM without known cardiovascular disease was not associated with clinically important cardiac arrhythmias.

Glucose Homeostasis, Hypoglycemia, and the Burnt-Out Diabetes Phenomenon in Kidney Disease

Chronic kidney disease (CKD) is among the most prevalent and dire complications of diabetes mellitus in adults across the world. Diabetes substantially contributes to the burden of kidney disease, such that one third to one half of CKD in the United States and many other countries is attributable to diabetic kidney disease (DKD). As DKD progresses to end-stage renal disease (ESRD), patients are at heightened risk for atypical glycemic complications, including the development of burnt-out diabetes, manifested by hypoglycemic bouts and poor outcomes. Furthermore, even in the absence of diabetes, hypoglycemia is a frequent occurrence in CKD patients that may contribute to their high burden of cardiovascular disease and death. Extrapolation of data from clinical trials in high-cardiovascular-risk populations and observational studies in patients with non-dialysis-dependent (NDD) CKD and ESRD suggest that moderate glycemic targets defined by glycated hemoglobin levels of 6% to 8% and glucose levels of 100 to 150 mg/dL are associated with better survival in DKD patients. However, given the imprecision of glycated hemoglobin levels in kidney disease, further research is needed to determine the optimal glycemic metric and target in diabetic NDD-CKD and ESRD patients. Given their exceedingly high cardiovascular morbidity and mortality, there is a compelling need for further investigation of how to optimally manage dysglycemia in the NDD-CKD and ESRD populations.

Glycemic Monitoring and Management in Advanced Chronic Kidney Disease

Glucose and insulin metabolism in patients with diabetes are profoundly altered by advanced chronic kidney disease (CKD). Risk of hypoglycemia is increased by failure of kidney gluconeogenesis, impaired insulin clearance by the kidney, defective insulin degradation due to uremia, increased erythrocyte glucose uptake during hemodialysis, impaired counterregulatory hormone responses (cortisol, growth hormone), nutritional deprivation, and variability of exposure to oral antihyperglycemic agents and exogenous insulin. Patients with end-stage kidney disease frequently experience wide glycemic excursions, with common occurrences of both hypoglycemia and hyperglycemia. Assessment of glycemia by glycated hemoglobin (HbA1c) is hampered by a variety of CKD-associated conditions that can bias the measure either to the low or high range. Alternative glycemic biomarkers, such as glycated albumin or fructosamine, are not fully validated. Therefore, HbA1c remains the preferred glycemic biomarker despite its limitations. Based on observational data for associations with mortality and risks of hypoglycemia with intensive glycemic control regimens in advanced CKD, an HbA1c range of 7% to 8% appears to be the most favorable. Emerging data on the use of continuous glucose monitoring in this population suggest promise for more precise monitoring and treatment adjustments to permit fine-tuning of glycemic management in patients with diabetes and advanced CKD.

Hypoglycaemia and cardiac arrhythmias in diabetes

Hypoglycaemia remains an inevitable risk in insulin-treated type 1 diabetes and type 2 diabetes and has been associated with multiple adverse outcomes. Whether hypoglycaemia is a cause of fatal cardiac arrhythmias in diabetes, or merely a marker of vulnerability, is still unknown. Since a pivotal report in 1991, hypoglycaemia has been suspected to induce cardiac arrhythmias in patients with type 1 diabetes, the so-called 'dead-in-bed syndrome'. This suspicion has subsequently been supported by the coexistence of an increased mortality and a three-fold increase in severe hypoglycaemia in patients with type 2 diabetes receiving intensive glucose-lowering treatment in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Studies have investigated the association between hypoglycaemia-induced cardiac arrhythmias. In a rat-model, severe hypoglycaemia resulted in a specific pattern of cardiac arrhythmias including QT-prolongation, ventricular tachycardia, second- and third-degree AV block and ultimately cardiorespiratory arrest. In clinical studies of experimentally induced hypoglycaemia, QTc-prolongation, a risk factor of ventricular arrhythmias, is an almost consistent finding. The extent of QT-prolongation seems to be modified by several factors, including antecedent hypoglycaemia, diabetes duration and cardiac autonomic neuropathy. Observational studies indicate diurnal differences in the pattern of electrocardiographic alterations during hypoglycaemia with larger QTc-prolongations during daytime, whereas the risk of bradyarrhythmias may be increased during sleep. Daytime periods of hypoglycaemia are characterized by shorter duration, increased awareness and a larger increase in catecholamines. The counterregulatory response is reduced during nightly episodes of hypoglycaemia, resulting in prolonged periods of hypoglycaemia with multiple nadirs. An initial sympathetic activity at plasma glucose nadir is replaced by increased vagal activity, which results in bradycardia. Here, we provide an overview of the existing literature exploring potential mechanisms for hypoglycaemia-induced cardiac arrhythmias and studies linking hypoglycaemia to cardiac arrhythmias in patients with diabetes.

Value of Capillary Glucose Profiles in Assessing Risk of Nocturnal Hypoglycemia in Type 1 Diabetes Based on Continuous Glucose Monitoring

INTRODUCTION

This study aimed to evaluate the occurrence of nocturnal hypoglycemia in type 1 diabetes (T1D) based on continuous glucose monitoring (CGM), and to explore the value of capillary glucose profiles in assessing the risk of nocturnal hypoglycemia. The study also intended to develop a predictive model to identify people with high risk of nocturnal hypoglycemia.

METHODS

A total of 169 participants with T1D received 3 days of blinded CGM; meanwhile, their self-monitoring blood glucose (SMBG) profiles were recorded. Logistic regression analyses were used to evaluate contributory factors of nocturnal hypoglycemia. Potential indicators were estimated using area under receiver operator curve (AUC) analyses.

RESULTS

During the retrospective CGM period, 95 (56.2%) participants with T1D reported 238 events of hypoglycemia, and 69 (29.0%) of these episodes occurred during the nighttime. Increased risk of nocturnal hypoglycemia correlated with lower HbA1c, glycated albumin, and mean blood glucose (OR = 0.790, 0.940, 0.651, respectively; P < 0.05) and higher standard deviation, mean amplitude of glycemic excursions, and low blood glucose index (OR = 1.463, 1.168, 4.035, respectively; P < 0.05) after adjustment for age and duration. Of the daily SMBG profiles, fasting blood glucose (OR = 0.643, P = 0.001) and blood glucose at bedtime (OR = 0.851, P = 0.037) were associated with the occurrence of nocturnal hypoglycemia. The BGn model, which was derived from the variation of capillary glucose, could discriminate individuals with increased risk of nocturnal hypoglycemia (AUC = 0.774).

CONCLUSIONS

Nocturnal hypoglycemia constitutes nearly one-third of hypoglycemic events in people with T1D. Strict glycemic control and great fluctuation of glucose are potential contributory factors. Daily SMBG profiles and the BGn model could help assess the risk of nocturnal hypoglycemia in T1D, which may support further development of preventive strategies.

Diabetes, Diabetic Complications, and Phosphate Toxicity: A Scoping Review

This article presents a scoping review and synthesis of research findings investigating the toxic cellular accumulation of dysregulated inorganic phosphate-phosphate toxicity-as a pathophysiological determinant of diabetes and diabetic complications. Phosphorus, an essential micronutrient, is closely linked to the cellular metabolism of glucose for energy production, and serum inorganic phosphate is often transported into cells along with glucose during insulin therapy. Mitochondrial dysfunction and apoptosis, endoplasmic reticulum stress, neuronal degeneration, and pancreatic cancer are associated with dysregulated levels of phosphate in diabetes. Ectopic calcification involving deposition of calcium-phosphate crystals is prevalent throughout diabetic complications, including vascular calcification, nephropathy, retinopathy, and bone disorders. A low-glycemic, low-phosphate dietary intervention is proposed for further investigations in the treatment and prevention of diabetes and related diabetic pathologies.

Realizing a Closed-Loop (Artificial Pancreas) System for the Treatment of Type 1 Diabetes

Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an "artificial pancreas" that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system.

Severe Hypoglycemia-Induced Fatal Cardiac Arrhythmias Are Mediated by the Parasympathetic Nervous System in Rats

The contribution of the sympathetic nervous system (SNS) versus the parasympathetic nervous system (PSNS) in mediating fatal cardiac arrhythmias during insulin-induced severe hypoglycemia is not well understood. Therefore, experimental protocols were performed in nondiabetic Sprague-Dawley rats to test the SNS with 1) adrenal demedullation and 2) chemical sympathectomy, and to test the PSNS with 3) surgical vagotomy, 4) nicotinic receptor (mecamylamine) and muscarinic receptor (AQ-RA 741) blockade, and 5) ex vivo heart perfusions with normal or low glucose, acetylcholine (ACh), and/or mecamylamine. In protocols 1-4, 3-h hyperinsulinemic (0.2 units/kg/min) and hypoglycemic (10-15 mg/dL) clamps were performed. Adrenal demedullation and chemical sympathectomy had no effect on mortality or arrhythmias during severe hypoglycemia compared with controls. Vagotomy led to a 6.9-fold decrease in mortality; reduced first- and second-degree heart block 4.6- and 4-fold, respectively; and prevented third-degree heart block compared with controls. Pharmacological blockade of nicotinic receptors, but not muscarinic receptors, prevented heart block and mortality versus controls. Ex vivo heart perfusions demonstrated that neither low glucose nor ACh alone caused arrhythmias, but their combination induced heart block that could be abrogated by nicotinic receptor blockade. Taken together, ACh activation of nicotinic receptors via the vagus nerve is the primary mediator of severe hypoglycemia-induced fatal cardiac arrhythmias.

Nocturnal ventricular arrhythmias are associated with the severity of cardiovascular autonomic neuropathy in type 2 diabetes

BACKGROUND

Cardiovascular autonomic neuropathy (CAN) is a risk factor for arrhythmias and adverse cardiovascular events, but the relationship between CAN severity and nocturnal arrhythmias needs to be clarified. This study evaluated the association between nocturnal arrhythmias and CAN severity in patients with type 2 diabetes (T2D).

METHODS

In all, 219 T2D patients were recruited from January 2017 to May 2018. Subjects were classified into no CAN (NCAN), early CAN (ECAN), definite CAN (DCAN), or advanced CAN (ACAN) based on cardiovascular autonomic reflex tests (CARTs). A 24-hour electrocardiogram was recorded and daytime (0700-2300 hours) and night-time (2300-0700 hours) heartbeats were analyzed separately.

RESULTS

After adjusting for age, the incidence of ventricular arrhythmias increased with CAN severity at night-time (18.6%, 29.9%, 36.2%, and 60.0% in the NCAN, ECAN, DCAN, and ACAN groups, respectively; P_trend  = 0.034). Patients with nocturnal ventricular arrhythmias (NVAs) had higher CART scores (2.0 ± 1.0 vs 1.5 ± 0.9; P < 0.001) and lower heart rate variability (HRV) during deep breathing (9.5 ± 5.7 vs 11.6 ± 6.6 b. p. m; P = 0.021), HRV during the Valsalva maneuver (1.2 ± 0.1 vs 1.2 ± 0.2; P = 0.006), and postural blood pressure change (-8.8 ± 15.5 vs -4.1 ± 11.2 mmHg; P = 0.023). Multivariate regression analysis revealed that CAN stage (odds ratio 1.765; 95% confidence interval 1.184-2.632; P = 0.005) was independently associated with NVAs.

CONCLUSIONS

In T2D, CAN stage was independently associated with the presence of NVAs. Early detection, diagnosis, and treatment of CAN may help predict and prevent adverse cardiovascular events and cardiovascular mortality in diabetes.

Asprosin response in hypoglycemia is not related to hypoglycemia unawareness but rather to insulin resistance in type 1 diabetes

Asprosin is a counter-regulatory hormone to insulin which plays a role in fasting. It may therefore also play a role in hypoglycaemia unawareness, which has been subsequently examined in this pilot study. Intravenous glucose tolerance test was used to induce controlled hyperglycemia whereas a hyperinsulinemic clamp test was used to induce a controlled hypoglycaemia in 15 patients with diabetes type 1, with and without hypoglycaemia unawareness. Changes in asprosin plasma levels did not differ between patients with and without hypoglycaemia unawareness. However, nine patients with insulin resistance as well as higher liver stiffness values and low-density lipoprotein but lower high-density lipoprotein levels did not show the expected increase in asprosin plasma levels during hypoglycemia. Therefore, insulin resistance and alterations in liver structure, most likely early stages of non-alcoholic fatty liver disease, seem to be relevant in type 1 diabetes and do not only lead to elevated plasma levels of asprosin, but also to a blunted asprosin response in hypoglycemia.

Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range

Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.

Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range

Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.

Risk Factors for Atrial Fibrillation in People With Type 1 Diabetes: An Observational Cohort Study of 36,258 Patients From the Swedish National Diabetes Registry

OBJECTIVE

This study identified variables associated with increased risk of atrial fibrillation in people with type 1 diabetes.

RESEARCH DESIGN AND METHODS

We performed a cohort study of people with type 1 diabetes from the Swedish National Diabetes Registry followed up between 1 January 2001 and 31 December 2013. Median follow-up was 9.7 years (interquartile range 5.2-13.0). The association between potential risk factors and incident atrial fibrillation was investigated using adjusted Cox regression. To compare the impact of each risk factor, the gradient of risk per 1 SD was estimated.

RESULTS

In this cohort of 36,258 patients with type 1 diabetes, 749 developed atrial fibrillation during follow-up. Older age, male sex, renal complications, increased BMI and HbA_1c, coronary artery disease, heart failure, and heart valve disease increased the risk of atrial fibrillation. Age, signs of renal dysfunction with macroalbuminuria, and decreasing estimated glomerular filtration rate were associated with the highest gradient of risk for atrial fibrillation. High blood pressure, severe obesity (BMI >35 kg/m²), and elevated levels of HbA_1c (>9.6%) were associated with increased risk, but no associations were found with hyperlipidemia or smoking.

CONCLUSIONS

The most prominent risk factors for atrial fibrillation in people with type 1 diabetes were older age, cardiovascular comorbidities, and renal complications, while obesity, hypertension, and hyperglycemia had more modest affects.

Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice

Use of continuous glucose monitoring (CGM) is recognized as a valuable component of diabetes self-management and is increasingly considered a standard of care for individuals with diabetes who are treated with intensive insulin therapy. As the clinical use of CGM technology expands, consistent and standardized glycemic metrics and glucose profile visualization have become increasingly important. A common set of CGM metrics has been proposed by an international expert panel in 2017, including standard definitions of time in ranges, glucose variability, and adequacy of data collection. We describe the core CGM metrics, as well as the standardized glucose profile format consolidating 2 weeks of CGM measurements, referred to as the ambulatory glucose profile (AGP), which was also recommended by the CGM expert panel. We present an updated AGP report featuring the core CGM metrics and a visualization of glucose patterns that need clinical attention. New tools for use by clinicians and patients to interpret AGP data are reviewed. Strategies based on the authors' experience in implementing CGM technology across the clinical care spectrum are highlighted.

The phenomenon of HbA1c stability and the risk of hypoglycemia in long-standing type 1 diabetes

AIMS

Hyperglycemia is the major factor underlying vascular complications of diabetes. Unfortunately, improved glycemia control is frequently accompanied by an increased risk of hypoglycemia. The aim of the study was to assess the relationship between hemoglobin A1c (HbA1c) and 1-week Continuous Glucose Monitoring (CGM) data in long-standing type 1 diabetes (T1DM).

METHODS

We recruited 58 subjects with long-standing T1DM consecutively enrolled to the study. Each patient underwent a 1-week CGM and laboratory profile at baseline. Subjects were divided into three subgroups according to baseline HbA1c tertiles: T1 < 7.1%, T2 = 7.1-8.0%, and T3 > 8.0%.

RESULTS

T1 patients were characterized by the longest time in range (66% of a week), whereas T3 patients experienced hyperglycemia in >50% time of the week. T1 patients were noted to have 25% of nighttime with glycemia <3.9 mmol/L (8% with glycemia <2.8 mmol/L). Most recent HbA1c closely reflected 10-years mean HbA1c values (R = 0.83; P < 0.0001).

CONCLUSIONS

(1) Long-term diabetes control (10 years HbA1c mean) is a strong predictor of the current HbA1c levels. (2) Current and historical HbA1c levels are closely linked to CGM-derived glycemia. (3) Risk of clinically significant hypoglycemia negatively correlates with HbA1c. (4) HbA1c > 8.0% is associated with unsatisfactorily low (44%) time in range.

The relationship between blood glucose and nocturnal supraventricular tachycardia attacks in non-diabetic patients

PURPOSE

Decrease in the blood glucose level may trigger the tachycardia or bradycardia because it has an arrhythmogenic effect on the heart. Our purpose in this study was to investigate whether the blood glucose level has an effect on patients who attended to the hospital with nocturnal supraventricular tachycardia (SVT).

METHODS

We included 151 patients in our study who have SVT history. Plasma glucose levels which were taken during night hours, electrolytes, and 12 lead electrocardiography were evaluated.

RESULTS

There were 105 patients without nocturnal SVT attack and 46 patients with nocturnal SVT attack. Patients with nocturnal SVT attack, blood glucose level, potassium, calcium, and hemoglobin levels were significantly lower, hs-CRP was significantly higher, basal cycle length (BCL) was significantly short, and QT interval was significantly longer. It was found that blood glucose (O.R. = 0.904, 95% GA 0.828-0.986, p = 0.023) and potassium levels (O.R. = 0.128, 95% GA 0.029-0.561, p = 0.006) and basal cycle length (BCL) (O.R. 0.988, 95% GA, 0.980-0.996, p = 0.005) values were in independently correlated with nocturnal SVT attacks.

CONCLUSION

The decrease in blood glucose level of the patients who are being followed with SVT diagnosis might trigger the nocturnal SVT attacks.

Hypoglycaemia, cardiovascular disease, and mortality in diabetes: epidemiology, pathogenesis, and management

Hypoglycaemia has long been recognised as a dangerous side-effect of treatment of diabetes with insulin or insulin secretagogues. With its potential to disrupt cerebral function, hypoglycaemia can have a major effect on peoples' lives. Study findings have suggested that hypoglycaemia is associated with an increased risk of cardiovascular events and mortality. Different mechanisms by which hypoglycaemia might provoke cardiovascular events have been identified in experimental studies, and in clinical studies cardiac arrhythmias have been reported to be induced by hypoglycaemia, with one report describing sudden death during a severe episode. Emerging evidence suggests that the association between hypoglycaemia and cardiovascular events and mortality is likely to be multifactorial. The association is probably partly caused by confounding, with hypoglycaemia occurring more frequently in people with comorbidities who are also more likely to die than those without. However, people with type 1 or type 2 diabetes also seem at risk of hypoglycaemia-induced cardiovascular effects. This risk should be recognised by clinicians when agreeing glycaemic goals with patients and choosing appropriate glucose-lowering therapies.

Variations in glucose/C-peptide ratio in patients with type 2 diabetes associated with renal function

INTRODUCTION

Accurate dosing of medications for glycemic control is a challenge for clinicians in diabetic patients with kidney disease. Diminishing glomerular filtration rates are associated with decreased renal clearance of insulin and increased prevalence of hypoglycemic episodes. Measurement of glucose/C peptide ratios may be useful to guide dosing in those patients who receive powerful insulin secretogogues as glomerular function decreases with age and disease.

METHODS

In order to determine the relationship between glucose, C-peptide and renal function, we reviewed the records of patients with type 2 diabetes followed in our kidney hypertension clinic who met the following criteria: age 35-90 years, requirement of medications to control glycemia, at least 4 simultaneous measurements of C peptide, HbA1c, creatinine and blood glucose.

RESULTS

87 patients (67 males, 20 females), ages 67.1 ± 10.6 years, BMI 32.5 ± 5.2, A1c 8.2 ± 1.2%, eGFR 73 ± 27.2 ml/min, had glucose/C-peptide ratios 60.7 ± 46.4. 59% of the total group were taking insulin secretogogues. Patients were divided into groups based upon mean eGFR and use or absence of insulin secretogogues. Glucose C-peptide ratios were lowest in the quartile of patients with the lowest eGFR (<50 ml/min).

CONCLUSION

Diminished renal function and advanced age are associated with the lowest glucose/C-peptide ratios, independent of achieved glycemic control. With similar use of secretogogues, glucose/C-peptide ratio were lower when eGFR was ≤49 ml/min compared to >50-80 ml/min. Use of secretogogues was associated with decreased glucose/C-peptide levels. In patients with reduced renal function (eGFR < 50 ml/min), use of insulin secretogogues may be associated with lower glucose/C-peptide ratios associated with higher risks for hypoglycemic reactions.