Sudden cardiac death in young patients with diabetes: a call to study additional causes beyond ischaemic heart disease

Urban-rural disparity in heatwave effects on diabetes mortality in eastern China: A case-crossover analysis in 2016-2019

Diabetics are sensitive to high ambient temperature due to impaired thermoregulation. However, available evidence on the impact of prolonged high temperature (i.e., heatwave) on diabetes deaths is limited and whether urban and rural areas differ in heatwave vulnerability remains unknown so far. A time-stratified case-crossover analysis was employed to estimate the association between heatwaves and diabetes deaths in 1486 districts (509 urban and 977 rural areas) of eastern China (Jiangsu Province), 2016-2019. For each decedent, residential heatwave exposure was measured by matching daily mean temperatures to the geocoded residential address. We adopted nine-tiered heatwave definitions incorporating intensity and duration. Stratified analyses by decedents' characteristics (gender, age, and education) were also conducted. During the study period, there were 18,685 deaths from diabetes (urban proportion: 36.95 %, p-value for urban-rural difference < 0.05). Heatwaves were associated with an increased risk of diabetes deaths, with greater and longer-lasting effects in rural areas than urban areas [e.g., rural odds ratio (OR): 1.19 (95 % confidence interval (CI): 1.14, 1.25) vs. urban OR: 1.09 (95 % CI: 1.05, 1.12)]. Risk of diabetes deaths increased with the intensity of heatwaves in rural areas (p-value for trend <0.01), but not in urban areas. Stratified analyses in rural areas suggested that females and less-educated people were more vulnerable to heatwave-related diabetes deaths. Our findings revealed the urban-rural disparity in the risk of diabetes deaths associated with heatwaves. Rural diabetics should be made aware of the increased death risk posed by heatwaves in the context of warming climate.

Identification of myocardial fibrosis by ATR-FTIR spectroscopy combined with chemometrics

Different degrees of myocardial fibrosis can often be observed in sudden cardiac death cases, so that the identification of myocardial fibrosis is an important step in forensics to identify cardiac death. Previous methods are restricted by complex algorithms, high cost, low sensitivity and high requirements. Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy is an efficient and rapid method to identify tissue types, which has been used increasingly in forensics. This study aims to identify novel biophysical biomarkers of myocardial fibrosis and establish a prediction model by using ATR-FTIR analysis combined with chemometrics. A total of 129 tissue blocks taken from human hearts were cut into slices, and then ATR-FTIR spectroscopy and hematoxylin and eosin (HE) staining were performed. By using HE staining, the samples were divided into the experimental group (with myocardial fibrosis) and the control group (without myocardial fibrosis). The chemometrics classification results showed that the sensitivity and specificity of the training dataset were 0.91 and 1.0 respectively, and the sensitivity and specificity of the predictive dataset were 0.862 and 0.900. This study demonstrated that ATR-FTIR spectroscopy combined with chemometrics is a novel method for identifying myocardial fibrosis.

Temporal variation in out-of-hospital cardiac arrest occurrence in individuals with or without diabetes

Objective

Out-of-hospital cardiac arrest (OHCA) occurrence has been shown to exhibit a circadian rhythm, following the circadian rhythm of acute myocardial infarction (AMI) occurrence. Diabetes mellitus (DM) is associated with changes in circadian rhythm. We aimed to compare the temporal variation of OHCA occurrence over the day and week between OHCA patients with DM and those without.

Methods

In two population-based OHCA registries (Amsterdam Resuscitation Studies [ARREST] 2010-2016, n = 4163, and Danish Cardiac Arrest Registry [DANCAR], 2010-2014, n = 12,734), adults (≥18y) with presumed cardiac cause of OHCA and available medical history were included. Single and double cosinor analysis was performed to model circadian variation of OHCA occurrence. Stratified analysis of circadian variation was performed in patients with AMI as immediate cause of OHCA.

Results

DM patients (22.8% in ARREST, 24.2% in DANCAR) were older and more frequently had cardiovascular risk factors or previous cardiovascular disease. Both cohorts showed 24 h-rhythmicity, with significant amplitudes in single and double cosinor functions (P-range < 0.001). In both registries, a morning peak (10:00-11:00) and an evening peak (20:00-21:00) was observed in both DM and non-DM patients. No septadian variation was observed in either DM or non-DM patients (P-range 0.13-84).

Conclusions

In these two population-based OHCA registries, we observed a similar circadian rhythm of OHCA occurrence in DM and non-DM patients.

Quantitative Analysis of Different Multi-Wavelength PPG Devices and Methods for Noninvasive In-Vivo Estimation of Glycated Hemoglobin

Diabetes is a serious disease affecting the insulin cycle in the human body. Thus, monitoring blood glucose levels and the diagnosis of diabetes in the early stages is very important. Noninvasive in vivo diabetes-diagnosis procedures are very new and require thorough studies to be error-resistant and user-friendly. In this study, we compare two noninvasive procedures (two-wavelength- and three-wavelength-based methods) to estimate glycated hemoglobin (HbA1c) levels in different scenarios and evaluate them with error level calculations. The three-wavelength method, which has more model parameters, results in a more accurate estimation of HbA1c even when the blood oxygenation (SpO2) values change. The HbA1c-estimation error range of the two-wavelength model, due to change in SpO2, is found to be from −1.306% to 0.047%. On the other hand, the HbA1c estimation error for the three-wavelength model is found to be in the magnitude of 10−14% and independent of SpO2. The approximation of SpO2 from the two-wavelength model produces a lower error for the molar concentration based technique (−4% to −1.9% at 70% to 100% of reference SpO2) as compared to the molar absorption coefficient based technique. Additionally, the two-wavelength model is less susceptible to sensor noise levels (max SD of %error, 0.142%), as compared to the three-wavelength model (max SD of %error, 0.317%). Despite having a higher susceptibility to sensor noise, the three-wavelength model can estimate HbA1c values more accurately; this is because it takes the major components of blood into account and thus becomes a more realistic model.

Diabetes and the Risk of Sudden Cardiac Death

PURPOSE OF REVIEW

Persons with diabetes mellitus (DM) have increased morbidity and mortality rates compared with persons without DM. Sudden cardiac death (SCD) is a leading cause of death, and multiple studies have found an increased risk of SCD among individuals with DM. This review sought to collect the latest knowledge of the epidemiological and pathophysiological interplay between DM and SCD.

RECENT FINDINGS

Persons with DM have a two- to tenfold increased risk of SCD compared with persons without DM. The underlying mechanisms for the increased risk of SCD are complex and multifactorial. The main pathophysiological contributors are DM-induced cardiac autonomic neuropathy (CAN), metabolic changes, silent ischemia, and polypharmacy. Persons with DM have an increased risk of SCD. Future studies should focus on CAN and the combined risk of QT prolongation from the interplay between CAN, hypoglycemia, and polypharmacy. Genes and pathways involved in control of the autonomic nervous system and cardiac ion channels could be a future focal point.