Significant abnormal glycemic variability increased the risk for arrhythmias in elderly type 2 diabetic patients

Ageing well with diabetes: the role of technology

Over the past two decades there has been a substantial rise in the adoption of diabetes therapeutic technology among children, adolescents and younger adults with type 1 diabetes, and its use is now also advocated for older individuals. Older people with diabetes are more prone to experience hypoglycaemia because of numerous predisposing factors and are at higher risk of hypoglycaemic events requiring third-party assistance as well as other adverse sequelae. Hypoglycaemia may also have long-term consequences, including cognitive impairment, frailty and disability. Diabetes in older people is often characterised by marked glucose variability related to age-associated changes such as variable appetite and levels of physical activity, comorbidities and polypharmacotherapy. Preventing hypoglycaemia and mitigating glucose excursions may have considerable positive impacts on physical and cognitive function and general well-being and may even prevent or improve frailty. Technology for older people includes continuous glucose monitoring systems, insulin pumps, automated insulin delivery systems and smart insulin pens. Clinical trials and real-world studies have shown that older people with diabetes benefit from technology in terms of glucose management, reductions in hypoglycaemic events, emergency department attendance and hospital admissions, and improvement in quality of life. However, ageing may bring physical impairments and other challenges that hinder the use of technology. Healthcare professionals should identify older adults with diabetes who may benefit from therapeutic technology and then adopt an individualised approach to education and follow-up for individuals and their caregivers. Future research should explore the impact of diabetes technology on outcomes relevant to older people with diabetes.

Short-term Glycemic Variability and Its Association With Macrovascular and Microvascular Complications in Patients With Diabetes

The introduction of continuous glucose monitoring inaugurated a new era in clinical practice by shifting the characterization of glycemic control from HbA1c to novel metrics. The one that gained widespread attention over the past decades was glycemic variability (GV), which typically refers to peaks and nadirs of blood glucose measured over a given time interval. GV can be dichotomized into two main categories: short-term and long-term. Short-term GV reflects within-day and between-day glycemic oscillations, and its contribution to diabetic complications remains an enigma. In this review, we summarize the available data about short-term GV and its possible association with both microvascular and macrovascular complications, evaluating different pathogenic mechanisms and demonstrating nonpharmaceutical, as well as pharmaceutical, therapeutic interventions.

Glucose fluctuations aggravated the late sodium current induced ventricular arrhythmias via the activation of ROS/CaMKII pathway

BACKGROUND

Recent evidence revealed that glucose fluctuation might be more likely to cause arrhythmia than persistent hyperglycemia, whereas its mechanisms were elusive. We aimed to investigate the effect of glucose fluctuation on the occurrence of ventricular arrhythmia and its mechanism.

METHODS

Streptozotocin (STZ) induced diabetic rats were randomized to five groups: the controlled blood glucose (C-STZ) group, uncontrolled blood glucose (U-STZ) group, fluctuated blood glucose (GF-STZ) group, and GF-STZ rats with 100 mg/kg Tempol (GF-STZ + Tempol) group or with 5 mg/kg KN93 (GF-STZ + KN93) group. Six weeks later, the susceptibility of ventricular arrhythmias and the electrophysiological dysfunctions of ventricular myocytes were evaluated using electrocardiogram and patch-clamp technique, respectively. The levels of reactive oxygen species (ROS) and oxidized CaMKII (ox-CaMKII) were determined by fluorescence assay and Western blot, respectively. Neonatal rat cardiomyocytes and H9C2 cells in vitro were used to explore the underlying mechanisms.

RESULTS

The induction rate of ventricular arrhythmias was 10%, 55%, and 90% in C-STZ group, U-STZ group, and GF-STZ group, respectively (P < 0.05). The electrophysiological dysfunctions of ventricular myocytes, including action potential duration at repolarization of 90% (APD90), APD90 short-term variability (APD90-STV), late sodium current (INa-L), early after depolarization (EAD) and delayed after depolarizations (DAD), as well as the levels of ROS and ox-CaMKII, were significantly increased in GF-STZ group. In vivo and ex vivo, inhibition of ROS or ox-CaMKII reversed these effects. Inhibition of INa-L also significantly alleviated the electrophysiological dysfunctions. In vitro, inhibition of ROS increase could significantly decrease the ox-CaMKII activation induced by glucose fluctuations.

CONCLUSIONS

Glucose fluctuations aggravated the INa-L induced ventricular arrhythmias though the activation of ROS/CaMKII pathway.

Glucose fluctuations aggravate myocardial fibrosis via activating the CaMKII/Stat3 signaling in type 2 diabtetes

BACKGROUND

Glucose fluctuations (GF) are a risk factor for cardiovascular complications associated with type 2 diabetes. However, there is a lack of adequate research on the effect of GF on myocardial fibrosis and the underlying mechanisms in type 2 diabetes. This study aimed to investigate the impact of glucose fluctuations on myocardial fibrosis and explore the potential mechanisms in type 2 diabetes.

METHODS

Sprague Dawley (SD) rats were randomly divided into three groups: the control (Con) group, the type 2 diabetic (DM) group and the glucose fluctuations (GF) group. The type 2 diabetic rat model was established using a high-fat diet combined with low-dose streptozotocin injection and the GF model was induced by using staggered glucose and insulin injections daily. After eight weeks, echocardiography was used to assess the cardiac function of the three groups. Hematoxylin-eosin and Masson staining were utilized to evaluate the degree of pathological damage and fibrosis. Meanwhile, a neonatal rat cardiac fibroblast model with GF was established. Western and immunofluorescence were used to find the specific mechanism of myocardial fibrosis caused by GF.

RESULTS

Compared with rats in the Con and the DM group, cardiac function in the GF group showed significant impairments. Additionally, the results showed that GF aggravated myocardial fibrosis in vitro and in vivo. Moreover, Ca2+/calmodulin‑dependent protein kinase II (CaMKII) was activated by phosphorylation, prompting an increase in phosphorylation of signal transducer and activator of transcription 3 (Stat3) and induced nuclear translocation. Pretreatment with KN-93 (a CaMKII inhibitor) blocked GF-induced Stat3 activation and significantly suppressed myocardial fibrosis.

CONCLUSIONS

Glucose fluctuations exacerbate myocardial fibrosis by triggering the CaMKII/Stat3 pathway in type 2 diabetes.

Dysglycemia and arrhythmias

Disorders in glucose metabolism can be divided into three separate but interrelated domains, namely hyperglycemia, hypoglycemia, and glycemic variability. Intensive glycemic control in patients with diabetes might increase the risk of hypoglycemic incidents and glucose fluctuations. These three dysglycemic states occur not only amongst patients with diabetes, but are frequently present in other clinical settings, such as during critically ill. A growing body of evidence has focused on the relationships between these dysglycemic domains with cardiac arrhythmias, including supraventricular arrhythmias (primarily atrial fibrillation), ventricular arrhythmias (malignant ventricular arrhythmias and QT interval prolongation), and bradyarrhythmias (bradycardia and heart block). Different mechanisms by which these dysglycemic states might provoke cardiac arr-hythmias have been identified in experimental studies. A customized glycemic control strategy to minimize the risk of hyperglycemia, hypoglycemia and glucose variability is of the utmost importance in order to mitigate the risk of cardiac arrhythmias.

Glycemic variability and in-hospital death of critically ill patients and the role of ventricular arrhythmias

BACKGROUND

Abnormal glycemic variability is common in the intensive care unit (ICU) and is associated with increased in-hospital mortality and major adverse cardiovascular events, but little is known about whether adverse outcomes are partly mediated by ventricular arrhythmias (VA). We aimed to explore the association between glycemic variability and VA in the ICU and whether VA related to glycemic variability mediate the increased risk of in-hospital death.

METHODS

We extracted all measurements of blood glucose during the ICU stay from The Medical Information Mart for Intensive Care IV (MIMIC-IV) database version 2.0. Glycemic variability was expressed by the coefficient of variation (CV), which was calculated by the ratio of standard deviation (SD) and average blood glucose values. The outcomes included the incidence of VA and in-hospital death. The KHB (Karlson, KB & Holm, A) is a method to analyze the mediation effect for nonlinear models, which was used to decompose the total effect of glycemic variability on in-hospital death into a direct and VA-mediated indirect effect.

RESULTS

Finally, 17,756 ICU patients with a median age of 64 years were enrolled; 47.2% of them were male, 64.0% were white, and 17.8% were admitted to the cardiac ICU. The total incidence of VA and in-hospital death were 10.6% and 12.8%, respectively. In the adjusted logistic model, each unit increase in log-transformed CV was associated with a 21% increased risk of VA (OR 1.21, 95% CI: 1.11-1.31) and a 30% increased risk (OR 1.30, 95% CI: 1.20-1.41) of in-hospital death. A total of 3.85% of the effect of glycemic variability on in-hospital death was related to the increased risk of VA.

CONCLUSION

High glycemic variability was an independent risk factor for in-hospital death in ICU patients, and the effect was caused in part by an increased risk of VA.

Relationship Between Time in Range and Dusk Phenomenon in Outpatients with Type 2 Diabetes Mellitus

Purpose

The dusk phenomenon refers to a spontaneous and transient pre-dinner hyperglycemia that affects glucose fluctuation and glycemic control, and the increasing use of continuous glucose monitoring (CGM) has facilitated its diagnosis. We investigated the frequency of the dusk phenomenon and its relationship with the time in range (TIR) in patients with type 2 diabetes mellitus (T2DM).

Patients and Methods

This study involved 102 patients with T2DM who underwent CGM for 14 days. CGM-derived metrics and clinical characteristics were evaluated. A consecutive dusk blood glucose difference (pre-dinner glucose minus 2-hour post-lunch glucose) of ≥ 0 or once-only dusk blood glucose difference of < 0 was diagnosed as the clinical dusk phenomenon (CLDP).

Results

We found that the percentage of CLDP was 11.76% (10.34% in men, 13.64% in women). Compared with the non-CLDP group, the CLDP group tended to be younger and have a lower percentage of TIR (%TIR^3.9-10) and higher percentage of time above range (%TAR^>10 and %TAR^>13.9) (P ≤ 0.05). Adjusted for confounding factors, the binary logistic regression analysis showed a negative association of CLDP with %TIR (odds ratio < 1, P < 0.05). We repeated the correlation analysis based on 70%TIR and found significant differences in hemoglobin A1c, fasting blood glucose, mean blood glucose, standard deviation of the sensor glucose values, glucose coefficient of variation, largest amplitude of glycemic excursions, mean amplitude of glycemic excursions, glucose management indicator, and percentage of CLDP between the two subgroups of TIR ≤ 70% and TIR > 70% (P < 0.05). The negative association between TIR and CLDP still remained after adjustment by the binary logistic regression analysis.

Conclusion

The CLDP was frequently present in patients with T2DM. The TIR was significantly correlated with the CLDP and could serve as an independent negative predictor.

Management of Type 2 Diabetes Mellitus in Elderly Patients with Frailty and/or Sarcopenia

The life expectancy of the population is increasing worldwide due to improvements in the prevention, diagnosis, and treatment of diseases. This favors a higher prevalence of type 2 diabetes mellitus (T2DM) in the elderly. Sarcopenia and frailty are also frequently present in aging. These three entities share common mechanisms such as insulin resistance, chronic inflammation, and mitochondrial dysfunction. The coexistence of these situations worsens the prognosis of elderly patients. In this paper, we review the main measures for the prevention and management of sarcopenia and/or frailty in elderly patients with T2DM.

Celebrities in the heart, strangers in the pancreatic beta cell: Voltage-gated potassium channels Kv 7.1 and Kv 11.1 bridge long QT syndrome with hyperinsulinaemia as well as type 2 diabetes

Voltage‐gated potassium (K_v) channels play an important role in the repolarization of a variety of excitable tissues, including in the cardiomyocyte and the pancreatic beta cell. Recently, individuals carrying loss‐of‐function (LoF) mutations in KCNQ1, encoding K_v7.1, and KCNH2 (hERG), encoding K_v11.1, were found to exhibit post‐prandial hyperinsulinaemia and episodes of hypoglycaemia. These LoF mutations also cause the cardiac disorder long QT syndrome (LQTS), which can be aggravated by hypoglycaemia. Interestingly, patients with LQTS also have a higher burden of diabetes compared to the background population, an apparent paradox in relation to the hyperinsulinaemic phenotype, and KCNQ1 has been identified as a type 2 diabetes risk gene. This review article summarizes the involvement of delayed rectifier K⁺ channels in pancreatic beta cell function, with emphasis on K_v7.1 and K_v11.1, using the cardiomyocyte for context. The functional and clinical consequences of LoF mutations and polymorphisms in these channels on blood glucose homeostasis are explored using evidence from pre‐clinical, clinical and genome‐wide association studies, thereby evaluating the link between LQTS, hyperinsulinaemia and type 2 diabetes.