Association of hyperglycemia with reduced heart rate variability (The Framingham Heart Study)

Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science

This updated guideline replaces the "Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science" first published in 2014. Based on the older version of the guideline, the authors have reviewed and evaluated the findings on the use of heart rate (HR) and heart rate variability (HRV) that have been published in the meantime and incorporated them into a new version of this guideline.This guideline was developed for application in clinical practice and research purposes in the fields of occupational medicine and occupational science to complement evaluation procedures with respect to exposure and risk assessment at the workplace by the use of objective physiological workload indicators. In addition, HRV is also suitable for assessing the state of health and for monitoring the progress of illnesses and preventive medical measures. It gives an overview of factors influencing the regulation of the HR and HRV at rest and during work. It further illustrates methods for measuring and analyzing these parameters under standardized laboratory and real workload conditions, areas of application as well as the quality control procedures to be followed during the recording and evaluation of HR and HRV.

Healthy lifestyle and essential metals attenuated association of polycyclic aromatic hydrocarbons with heart rate variability in coke oven workers

Whether adopting healthy lifestyles and maintaining moderate levels of essential metals could attenuate the reduction of heart rate variability (HRV) related to polycyclic aromatic hydrocarbons (PAHs) exposure are largely unknown. In this study, we measured urinary metals and PAHs as well as HRV, and constructed a healthy lifestyle score in 1267 coke oven workers. Linear regression models were used to explore the association of healthy lifestyle score and essential metals with HRV, and interaction analysis was performed to investigate the potential interaction between healthy lifestyle score, essential metals, and PAHs on HRV. Mean age of the participants was 41.9 years (84.5% male). Per one point higher healthy lifestyle score was associated with a 2.5% (95% CI, 1.0%-3.9%) higher standard deviation of all normal to normal intervals (SDNN), 2.1% (95% CI, 0.5%-3.6%) higher root mean square of successive differences in adjacent NN intervals (r-MSSD), 4.3% (95% CI, 0.4%-8.2%) higher low frequency, 4.4% (95% CI, 0.2%-8.5%) higher high frequency, and 4.4% (95% CI, 1.2%-7.6%) higher total power, respectively. Urinary level of chromium was positively associated with HRV indices, with the corresponding β (95% CI) (%) was 5.17 (2.84, 7.50) for SDNN, 4.29 (1.74, 6.84) for r-MSSD, 12.26 (6.08, 18.45) for low frequency, 12.61 (5.87, 19.36) for high frequency, and 11.31 (6.19, 16.43) for total power. Additionally, a significant interaction was found between healthy lifestyle score and urinary total hydroxynaphthalene on SDNN (Pinteraction = 0.04), and higher level of urinary chromium could attenuate the adverse effect of total hydroxynaphthalene level on HRV (all Pinteraction <0.05). Findings of our study suggest adopting healthy lifestyle and maintaining a relatively high level of chromium might attenuate the reduction of HRV related to total hydroxynaphthalene exposure.

Detection of Hypoglycemia and Hyperglycemia Using Noninvasive Wearable Sensors: Electrocardiograms and Accelerometry

BACKGROUND

Monitoring glucose excursions is important in diabetes management. This can be achieved using continuous glucose monitors (CGMs). However, CGMs are expensive and invasive. Thus, alternative low-cost noninvasive wearable sensors capable of predicting glycemic excursions could be a game changer to manage diabetes.

METHODS

In this article, we explore two noninvasive sensor modalities, electrocardiograms (ECGs) and accelerometers, collected on five healthy participants over two weeks, to predict both hypoglycemic and hyperglycemic excursions. We extract 29 features encompassing heart rate variability features from the ECG, and time- and frequency-domain features from the accelerometer. We evaluated two machine learning approaches to predict glycemic excursions: a classification model and a regression model.

RESULTS

The best model for both hypoglycemia and hyperglycemia detection was the regression model based on ECG and accelerometer data, yielding 76% sensitivity and specificity for hypoglycemia and 79% sensitivity and specificity for hyperglycemia. This had an improvement of 5% in sensitivity and specificity for both hypoglycemia and hyperglycemia when compared with using ECG data alone.

CONCLUSIONS

Electrocardiogram is a promising alternative not only to detect hypoglycemia but also to predict hyperglycemia. Supplementing ECG data with contextual information from accelerometer data can improve glucose prediction.

An association between heart rate variability and incident heart failure in an elderly cohort

BACKGROUND

Early identification of individuals at risk of developing heart failure (HF) may improve poor prognosis. A dominant sympathetic activity is common in HF and associated with worse outcomes; however, less is known about the autonomic balance before HF.

HYPOTHESIS

A low frequency/high frequency (L-F/H-F) ratio, index of heart rate variability, and marker of the autonomic balance predict the development of HF and may improve the performance of the HF prediction model when added to traditional cardiovascular (CV) risk factors.

METHODS

Individuals in the PIVUS (Prospective Investigation of the Vasculature in Uppsala Seniors) study (n = 1016, all aged 70 years) were included. Exclusion criteria were prevalent HF, electrocardiographic QRS duration ≥130 millisecond, major arrhythmias, or conduction blocks at baseline. The association between the L-F/H-F ratio and incident HF was assessed using Cox proportional hazard analysis. The C-statistic evaluated whether adding the L-F/H-F-ratio to traditional CV risk factors improved the discrimination of incident HF.

RESULTS

HF developed in 107/836 study participants during 15 years of follow-up. A nonlinear, inverse association between the L-F/H-F ratio and incident HF was mainly driven by an L-F/H-F ratio of <30. The association curve was flat for higher values (hazard ratio, HR for the total curve = 0.78 [95% confidence interval, CI: 0.69-0.88, p < .001]; HR = 2 for L-F/H-F ratio = 10). The traditional prediction model improved by 3.3% (p < .03) when the L-F/H-F ratio was added.

CONCLUSIONS

An L-F/H-F ratio of <30 was related to incident HF and improved HF prediction when added to traditional CV risk factors.

Innervation of the pancreas in development and disease

The autonomic nervous system innervates the pancreas by sympathetic, parasympathetic and sensory branches during early organogenesis, starting with neural crest cell invasion and formation of an intrinsic neuronal network. Several studies have demonstrated that signals from pancreatic neural crest cells direct pancreatic endocrinogenesis. Likewise, autonomic neurons have been shown to regulate pancreatic islet formation, and have also been implicated in type I diabetes. Here, we provide an overview of recent progress in mapping pancreatic innervation and understanding the interactions between pancreatic neurons, epithelial morphogenesis and cell differentiation. Finally, we discuss pancreas innervation as a factor in the development of diabetes.

The Vagus Nerve Regulates Immunometabolic Homeostasis in the Ovine Fetus near Term: The Impact on Terminal Ileum

BACKGROUND

Glucosensing elements are widely distributed throughout the body and relay information about circulating glucose levels to the brain via the vagus nerve. However, while anatomical wiring has been established, little is known about the physiological role of the vagus nerve in glucosensing. The contribution of the vagus nerve to inflammation in the fetus is poorly understood. Increased glucose levels and inflammation act synergistically when causing organ injury, but their interplay remains incompletely understood. We hypothesized that vagotomy (Vx) will trigger a rise in systemic glucose levels and this will be enhanced during systemic and organ-specific inflammation. Efferent vagus nerve stimulation (VNS) should reverse this phenotype.

METHODS

Near-term fetal sheep (n = 57) were surgically prepared using vascular catheters and ECG electrodes as the control and treatment groups (lipopolysaccharide (LPS), Vx + LPS, Vx + LPS + selective efferent VNS). The experiment was started 72 h postoperatively to allow for post-surgical recovery. Inflammation was induced with LPS bolus intravenously (LPS group, 400 ng/fetus/day for 2 days; n = 23). For the Vx + LPS group (n = 11), a bilateral cervical vagotomy was performed during surgery; of these n = 5 received double the LPS dose, LPS800. The Vx + LPS + efferent VNS group (n = 8) received cervical VNS probes bilaterally distal from Vx in eight animals. Efferent VNS was administered for 20 min on days 1 and 2 +/10 min around the LPS bolus. Fetal arterial blood samples were drawn on each postoperative day of recovery (-72 h, -48 h, and -24 h) as well as at the baseline and seven selected time points (3-54 h) to profile inflammation (ELISA IL-6, pg/mL), insulin (ELISA), blood gas, and metabolism (glucose). At 54 h post-LPS, a necropsy was performed, and the terminal ileum macrophages' CD11c (M1 phenotype) immunofluorescence was quantified to detect inflammation. The results are reported for p < 0.05 and for Spearman R2 > 0.1. The results are presented as the median (IQR).

RESULTS

Across the treatment groups, blood gas and cardiovascular changes indicated mild septicemia. At 3 h in the LPS group, IL-6 peaked. That peak was decreased in the Vx + LPS400 group and doubled in the Vx + LPS800 group. The efferent VNS sped up the reduction in the inflammatory response profile over 54 h. The M1 macrophage activity was increased in the LPS and Vx + LPS800 groups only. The glucose and insulin concentrations in the Vx + LPS group were, respectively, 1.3-fold (throughout the experiment) and 2.3-fold higher vs. control (at 3 h). The efferent VNS normalized the glucose concentrations.

CONCLUSIONS

The complete withdrawal of vagal innervation resulted in a 72-h delayed onset of a sustained increase in glucose for at least 54 h and intermittent hyperinsulinemia. Under the conditions of moderate fetal inflammation, this was related to higher levels of gut inflammation. The efferent VNS reduced the systemic inflammatory response as well as restored both the concentrations of glucose and the degree of terminal ileum inflammation, but not the insulin concentrations. Supporting our hypothesis, these findings revealed a novel regulatory, hormetic, role of the vagus nerve in the immunometabolic response to endotoxin in near-term fetuses.

Validity and Efficacy of the Elite HRV Smartphone Application during Slow-Paced Breathing

Slow-paced breathing is a clinical intervention used to increase heart rate variability (HRV). The practice is made more accessible via cost-free smartphone applications like Elite HRV. We investigated whether Elite HRV can accurately measure and augment HRV via its slow-paced breathing feature. Twenty young adults completed one counterbalanced cross-over protocol involving 10 min each of supine spontaneous (SPONT) and paced (PACED; 6 breaths·min-1) breathing while RR intervals were simultaneously recorded via a Polar H10 paired with Elite HRV and reference electrocardiography (ECG). Individual differences in HRV between devices were predominately skewed, reflecting a tendency for Elite HRV to underestimate ECG-derived values. Skewness was typically driven by a limited number of outliers as median bias values were ≤1.3 ms and relative agreement was ≥very large for time-domain parameters. Despite no significant bias and ≥large relative agreement for frequency-domain parameters, limits of agreement (LOAs) were excessively wide and tended to be wider during PACED for all HRV parameters. PACED significantly increased low-frequency power (LF) for Elite HRV and ECG, and between-condition differences showed very large relative agreement. Elite HRV-guided slow-paced breathing effectively increased LF values, but it demonstrated greater precision during SPONT and in computing time-domain HRV.

Evaluation of measurement accuracy of wearable devices for heart rate variability

This paper proposed a method based on heart rate variability (HRV) for evaluating the accuracy of wearable devices in measuring heart rate. HRV refers to the variation in time intervals between successive heartbeats, widely used in many fields such as clinical and sports fields. Wearable devices such as Electrocardiogram (ECG) electrode patches have gained popularity due to their portability and ease of use. However, they can be prone to measurement interference caused by environmental noise, human respiration, etc. The proposed method consists of four main components: selection of "gold standard measurement devices", identification of HRV measurement metrics, construction of an HRV evaluation framework, and quantification of measurement errors. The method is validated through simulated experiments using ECG patches. The evaluation framework and quantification model established in this method have significant implications in establishment of industry standards and diagnosis of diseases in clinical practice.

Combining Celiac and Hepatic Vagus Nerve Neuromodulation Reverses Glucose Intolerance and Improves Glycemic Control in Pre- and Overt-Type 2 Diabetes Mellitus

Neurological disorders and type 2 diabetes mellitus (T2DM) are deeply intertwined. For example, autonomic neuropathy contributes to the development of T2DM and continued unmanaged T2DM causes further progression of nerve damage. Increasing glycemic control has been shown to prevent the onset and progression of diabetic autonomic neuropathies. Neuromodulation consisting of combined stimulation of celiac vagal fibers innervating the pancreas with concurrent electrical blockade of neuronal hepatic vagal fibers innervating the liver has been shown to increase glycemic control in animal models of T2DM. The present study demonstrated that the neuromodulation reversed glucose intolerance in alloxan-treated swine in both pre- and overt stages of T2DM. This was demonstrated by improved performance on oral glucose tolerance tests (OGTTs), as assessed by area under the curve (AUC). In prediabetic swine (fasting plasma glucose (FPG) range: 101-119 mg/dL) the median AUC decreased from 31.9 AUs (IQR = 28.6, 35.5) to 15.9 AUs (IQR = 15.1, 18.3) p = 0.004. In diabetic swine (FPG range: 133-207 mg/dL) the median AUC decreased from 54.2 AUs (IQR = 41.5, 56.6) to 16.0 AUs (IQR = 15.4, 21.5) p = 0.003. This neuromodulation technique may offer a new treatment for T2DM and reverse glycemic dysregulation at multiple states of T2DM involved in diabetic neuropathy including at its development and during progression.

Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling

Wearable biosensors and smartphone applications can measure physiological variables over multiple days in free-living conditions. We measure food and drink ingestion, glucose dynamics, physical activity, heart rate (HR), and heart rate variability (HRV) in 25 healthy participants over 14 days. We develop a Bayesian inference framework to learn personal parameters that quantify circadian rhythms and physiological responses to external stressors. Modeling the effects of ingestion events on glucose levels reveals that slower glucose decay kinetics elicit larger postprandial glucose spikes, and we uncover a circadian baseline rhythm for glucose with high amplitudes in some individuals. Physical activity and circadian rhythms explain as much as 40%-65% of the HR variance, whereas the variance explained for HRV is more heterogeneous across individuals. A more complex model incorporating activity, HR, and HRV explains up to 15% of additional glucose variability, highlighting the relevance of integrating multiple biosensors to better predict glucose dynamics.

Signal Quality Analysis of Single-Arm Electrocardiography

The number of people experiencing mental stress or emotional dysfunction has increased since the onset of the COVID-19 pandemic, as many individuals have had to adapt their daily lives. Numerous studies have demonstrated that mental health disorders can pose a risk for certain diseases, and they are also closely associated with the problem of mental workload. Now, wearable devices and mobile health applications are being utilized to monitor and assess individuals' mental health conditions on a daily basis using heart rate variability (HRV), typically measured by the R-to-R wave interval (RRI) of an electrocardiogram (ECG). However, portable or wearable ECG devices generally require two electrodes to perform bipolar limb leads, such as the Einthoven triangle. This study aims to develop a single-arm ECG measurement method, with lead I ECG serving as the gold standard. We conducted static and dynamic experiments to analyze the morphological performance and signal-to-noise ratio (SNR) of the single-arm ECG. Three morphological features were defined, RRI, the duration of the QRS complex wave, and the amplitude of the R wave. Thirty subjects participated in this study. The results indicated that RRI exhibited the highest cross-correlation (R = 0.9942) between the single-arm ECG and lead I ECG, while the duration of the QRS complex wave showed the weakest cross-correlation (R = 0.2201). The best SNR obtained was 26.1 ± 5.9 dB during the resting experiment, whereas the worst SNR was 12.5 ± 5.1 dB during the raising and lowering of the arm along the z-axis. This single-arm ECG measurement method offers easier operation compared to traditional ECG measurement techniques, making it applicable for HRV measurement and the detection of an irregular RRI.

Reduced heart rate variability in people with type 1 diabetes and elevated diabetes distress: Results from the longitudinal observational DIA-LINK1 study

AIMS

People with type 1 diabetes have a higher risk for cardiovascular disease (CVD). Reduced heart rate variability (HRV) is a clinical marker for CVD. In this observational study using continuous HRV measurement across 26 days, we investigated whether psychological stressors (diabetes distress, depressive symptoms) and glycaemic parameters (hypo- and hyperglycaemic exposure, glycaemic variability and HbA_1c ) are associated with lower HRV in people with type 1 diabetes.

METHODS

Data from the non-interventional prospective DIA-LINK1 study were analysed. At baseline, depressive symptoms and diabetes distress were assessed. Glucose values and HRV were recorded daily for 26 days using continuous glucose monitoring (CGM) and a wrist-worn health tracker respectively. Multilevel modelling with participant as nesting factor was used to analyse associations between day-to-day HRV and diabetes distress, depressive symptoms and CGM-derived parameters.

RESULTS

Data from 149 participants were analysed (age: 38.3 ± 13.1 years, HbA_1c : 8.6 ± 1.9%). Participants with elevated diabetes distress had a significantly lower HRV across the 26 days compared to participants without elevated distress (β = -0.28; p = 0.004). Elevated depressive symptoms were not significantly associated with HRV (β = -0.18; p = 0.074). Higher daily exposure to hyperglycaemia (β = -0.44; p = 0.044), higher average exposure to hypoglycaemia (β = -0.18; p = 0.042) and higher HbA_1c (β = -0.20; p = 0.018) were associated with reduced HRV across the 26 days. Sensitivity analysis with HRV averaged across all days corroborated these results.

CONCLUSIONS

Diabetes distress is a clinically meaningful psychosocial stressor that could play a role in the cardiovascular health of people with type 1 diabetes. These findings highlight the need for integrated psychosocial care in diabetes management.

Reduction in the Risk of Peripheral Neuropathy and Lower Decrease in Kidney Function with Metformin, Linagliptin or Their Fixed-Dose Combination Compared to Placebo in Prediabetes: A Randomized Controlled Trial

OBJECTIVE

To compare the effect of glucose-lowering drugs on peripheral nerve and kidney function in prediabetes.

METHODS

Multicenter, randomized, placebo-controlled trial in 658 adults with prediabetes treated for 1 year with metformin, linagliptin, their combination or placebo. Endpoints are small fiber peripheral neuropathy (SFPN) risk estimated by foot electrochemical skin conductance (FESC < 70 μSiemens) and estimated glomerular filtration rate (eGFR).

RESULTS

Compared to the placebo, the proportion of SFPN was reduced by 25.1% (95% CI:16.3-33.9) with metformin alone, by 17.3% (95% CI 7.4-27.2) with linagliptin alone, and by 19.5% (95% CI 10.1-29.0) with the combination linagliptin/metformin (p < 0.0001 for all comparisons). eGFR remained +3.3 mL/min (95% CI: 0.38-6.22) higher with the combination linagliptin/metformin than with the placebo (p = 0.03). Fasting plasma glucose (FPG) decreased more with metformin monotherapy -0.3 mmol/L (95%CI: -0.48; 0.12, p = 0.0009) and with the combination metformin/linagliptin -0.2 mmol/L (95% CI: -0.37; -0.03) than with the placebo (p = 0.0219). Body weight (BW) decreased by -2.0 kg (95% CI: -5.65; -1.65, p = 0.0006) with metformin monotherapy, and by -1.9 kg (95% CI: -3.02; -0.97) with the combination metformin/linagliptin as compared to the placebo (p = 0.0002).

CONCLUSIONS

in people with prediabetes, a 1 year treatment with metformin and linagliptin, combined or in monotherapy, was associated with a lower risk of SFPN, and with a lower decrease in eGFR, than treatment with placebo.

An intelligent health monitoring and diagnosis system based on the internet of things and fuzzy logic for cardiac arrhythmia COVID-19 patients

BACKGROUND

During the COVID-19 pandemic, there is a global demand for intelligent health surveillance and diagnosis systems for patients with critical conditions, particularly those with severe heart diseases. Sophisticated measurement tools are used in hospitals worldwide to identify serious heart conditions. However, these tools need the face-to-face involvement of healthcare experts to identify cardiac problems.

OBJECTIVE

To design and implement an intelligent health monitoring and diagnosis system for critical cardiac arrhythmia COVID-19 patients.

METHODOLOGY

We use artificial intelligence tools divided into two parts: (i) IoT-based health monitoring; and (ii) fuzzy logic-based medical diagnosis. The intelligent diagnosis of heart conditions and IoT-based health surveillance by doctors is offered to critical COVID-19 patients or isolated in remote locations. Sensors, cloud storage, as well as a global system for mobile texts and emails for communication with doctors in case of emergency are employed in our proposal.

RESULTS

Our implemented system favors remote areas and isolated critical patients. This system utilizes an intelligent algorithm that employs an ECG signal pre-processed by moving through six digital filters. Then, based on the processed results, features are computed and assessed. The intelligent fuzzy system can make an autonomous diagnosis and has enough information to avoid human intervention. The algorithm is trained using ECG data from the MIT-BIH database and achieves high accuracy. In real-time validation, the fuzzy algorithm obtained almost 100% accuracy for all experiments.

CONCLUSION

Our intelligent system can be helpful in many situations, but it is particularly beneficial for isolated COVID-19 patients who have critical heart arrhythmia and must receive intensive care.

Enhancing Inhibitory Control in Older Adults: A Biofeedback Study

Multidomain interventions based on bio-/neurofeedback have proven useful in improving executive functions. The present study aimed to explore the potential efficacy and feasibility of an intervention that combined Heart Rate Variability Biofeedback (HRV-BF) and Near Infrared Hemoencephalography Neurofeedback (nirHEG-NF) on inhibitory control (IC) of healthy older adults. Thirty-four participants were randomly assigned to two groups: the biofeedback group (received a 10-week combined intervention of HRV-BF and nirHEG-NF) and the active control group (received a similar protocol without real-time biofeedback). Besides cognitive outcomes, the study examined pre- and post-changes in autonomic regulation and prefrontal blood oxygenation at rest and during training. Results revealed training-induced inhibitory control gains in one of the two interference tasks, whereas no effect was found on response inhibition. After the intervention, HRV increased in participants with the lowest levels of HRV at baseline. Although older adults increased blood oxygenation during training, no significant pre- and post-changes were found in blood flow oxygenation. These findings not only suggest that HRV-BF and nirHEG-NF potentially improve performance in certain subcomponents of inhibition (i.e., interference vs. response inhibition), but it may also be beneficial for parasympathetic activity in participants with low HRV and for increasing blood flow oxygenation on prefrontal areas during training.

Detecting and treating the protean manifestations of diabetic autonomic neuropathy

The manifestations of diabetic autonomic neuropathy (DAN) are protean and clinically involve multiple systems, including the cardiovascular system, the gastrointestinal system, the genitourinary system as well as the sweat glands (sudomotor dysfunction) and the gallbladder. In addition, cardiac autonomic neuropathy (CAN) is associated with a correctible inability to appreciate and correct hypoglycaemia. While not a clinical problem, pupillary involvement should be the clue and the catalyst to investigate for other manifestations of DAN. This review outlines a practical approach to detecting and investigating the manifestations of DAN. Of particular importance is early detection of cardiovascular involvement where prompt therapy through glycaemic control can decrease the severity of CAN and decelerate the frequency and severity of retinopathy and nephropathy in addition to decreasing cardiovascular events and mortality. CAN also plays a role in accelerating other diabetic complications such as acute ischaemic stroke, heart failure, medial artery calcinosis, foot ulcers, peripheral artery disease and Charcot joints. Many therapies of DAN are available, which should not only decrease morbidity and mortality from DAN, but also improve the patient's quality of life. However, the therapies available are largely symptomatic.

The Effect of Watermelon Juice Supplementation on Heart Rate Variability and Metabolic Response during an Oral Glucose Challenge: A Randomized, Double-Blind, Placebo-Controlled Crossover Trial

Heart rate variability (HRV) provides a simple method to evaluate autonomic function in health and disease. A reduction in HRV may indicate autonomic dysfunction and is strongly associated with aspects of cardiometabolic disease, including hyperglycemia. Reduced nitric oxide (NO) bioavailability is also implicated in the development of cardiometabolic disease and autonomic dysfunction. Watermelons are natural sources of L-arginine and L-citrulline, substrates used for NO synthesis. Watermelon consumption can improve NO bioavailability. We conducted a randomized, double-blind, placebo-controlled crossover trial to test the effects of 2 weeks of daily watermelon juice (WMJ) supplementation on HRV in response to an oral glucose challenge (OGC) in healthy young adults. We also performed indirect calorimetry to assess if our intervention altered the metabolic response to the OGC. WMJ supplementation preserved high-frequency power (HF) (treatment effect, p = 0.03) and the percentage of successive differences that differ by more than 50 ms (pNN50) (treatment effect, p = 0.009) when compared to the placebo treatment. There was no difference in resting energy expenditure or substate oxidation according to treatment. We report that WMJ supplementation attenuates OGC-induced reductions in HRV. Future work should emphasize the importance of NO bioavailability in autonomic dysfunction in cardiometabolic disease.

Artificial intelligence for non-invasive glycaemic-events detection via ECG in a paediatric population: study protocol

Purpose

Paediatric Type 1 Diabetes (T1D) patients are at greater risk for developing severe hypo and hyperglycaemic events due to poor glycaemic control. To reduce the risk of adverse events, patients need to achieve the best possible glycaemic management through frequent blood glucose monitoring with finger prick or Continuous Glucose Monitoring (CGM) systems. However, several non-invasive techniques have been proposed aiming at exploiting changes in physiological parameters based on glucose levels. The overall objective of this study is to validate an artificial intelligence (AI) based algorithm to detect glycaemic events using ECG signals collected through non-invasive device.

Methods

This study will enrol T1D paediatric participants who already use CGM. Participants will wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glycaemic measurements driven through ECG variables are the main outcomes. Data collected will be used to design, develop and validate the personalised and generalized classifiers based on a deep learning (DL) AI algorithm, able to automatically detect hypoglycaemic events by using few ECG heartbeats recorded with wearable devices.

Results

Data collection is expected to be completed approximately by June 2023. It is expected that sufficient data will be collected to develop and validate the AI algorithm.

Conclusion

This is a validation study that will perform additional tests on a larger diabetes sample population to validate the previous pilot results that were based on four healthy adults, providing evidence on the reliability of the AI algorithm in detecting glycaemic events in paediatric diabetic patients in free-living conditions.

Trial registration

ClinicalTrials.gov identifier: NCT03936634. Registered on 11 March 2022, retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT05278143?titles=AI+for+Glycemic+Events+Detection+Via+ECG+in+a+Pediatric+Population&draw=2&rank=1.

Supplementary information

The online version contains supplementary material available at 10.1007/s12553-022-00719-x.

Heart rate variability in different sleep stages is associated with metabolic function and glycemic control in type 2 diabetes mellitus

Introduction: Autonomic nervous system (ANS) plays an important role in the exchange of metabolic information between organs and regulation on peripheral metabolism with obvious circadian rhythm in a healthy state. Sleep, a vital brain phenomenon, significantly affects both ANS and metabolic function. Objectives: This study investigated the relationships among sleep, ANS and metabolic function in type 2 diabetes mellitus (T2DM), to support the evaluation of ANS function through heart rate variability (HRV) metrics, and the determination of the correlated underlying autonomic pathways, and help optimize the early prevention, post-diagnosis and management of T2DM and its complications. Materials and methods: A total of 64 volunteered inpatients with T2DM took part in this study. 24-h electrocardiogram (ECG), clinical indicators of metabolic function, sleep quality and sleep staging results of T2DM patients were monitored. Results: The associations between sleep quality, 24-h/awake/sleep/sleep staging HRV and clinical indicators of metabolic function were analyzed. Significant correlations were found between sleep quality and metabolic function (|r| = 0.386 ± 0.062, p < 0.05); HRV derived ANS function showed strengthened correlations with metabolic function during sleep period (|r| = 0.474 ± 0.100, p < 0.05); HRV metrics during sleep stages coupled more tightly with clinical indicators of metabolic function [in unstable sleep: |r| = 0.453 ± 0.095, p < 0.05; in stable sleep: |r| = 0.463 ± 0.100, p < 0.05; in rapid eye movement (REM) sleep: |r| = 0.453 ± 0.082, p < 0.05], and showed significant associations with glycemic control in non-linear analysis [fasting blood glucose within 24 h of admission (admission FBG), |r| = 0.420 ± 0.064, p < 0.05; glycated hemoglobin (HbA1c), |r| = 0.417 ± 0.016, p < 0.05]. Conclusions: HRV metrics during sleep period play more distinct role than during awake period in investigating ANS dysfunction and metabolism in T2DM patients, and sleep rhythm based HRV analysis should perform better in ANS and metabolic function assessment, especially for glycemic control in non-linear analysis among T2DM patients.

Utilization of Personalized Machine-Learning to Screen for Dysglycemia from Ambulatory ECG, toward Noninvasive Blood Glucose Monitoring

Blood glucose (BG) monitoring is important for critically ill patients, as poor sugar control has been associated with increased mortality in hospitalized patients. However, constant BG monitoring can be resource-intensive and pose a healthcare burden in clinical practice. In this study, we aimed to develop a personalized machine-learning model to predict dysglycemia from electrocardiogram (ECG) data. We used the Medical Information Mart for Intensive Care III database as our source of data and obtained more than 20 ECG records from each included patient during a single hospital admission. We focused on lead II recordings, along with corresponding blood sugar data. We processed the data and used ECG features from each heartbeat as inputs to develop a one-class support vector machine algorithm to predict dysglycemia. The model was able to predict dysglycemia using a single heartbeat with an AUC of 0.92 ± 0.09, a sensitivity of 0.92 ± 0.10, and specificity of 0.84 ± 0.04. After applying 10 s majority voting, the AUC of the model's dysglycemia prediction increased to 0.97 ± 0.06. This study showed that a personalized machine-learning algorithm can accurately detect dysglycemia from a single-lead ECG.

Heart Rate Variability and Chronotype in Young Adult Men

Whether morning heart rate variability (HRV) predicts the magnitude of its circadian variation in the absence of disease or is influenced by chronotype is unclear. We aimed to quantify associations between (1) morning HRV and its diurnal change, and (2) morning HRV and a Morningness−Eveningness Questionnaire (MEQ)-derived chronotype. Resting electrocardiograms were obtained in the morning and evening on separate days in a counterbalanced order to determine the mean RR interval, root mean square of successive differences (RMSSD), and standard deviation of normal-to-normal RR intervals (SDNN) in 23 healthy men (24.6 ± 3.4 yrs; body mass index: 25.3 ± 2.8 kg/m2). The MEQ was completed during the first laboratory visit. Morning RMSSD and SDNN were significantly higher (Ps < 0.05) than evening values. Morning RMSSD and SDNN were associated with their absolute (Ps < 0.0001), and relative diurnal changes (Ps < 0.01). No associations were observed between HRV parameters and the MEQ chronotypes (Ps > 0.09). Morning HRV was a stronger determinant of its evening change than chronotype. Greater diurnal variation in HRV was dependent on higher morning values. Strategies to improve basal HRV may therefore support healthier cardio-autonomic circadian profiles in healthy young men.

Cardiopulmonary benefits of respirator intervention against near road ambient particulate matters in healthy young adults: A randomized, blinded, crossover, multi-city study

Wearing a respirator is generally the most convenient individual intervention against ambient particulate matter (PM), and therefore there has been considerable research into its effectiveness. However, the effects of respirator intervention under different PM concentration settings have been insufficiently elucidated. We conducted a randomized, blinded, crossover intervention study in four representative cities in China in which 128 healthy university students spent 2-h walking along a busy road wearing either a real or a sham respirator and then spent the next 5-h indoors away from traffic pollution. Lung function, blood pressure, and heart rate variability were continuously measured throughout the visit. Linear mixed-effect models were fitted to evaluate the protective effects of respirator intervention on the cardiopulmonary indicators. Results showed that the beneficial effects of respirator intervention were only occasionally significant at specific time points or in specific cities or in selected parameters. Overall, respirator intervention was associated with reduced SBP (6.2 vs. 11.5 mmHg compared to baseline, p < 0.05) and increased LF (44 vs. 35 ms² compared to baseline, p < 0.05) over the 2-h walk, but no significant effects were found over the 7-h period. Respirators have significant effect modifications on the associations between PM_2.5/PM₁₀ and the cardiopulmonary indicators, but the directions of effects were inconsistent. The intercity difference in the effects of respirator intervention was found significant, with Taiyuan and Shanghai to be the two cities with lower personal PM concentrations but more pronounced benefits. In conclusion, reducing personal exposure to PM can have some beneficial effects in some scenarios. However, respirators may not provide sufficient protection from air pollution overall, and we should avoid over-reliance on respirators and accelerate efforts to reduce emissions of pollutants in the first place. Despite standardized procedures, we found inconsistency in results across cities, consistent with the previous literature.

Excess out-of-hospital cardiac arrests due to ambient temperatures in South Korea from 2008 to 2018

Out-of-hospital cardiac arrest (OHCA) is a notable public health issue with negative outcomes, such as high mortality and aftereffects. Additionally, the adverse effects of extreme temperatures on health have become more important under climate change; however, few studies have investigated the relationship between temperature and OHCA. In this study, we examined the association between temperature and OHCA and its underlying risk factors. We conducted a two-stage time-series analysis using a Poisson regression model with a distributed lag non-linear model (DLNM) and meta-analysis, based on a nationwide dataset from South Korea (2008-2018). We found that 17.4% of excess OHCA was attributed to cold, while 0.9% was attributed to heat. Based on central estimates, excess OHCA attributed to cold were more prominent in the population with hypertension comorbidity (31.0%) than the populations with diabetes (24.3%) and heart disease (17.4%). Excess OHCA attributed to heat were larger in the populations with diabetes (2.7%) and heart disease comorbidity (2.7%) than the population with hypertension (1.2%) based on central estimates. Furthermore, the time-varying excess OHCA attributed to cold have decreased over time, and although those of heat did not show a certain pattern during the study period, there was a weak increasing tendency since 2011. In conclusion, we found that OHCAs were associated with temperature, and cold temperatures showed a greater impact than that of hot temperatures. The effects of cold and hot temperatures on OHCA were more evident in the populations with hypertension, diabetes, and heart diseases, compared to the general population. In addition, the impacts of heat on OHCA increased in recent years, while those of cold temperatures decreased. Our results provide scientific evidence for policymakers to mitigate the OHCA burden attributed to temperature.

Diabetes Detection and Management through Photoplethysmographic and Electrocardiographic Signals Analysis: A Systematic Review

(1) Background: Diabetes mellitus (DM) is a chronic, metabolic disease characterized by elevated levels of blood glucose. Recently, some studies approached the diabetes care domain through the analysis of the modifications of cardiovascular system parameters. In fact, cardiovascular diseases are the first leading cause of death in diabetic subjects. Thanks to their cost effectiveness and their ease of use, electrocardiographic (ECG) and photoplethysmographic (PPG) signals have recently been used in diabetes detection, blood glucose estimation and diabetes-related complication detection. This review's aim is to provide a detailed overview of all the published methods, from the traditional (non machine learning) to the deep learning approaches, to detect and manage diabetes using PPG and ECG signals. This review will allow researchers to compare and understand the differences, in terms of results, amount of data and complexity that each type of approach provides and requires. (2) Method: We performed a systematic review based on articles that focus on the use of ECG and PPG signals in diabetes care. The search was focused on keywords related to the topic, such as "Diabetes", "ECG", "PPG", "Machine Learning", etc. This was performed using databases, such as PubMed, Google Scholar, Semantic Scholar and IEEE Xplore. This review's aim is to provide a detailed overview of all the published methods, from the traditional (non machine learning) to the deep learning approaches, to detect and manage diabetes using PPG and ECG signals. This review will allow researchers to compare and understand the differences, in terms of results, amount of data and complexity that each type of approach provides and requires. (3) Results: A total of 78 studies were included. The majority of the selected studies focused on blood glucose estimation (41) and diabetes detection (31). Only 7 studies focused on diabetes complications detection. We present these studies by approach: traditional, machine learning and deep learning approaches. (4) Conclusions: ECG and PPG analysis in diabetes care showed to be very promising. Clinical validation and data processing standardization need to be improved in order to employ these techniques in a clinical environment.

Novel Application of Multiscale Cross-Approximate Entropy for Assessing Early Changes in the Complexity between Systolic Blood Pressure and ECG R-R Intervals in Diabetic Rats

Cardiac autonomic neuropathy (CAN) is a common complication of diabetes mellitus, and can be assessed using heart rate variability (HRV) and the correlations between systolic blood pressure (SBP) and ECG R-R intervals (RRIs), namely baroreflex sensitivity (BRS). In this study, we propose a novel parameter for the nonlinear association between SBP and RRIs based on multiscale cross-approximate entropy (MS-CXApEn). Sixteen male adult Wistar Kyoto rats were equally divided into two groups: streptozotocin-induced diabetes and age-matched controls. RRIs and SBP were acquired in control rats and the diabetic rats at the onset of hyperglycemia and insulin-treated euglycemia to determine HRV by the ratio of low-frequency to high-frequency power (LF/HF) and Poincaré plot as SSR (SD1/SD2), BRS, and MS-CXApEn. SSR and BRS were not significantly different among the three groups. The LF/HF was significantly higher in the hyperglycemic diabetics than those in the controls and euglycemic diabetic rats. MS-CXApEn was higher in the diabetic hyperglycemic rats than the control rats from scales 2 to 10, and approached the values of controls in diabetic euglycemic rats at scales 9 and 10. Conclusions: We propose MS-CXApEn as a novel parameter to quantify the dynamic nonlinear interactions between SBP and RRIs that reveals more apparent changes in early diabetic rats. Furthermore, changes in this parameter were related to correction of hyperglycemia and could be useful for detecting and assessing CAN in early diabetes.

Acute Changes in Heart Rate Variability to Glucose and Fructose Supplementation in Healthy Individuals: A Double-Blind Randomized Crossover Placebo-Controlled Trial

Simple Summary

In this study, we investigated the cardio-autonomic stress responses to the ingestion of liquid glucose, fructose, a combination thereof and a placebo in healthy individuals at rest. The cardio-autonomic response was more pronounced in all groups with carbohydrates compared to placebo indicating an increased cardio-autonomic stress response resulting in a reduced heart-rate variability. When investigating different levels of blood glucose, the findings showed a significant decline in heart-rate variability with increasing blood glucose levels. This was also seen with severely low levels of blood glucose. The speed of how quick blood glucose increased and decreased also impacted the cardio-autonomic response which further deteriorated heart-rate variability. These findings indicate that healthy human’s autonomic system responds quickly to changes in their blood glucose.

Abstract

Background: It is unknown how different types of carbohydrates alter the cardio-autonomic system in healthy individuals. Therefore, the aim of this study was to investigate how heart-rate variability changes to single dose ingestion of glucose, fructose, glucose and fructose, and an artificial sweetener (sucralose). Methods: In a double-blind randomized crossover placebo-controlled setting, 15 participants received all study-specific substances in liquid form. During each 2-h visit, venous blood glucose was measured in a 5-min interval while heart-rate variability was measured continuously via Holter-electrocardiograph. Results: Ingestion of different types of carbohydrates and sucralose showed significant differences for heart rate (p < 0.001), SDNN (p < 0.008), RMSSD (p < 0.001), pNN50 (p < 0.001) and blood pressure (p < 0.001). Different glucose levels significantly altered parameters of heart-rate variability and blood pressure (all p < 0.001), while the rate of change in blood glucose led to changes in heart rate variability, but not in heart rate (p = 0.25) or blood pressure (p = 0.99). Conclusions: Ingestion of different types of carbohydrates lead to reductions in heart-rate variability compared to a placebo. Blood glucose values above or below 70–90 mg/dL decreased heart rate variability while this was also seen for rapid glucose changes, yet not as pronounced. Healthy individuals should be conscious about carbohydrate intake while maintaining blood glucose levels between 70–90 mg/dL.

Acupuncture Improves Heart Rate Variability, Oxidative Stress Level, Exercise Tolerance, and Quality of Life in Tracheal Collapse Dogs

Among the respiratory disorders in dogs from small breeds, tracheal collapse is one of the most commonly found in clinical practice. Presently, acupuncture is widely used as an alternative treatment which was shown to bring about positive effects in the treatment of human respiratory diseases. The present study demonstrated the effect of acupuncture on tracheal collapse dogs. We hypothesized that acupuncture can help dogs suffering from tracheal collapse by improving various parameters including heart rate variability, serum biomarkers for oxidative stress, exercise performance, and quality of life. Twenty client-owned dogs from small breeds with tracheal collapse disease were enrolled. The study was divided into two 5-week periods. During the first period, the dogs received normal veterinary care but received no acupuncture treatment (NAC). After completing that period, all forms of treatment were withheld for one week before the beginning of the second period. In the second period, all dogs restarted normal veterinary care and underwent acupuncture treatment (AC) once a week for five consecutive weeks. Blood was collected at the beginning and end of each of the two periods for malondialdehyde (MDA) level measurement. Heart rate variability (HRV) was recorded at the 1st, 3rd and 5th weeks of both periods. Exercise tests were performed at the beginning and end of AC period and questionnaire interviews with the owners were accomplished at the end of each period. The results showed that acupuncture can alleviate clinical signs of tracheal collapse, reduce MDA level, and improve sympathovagal balance. We suggest that acupuncture treatment could be used as an adjunct treatment for canine tracheal collapse.

Diagnostic and therapeutic characteristics of diabetes mellitus and risk of out-of-hospital cardiac arrest

This study aimed to evaluate the risks of diabetes mellitus (DM) on out-of-hospital cardiac arrest (OHCA) and to investigate whether the risks of DM on OHCA varied according to the diagnostic and therapeutic characteristics of diabetes. We conducted a multicenter prospective case–control study in 17 University hospitals in Korea from September 2017 to December 2020. Cases were EMS-treated OHCA patients aged 20 to 79 with a presumed cardiac etiology. Community-based controls were recruited at a 1:2 ratio after matching for age, sex, and urbanization level of residence. A structured questionnaire and laboratory findings were collected from cases and controls. Multivariable conditional logistic regression analyses were conducted to estimate the risk of DM on OHCA by characteristics. A total of 772 OHCA cases and 1544 community-based controls were analyzed. A total of 242 (31.3%) OHCAs and 292 (18.9%) controls were previously diagnosed with DM. The proportions of type I DM (10.7% vs. 2.1%) and insulin therapy (15.3% vs. 6.5%) were higher in OHCAs with DM than in controls with DM. The duration of DM was longer in OHCAs than in controls (median 12 vs. 7 years). DM was associated with an increased risk of OHCA (aOR (95% CI), 2.13 (1.64–2.75)). Compared to the no diabetes group, the risks of OHCA increased in the diabetes patients with type I DM (5.26 (1.72–16.08)) and type II DM group (1.63 (1.18–2.27)), a long duration of DM prevalence (1.04 (1.02–1.06) per 1-year prevalence duration), and a high HbA1c level (1.38 (1.19–1.60) per 1% increase). By treatment modality, the aOR (95% CI) was lowest in the oral hypoglycemic agent (1.47 (1.08–2.01)) and highest in the insulin (6.63 (3.04–14.44)) groups. DM was associated with an increased risk of OHCA, and the risk magnitudes varied according to the diagnostic and therapeutic characteristics.

Structural and Electrical Remodeling of the Sinoatrial Node in Diabetes: New Dimensions and Perspectives

The sinoatrial node (SAN) is composed of highly specialized cells that mandate the spontaneous beating of the heart through self-generation of an action potential (AP). Despite this automaticity, the SAN is under the modulation of the autonomic nervous system (ANS). In diabetes mellitus (DM), heart rate variability (HRV) manifests as a hallmark of diabetic cardiomyopathy. This is paralleled by an impaired regulation of the ANS, and by a pathological remodeling of the pacemaker structure and function. The direct effect of diabetes on the molecular signatures underscoring this pathology remains ill-defined. The recent focus on the electrical currents of the SAN in diabetes revealed a repressed firing rate of the AP and an elongation of its tracing, along with conduction abnormalities and contractile failure. These changes are blamed on the decreased expression of ion transporters and cell-cell communication ports at the SAN (i.e., HCN4, calcium and potassium channels, connexins 40, 45, and 46) which further promotes arrhythmias. Molecular analysis crystallized the RGS4 (regulator of potassium currents), mitochondrial thioredoxin-2 (reactive oxygen species; ROS scavenger), and the calcium-dependent calmodulin kinase II (CaMKII) as metabolic culprits of relaying the pathological remodeling of the SAN cells (SANCs) structure and function. A special attention is given to the oxidation of CaMKII and the generation of ROS that induce cell damage and apoptosis of diabetic SANCs. Consequently, the diabetic SAN contains a reduced number of cells with significant infiltration of fibrotic tissues that further delay the conduction of the AP between the SANCs. Failure of a genuine generation of AP and conduction of their derivative waves to the neighboring atrial myocardium may also occur as a result of the anti-diabetic regiment (both acute and/or chronic treatments). All together, these changes pose a challenge in the field of cardiology and call for further investigations to understand the etiology of the structural/functional remodeling of the SANCs in diabetes. Such an understanding may lead to more adequate therapies that can optimize glycemic control and improve health-related outcomes in patients with diabetes.

Cardiovascular Autonomic Reflex Tests and 7 Heart Rate Variability Indices for Early Diagnosis of Cardiovascular Autonomic Neuropathy in Type 2 Diabetes Individuals

BACKGROUND

Cardiovascular autonomic neuropathy (CAN) is a common complication of type 2 Diabetes mellitus (T2D), and prevalence varies according to the methodology used. CAN should be diagnosed in the subclinical stage when an intensive treatment of T2D could avoid the progression to irreversible phases.

OBJECTIVE

Determine the prevalence of early involvement (EI) of CAN in T2D individuals comparing two methodologies.

METHODS

This was a cross-sectional study that included 183 T2D individuals who were monitored in a Tertiary centre. The diagnosis of CAN was based on the results of four cardiovascular autonomic reflex tests (CARTs: expiration-inspiration index, Valsalva maneuver, orthostatic test, and changes in blood pressure after standing) and of seven heart rate variability (7HRV) indices (CARTs plus the spectral analysis). The findings were validated in an independent cohort comprised of 562 T2D individuals followed in a Primary care setting.

RESULTS

With the use of 7HRV, 30.6% and 77.8% of individuals in the Tertiary and in the Primary centers, respectively, were classified as without CAN; 25.1% and 15.3% as EI and 44.3% and 6.9% as definitive CAN, respectively. The use of CARTs decreased the proportion of individuals without CAN in both centers (7.1% and 47%) and increased the frequency of EI (30.6% and 36.6%) and definitive CAN (62.3% and 16.4%), respectively. The concordance between both evaluated methodologies was weak.

CONCLUSION

Higher proportions of T2D individuals were diagnosed with EI and with definitive CAN with the use of CARTs.

The prognostic role of heart rate recovery after exercise and metabolic syndrome in IgA nephropathy

Background

Cardiovascular (CV) morbidity and mortality are higher in chronic kidney disease (CKD) than in the general population. Reduced heart rate recovery (HRR) is an independent risk factor for CV disease. The aim of the study was to determine the prognostic role of HRR in a homogenous group of CKD patients.

Methods

One hundred and twenty-five IgA nephropathy patients (82 male, 43 female, age 54.7 ± 13 years) with CKD stage 1–4 were investigated and followed for average 70 months. We performed a graded exercise treadmill stress test. HRR was derived from the difference of the peak heart rate and the heart rate at 1 min after exercise. Patients were divided into two groups by the mean HRR value (22.9 beats/min). The composite (CV and renal) endpoints included all-cause mortality and any CV event such as stroke, myocardial infarction, revascularisation (CV) and end-stage renal disease, renal replacement therapy (renal).

Results

Patients with reduced HRR (< 23 bpm) had significantly more end point events (22/62 patients vs. 9/53 patients, p = 0.013) compared to the higher HRR (≥23 bpm). Of the secondary the endpoints (CV or renal separately) rate of the renal endpoint was significantly higher in the lower HRR group (p = 0.029), while there was no significant difference in the CV endpoint between the two HRR groups (p = 0.285). Independent predictors of survival were eGFR and diabetes mellitus by using Cox regression analysis. Kaplan-Meier curves showed significant differences in metabolic syndrome and non-metabolic syndrome when examined at the combined endpoints (cardiovascular and renal) or at each endpoint separately. The primary endpoint rate was increased significantly with the increased number of metabolic syndrome component (Met.sy. comp. 0 vs. Met. sy. comp. 2+, primary endpoints, p = 0.012).

Conclusion

Our results showed that reduced HRR measured by treadmill exercise test has a predictive value for the prognosis of IgA nephropathy. The presence of metabolic syndrome may worsen the prognosis of IgA nephropathy.

Hyperglycemia Identification Using ECG in Deep Learning Era

A growing number of smart wearable biosensors are operating in the medical IoT environment and those that capture physiological signals have received special attention. Electrocardiogram (ECG) is one of the physiological signals used in the cardiovascular and medical fields that has encouraged researchers to discover new non-invasive methods to diagnose hyperglycemia as a personal variable. Over the years, researchers have proposed different techniques to detect hyperglycemia using ECG. In this paper, we propose a novel deep learning architecture that can identify hyperglycemia using heartbeats from ECG signals. In addition, we introduce a new fiducial feature extraction technique that improves the performance of the deep learning classifier. We evaluate the proposed method with ECG data from 1119 different subjects to assess the efficiency of hyperglycemia detection of the proposed work. The result indicates that the proposed algorithm is effective in detecting hyperglycemia with a 94.53% area under the curve (AUC), 87.57% sensitivity, and 85.04% specificity. That performance represents an relative improvement of 53% versus the best model found in the literature. The high sensitivity and specificity achieved by the 10-layer deep neural network proposed in this work provide an excellent indication that ECG possesses intrinsic information that can indicate the level of blood glucose concentration.

A Review of Heartbeat Detection Systems for Automotive Applications

Many accidents are caused by sudden changes in the physical conditions of professional drivers. Therefore, it is quite important that the driver monitoring system must not restrict or interfere with the driver’s action. Applications that can measure a driver’s heartbeat without restricting the driver’s action are currently under development. In this review, examples of heartbeat-monitoring systems are discussed. In particular, methods for measuring the heartbeat through sensing devices of a wearable-type, such as wristwatch-type, ring-type, and shirt-type devices, as well as through devices of a nonwearable type, such as steering-type, seat-type, and other types of devices, are discussed. The emergence of wearable devices such as the Apple Watch is considered a turning point in the application of driver-monitoring systems. The problems associated with current smartwatch- and smartphone-based systems are discussed, as are the barriers to their practical use in vehicles. We conclude that, for the time being, detection methods using in-vehicle devices and in-vehicle cameras are expected to remain dominant, while devices that can detect health conditions and abnormalities simply by driving as usual are expected to emerge as future applications.

Pathophysiological mechanisms of bradycardia in patients with anorexia nervosa

BACKGROUND

The purpose of this investigation was to examine heart rate variability (HRV), interbeat interval (IBI), and their interrelationship in healthy controls, bradycardic hyperpolarization-activated cyclic nucleotide-gated channel 4 (HCN4) mutation carriers, and patients with anorexia nervosa (AN). We tested the hypothesis that neural mechanisms cause bradycardia in patients with AN. Therefore, we assumed that saturation of the HRV/IBI relationship as a consequence of sustained parasympathetic control of the sinus node is exclusively detectable in patients with AN.

METHODS

Patients with AN between the ages of 12 and 16 years admitted to our hospital due to malnutrition were grouped and included in the present investigation (N = 20). A matched-pair group with healthy children and adolescents was created. Groups were matched for age and sex. A 24-hour Holter electrocardiography (ECG) was performed in controls and patients. More specifically, all patients underwent two 24-hour Holter ECG examinations (admission; refeeding treatment). Additionally, the IBI was recorded during the night in HCN4 mutation carriers (N = 4). HRV parameters were analyzed in 5-minute sequences during the night and plotted against mean corresponding IBI length. HRV, IBI, and their interrelationship were examined using Spearman's rank correlation analyses, Mann-Whitney U tests, and Wilcoxon signed-rank tests.

RESULTS

The relationship between IBI and HRV showed signs of saturation in patients with AN. Furthermore, signs of HRV saturation were present in two HCN4 mutation carriers. In contrast, signs of HRV saturation were not present in controls.

CONCLUSIONS

The existence of HRV saturation does not support the existence of parasympathetically mediated bradycardia. Nonneural mechanisms, such as HCN4 downregulation, may be responsible for bradycardia and HRV saturation in patients with AN.

Mind-Body and Psychosocial Interventions May Similarly Affect Heart Rate Variability Patterns in Cancer Recovery: Implications for a Mechanism of Symptom Improvement

Background:

Advancements in early detection and treatment of cancer have led to increased survival rates and greater need to identify effective supportive care options for resolving symptoms of survivorship. Many non-pharmacological approaches to symptom management during and after cancer treatment involve emotional self-regulation as a central strategy for improving well-being. Identifying commonalities among these strategies’ mechanisms of action may facilitate understanding of what might be useful for optimizing intervention effects. Heart rate variability (HRV) parameters are indicative of improved autonomic nervous system (ANS) balance and resiliency and reduced emotional distress and are thus identified as a mechanism to discuss as a marker of potential for intervention efficacy and a target for optimization.

Methods:

HRV data from 2 studies, 1 examining a mind-body intervention and 1 examining a psychosocial intervention, are presented as a point of discussion about preliminary associations between the interventions, change in HRV, and emotional distress reduction.

Results:

HRV significantly decreased in sympathetic activity in response to a mind-body intervention (Qigong/Tai Chi), and increased vagal tone in response to a psychosocial (storytelling) intervention. In both, these changes in HRV parameters were associated with improved emotional states.

Conclusion:

Our preliminary data suggest that HRV may serve as an important marker of underlying changes that mediate emotional regulation; this observation deserves further investigation. If identified as a worthy target, focusing on interventions that improve HRV within the context of interventions for cancer patients may be important to key outcomes and clinical practice.

Clinical significance of heart rate variability for the monitoring of cardiac autonomic neuropathy in end-stage renal disease patients

BACKGROUND AND AIMS

The aim of this study is to determine whether the measurement of continuous heart rate variability (HRV) is useful in the evaluation of cardiac autonomic neuropathy (CAN) in end-stage renal disease (ESRD) patients.

METHODS AND RESULTS

This cross-sectional study was performed at Seoul St. Mary's hospital between June 2017 and February 2018. Seventy-seven ESRD patients, and 29 healthy controls (HCs) were asked to wear a continuous ambulatory HRV monitor for 24 h. General cardiac function was evaluated using transthoracic echocardiogram (TTE), pulse wave velocity (PWV), coronary calcium scoring (CCS), and 24-h ambulatory blood pressure monitoring (ABPM). HRV parameters of ESRD patients and HCs, and the correlation of HRV parameters with cardiovascular screening methods were observed. All HRV parameters were significantly decreased in ESRD patients compared to HCs (P < 0.001). In the correlation analysis between TTE results and HRV parameters, 24-h standard deviation of all N-N intervals (24SDNN), 24-h standard deviation of sequential 5-min N-N interval means (24DANN) and Low Frequency Power/High Frequency Power (LF/HF) ratio showed negative correlations with E/e', LAVI and TR velocity which are representative indices for the diastolic function of the heart (P < 0.05). HRV parameters showed negative correlations with baPWV, CCS, and 24-h ABPM results as well (P < 0.05). Hemoglobin and serum albumin showed positive correlations with HRV parameters, and glucose, BUN, creatinine, and iPTH levels showed negative correlations (P < 0.05).

CONCLUSION

Continuous HRV monitoring may be a useful tool for the evaluation of CAN in ESRD.

A Systematic Review of Respiratory Sinus Arrhythmia in Romantic Relationships

Respiratory sinus arrhythmia (RSA), an index of the parasympathetic nervous system, has recently gained attention as a physiological component of regulatory processes, social connectedness, and health. Within the context of romantic relationships, studies have operationalized and conceptualized RSA in disparate ways, obscuring a clear pattern of findings. This systematic review synthesizes the rapidly developing literature and clarifies the role of RSA in romantic relationships. We evaluate support for three conceptual hypotheses: (1) resting baseline RSA is associated with better quality relationships; (2) phasic RSA is reflective of changes in threat and connection during couple interactions; and (3) physiological linkage in RSA between romantic partners relates to positive or negative relationship functioning depending on the nature of the linkage (e.g., in-phase vs. antiphase). We identified 26 empirical studies that tested associations between RSA and an index of romantic relationships (i.e., relationship satisfaction). Our findings show that higher RSA is not uniformly "good" for relationships. Higher resting baseline RSA was contemporaneously associated with better quality relationships, yet higher baseline RSA was also unexpectedly associated with relationship violence. Short-term decreases in RSA were found during relationship conflict, though the opposite-phasic increases in RSA during positive romantic partner interactions-was not found due to mixed empirical support. As expected, evidence for RSA linkage was found, though the connection between linkage and relationship functioning depends on the context in which it was measured. We discuss methodological limitations and directions for future research.

Effects of respiratory muscle training on parasympathetic activity in diabetes mellitus

This study verified the effects of respiratory muscle training (RMT) on hemodynamics, heart rate (HR) variability, and muscle morphology in rats with streptozotocin-induced diabetes mellitus (DM). Thirty-six male Wistar rats were randomized into 4 groups and 34 completed the study: i) sham-sedentary (Sham-ST; n=9); ii) sham-RMT (Sham-RMT; n=9); iii) DM-sedentary (DM-ST; n=8); and iv) DM-RMT (DM-RMT; n=8). Hemodynamics were assessed by central cannulation, and R-R intervals were measured by electrocardiogram. In addition, the effects of RMT on the cross-sectional area of the diaphragm, anterior tibial, and soleus muscles were analyzed. The induction of DM by streptozotocin resulted in weight loss, hyperglycemia, reduced blood pressure, and attenuated left ventricular contraction and relaxation (P<0.05). We also observed a decrease in root mean square of successive differences between adjacent RR intervals (RMSSD) index and in the cross-sectional area of the muscles assessed, specifically the diaphragm, soleus, and anterior tibial muscles in diabetic rats (P<0.05). Interestingly, RMT led to an increase in RMSSD in rats with DM (P<0.05). The induction of DM produced profound deleterious changes in the diaphragmatic and peripheral muscles, as well as impairments in cardiovascular hemodynamics and autonomic control. Nevertheless, RMT may beneficially attenuate autonomic changes and improve parasympathetic modulation.

Supramaximal-Exercise Training Improves Heart Rate Variability in Association With Reduced Catecholamine in Obese Adults

This study investigates the effect of 6 weeks of supramaximal exercise training (SET) on heart rate variability (HRV) and associated factors in sedentary obese (OB) and normal-weight (NW) adults. In this study, 19 OB [22.9 (8.4) years; body mass index (BMI) 33.4 (1.4) kg/m²] and 18 NW [23.2 (4.4) years; BMI 23.3 (1.2) kg/m²] adults completed a 6-week SET intervention. Anthropometric and aerobic indicators as well the homeostasis model assessment index for insulin resistance index (HOMA-IR) were assessed at baseline and after SET. The low- and high-frequency [(LF (0.03–0.15 Hz) in ms² and HF (0.15–0.4 Hz) in ms²)] analysis of HRV as well as adrenaline (A in nmol/l) and noradrenaline (NA in nmol/l) responses were assessed at resting condition and during ventilatory threshold 1 (VT1) of a graded maximal test at baseline and after SET. At baseline, resting HF, LF and the LF/HF ratio were different among groups (P < 0.01, respectively) and were significantly associated with waist-to-hip ratio (β = −0.26; p = 0.01, β = −0.12; p = 0.01 and, β = 0.21; p = 0.01). During exertion at VT1, only LF/HF ratio was associated with NA responses (β = 0.23; p = 0.01). After SET, the frequency domain marker improved significantly for both groups in comparison to baseline. These improvements are manifested by LF and HF increases and LF/HF ratio decreases in the rest condition (p < 0.01, respectively) and during exertion at VT1 (p < 0.01, respectively). The improvement in LH and HF were associated with VO₂max increases (β = 0.22 p = 0.01 and β = 0.33; p = 0.01). The decreases observed for the LF/HF ratio are mainly associated to NA decreases observed at rest (β = 0.31; p = 0.001) and at VT1 (β = 0.38; p = 0.001). Obese adults have altered HRV, and 6 weeks of SET improves HRV variables at rest and during VT1 exertion. While LF and HF improvement were associated with VO2max increases, the LF/HF ratio was mainly associated with noradrenaline decreases observed at rest and at VT1.

Calcium Dobesilate (CaD) Attenuates High Glucose and High Lipid-Induced Impairment of Sarcoplasmic Reticulum Calcium Handling in Cardiomyocytes

Calcium dobesilate (CaD) is used effectively in patients with diabetic microvascular disorder, retinopathy, and nephropathy. Here we sought to determine whether it has an effect on cardiomyocytes calcium mishandling that is characteristic of diabetic cardiomyopathy. Cardiomyocytes were sterile isolated and cultured from 1 to 3 days neonatal rats and treated with vehicle (Control), 25 mM glucose+300 μM Palmitic acid (HG+PA), 100 μM CaD (CaD), or HG+PA+CaD to test the effects on calcium signaling (Ca²⁺ sparks, transients, and SR loads) and reactive oxygen species (ROS) production by confocal imaging. Compared to Control, HG+PA treatment significantly reduced field stimulation-induced calcium transient amplitudes (2.22 ± 0.19 vs. 3.56 ± 0.21, p < 0.01) and the levels of caffeine-induced calcium transients (3.19 ± 0.14 vs. 3.72 ± 0.15, p < 0.01), however significantly increased spontaneous Ca²⁺ sparks firing levels in single cardiomyocytes (spontaneous frequency 2.65 ± 0.23 vs. 1.72 ± 0.12, p < 0.01) and ROS production (67.12 ± 4.4 vs. 47.65 ± 2.12, p < 0.05), which suggest that HG+PA treatment increases the Spontaneity Ca²⁺ spark frequency, and then induced partial reduction of SR Ca²⁺ content and subsequently weaken systolic Ca²⁺ transient in cardiomyocyte. Remarkably, these impairments in calcium signaling and ROS production were largely prevented by pre-treatment of the cells with CaD. Therefore, CaD may contribute to a good protective effect on patients with calcium mishandling and contractile dysfunction in cardiomyocytes associated with diabetic cardiomyopathy.

Diabetes and subclinical hypothyroidism on heart rate variability

BACKGROUND

We aimed to analyse if the effects of coexistent diabetes and subclinical hypothyroidism extend to the cardio autonomic nervous system, using heart rate variability baseline data from the Brazilian Longitudinal Study of Adult Health.

MATERIALS AND METHODS

Heart rate variability analyses were performed by linear time and frequency domains in 5-minute time series collected in the supine position. The associations of diabetes and subclinical hypothyroidism with the lowest quartile group for heart rate and the highest quartile group for each heart rate variability parameter were analysed using additive and multiplicative terms in logistic models. For the first approach, the subsample was categorized into four groups: subjects without diabetes and normal thyroid function (controls); subjects without diabetes and subclinical hypothyroidism; patients with diabetes and normal thyroid function; and patients with diabetes and subclinical hypothyroidism. For the interaction alnalysis, diabetes and subclinical hypothyroidism diagnoses were included in separate, along with a multiplicative interaction term between them.

RESULTS

Point odds ratio estimates for the 4th quartiles of heart rate, and 1st quartiles of all heart rate variability measurements were higher for subjects with combined diabetes and subclinical hypothyroidism than for diabetes only, independently of main sociodemographic and clinical variables (HR: 8.33 vs 2.63; SDNN: 2.59 vs 1.61; RMSSD: 2.37 vs 1.42; LF: 2.83 vs 1.71; HF: 3.06 vs 1.39), but not independently of HbA1c and TSH. Only the interaction term for the association with heart rate, adjusted for sociodemographic and clinical variables, had borderline statistical significance.

CONCLUSION

Diabetes and subclinical hypothyroidism exert a potential joint impact on cardiac autonomic control, showed by additive effects between diabetes and subclinical hypothyroidism, as well as a significant interaction term for the association with heart rate.

Diabetic microvascular complications associated with myocardial repolarization heterogeneity evaluated by Tp-e interval and Tp-e/QTc ratio

INTRODUCTION

The heterogeneity in myocardial repolarization increases the risk of ventricular arrhythmias and sudden death in patients with diabetes mellitus (DM). The Tp-e interval and Tp-e/QTc ratio are found to be useful in the prediction of ventricular arrhythmias. In this study, we aimed to investigate the Tp-e interval and Tp-e/QTc ratio in diabetic patients with and without microvascular complications.

MATERIALS AND METHODS

This cross-sectional observational study included patients with type 2 DM who presented to the endocrinology outpatient clinic. Diabetic microvascular complications were evaluated. The Tp-e interval, Tp-e/QT ratio, and Tp-e/QTc ratio were also calculated.

RESULTS

A total of 240 patients with type 2 DM (148 patients had microvascular complications) were included in the study. Diabetic neuropathy rate was 30.4%, diabetic nephropathy rate was 38.4%, and diabetic retinopathy rate was 21.7%. Upon comparing patients according to Tp-e/QTc ratio, the median Tp-e/QTc interval of the group of patients with complications was 0.21 (0.19-0.23) and the median Tp-e/QTc ratio of the group of patients without complications was 0.19 (0.18-0.20) (p < 0.001). When patients were grouped according to the presence and severity of retinopathy, the Tp-e/QTc ratio was more prolonged in the proliferative retinopathy group [0.27 (0.23-0.30)] than the non-proliferative retinopathy group [0.20 (0.19-0.22), p < 0.001]. When patients were grouped according to the presence and severity of nephropathy, the Tp-e/QTc ratio was more prolonged in the macroalbuminuria and microalbuminuria group than the normoalbuminuric group [0.25 (0.21-0.30), 0.23 (0.19-0.24), and 0.19 (0.20-0.22), respectively, p = 0.002].

CONCLUSIONS

Our study is the first to demonstrate the association of the Tp-e interval and Tp-e/QTc ratio with the presence and severity of microvascular complications in patients with type 2 DM.

Chronic Microvascular Complications in Prediabetic States-An Overview

A prediabetic state is a major risk factor for the development of diabetes, and, because of an identical pathophysiological background of both conditions, their prevalence increases parallelly and equally fast. Long-term hyperglycemia is the main cause inducing chronic complications of diabetes, yet the range of glucose levels at which they start has not been yet unequivocally determined. The current data show that chronic microvascular complications of diabetes can be observed in patients with abnormal glucose metabolism in whom glycaemia is higher than optimal but below diagnostic criteria for diabetes. Prediabetes is a heterogenous nosological unit in which particular types are differently characterized and show different correlations with particular kinds of complications. Analysis of the latest research results shows the need to continue studies in a larger population and can imply the need to verify the currently employed criteria of diagnosing diabetes and chronic complications of diabetes in people with prediabetes.

The autonomic nervous system in its natural environment: Immersion in nature is associated with changes in heart rate and heart rate variability

Stress Recovery Theory (SRT) suggests that time spent in nature reduces stress. While many studies have examined changes in stress physiology after exposure to nature imagery, nature virtual reality, or nature walks, this study is the first to examine changes in heart rate (HR) and vagally mediated HR variability, as assessed by Respiratory Sinus Arrythmia (RSA), after a longer duration of nature exposure. Consistent with SRT, we hypothesized that immersion in nature would promote stress recovery, as indexed by an increase in RSA and a decrease in HR. We also predicted that exposure to nature would improve self-reported mood. We used a within-subjects design (N = 67) to assess changes in peripheral physiology before, during, and after a 5-day nature trip. Results demonstrated a significant decrease in RSA and a significant increase in HR during the trip compared to before or after the trip, suggesting that immersion in nature is associated with a shift toward parasympathetic withdrawal and possible sympathetic activation. These results were contrary to our hypotheses and may suggest increased attentional intake or presence of emotions associated with an increase in sympathetic activation. We also found an improvement in self-reported measures of mood during the trip compared to before or after the trip, confirming our hypotheses and replicating previous research. Implications of this study are discussed in the context of SRT.

Is there cardiac autonomic neuropathy in prediabetes?

Although there is considerably more data showing an association between type 2 diabetes mellitus (T2DM) and autonomic neuropathy, accumulating evidence indicates that cardiovascular autonomic neuropathy (CAN) is common in persons with impaired glucose tolerance (IGT). Furthermore, CAN may occur early after a metabolic insult and obesity, especially among mean, and seems to play an important role in the early pathogenesis of CAN. Autonomic symptoms are common in subjects with IGT. In addition to defects in CAN, in subjects with IGT, there is impaired sudomotor function and abnormalities of endothelial peripheral vasoreactivity. At the present time, the only interventions that may be effective in preventing or reversing IGT associated autonomic neuropathy are lifestyle improvement. These include a tailored diet and exercise program. Other approaches that may be beneficial include modulation of oxidative stress and improvement of metabolic regulation in subjects with IGT. Interventions are most likely to be effective early in the course of disease and therefore it is extremely important to have early diagnosis of IGT and autonomic neuropathy.

Early changes in ambulatory electrocardiography after transcatheter closure in patients with atrial septal defect and factors affecting heart rate variability

Background

Factors affecting heart rate variability (HRV) in patients with atrial septal defect (ASD) have not been clarified. This study sought to identify those factors and establish a preliminary risk model.

Methods

A total of 154 patients with ASD who underwent transcatheter closure and met the study requirements were analyzed in this study. Moreover, 26 patients with patent foramen ovale (PFO) were enrolled in our study as a control group. All patients underwent echocardiography and ambulatory electrocardiography before and one day after the procedure.

Results

The standard deviation of all normal-to-normal (NN) intervals (SDNN) and the standard deviation of the averages of the NN intervals in all 5 min segments of the entire recording (SDANN) were significantly higher and the heart rate was lower after closure than before closure in patients with ASD (SDNN: 6.08, 95% CI 3.00 to 9.15, p < 0.001; SDANN: 7.57, 95% CI 4.50 to 10.64, p < 0.001; heart rate: -1.17, 95% CI − 2.86 to − 0.48, p = 0.006). Multiple regression analyses indicated that age, sex, defect diameter, heart rate and diabetes were significantly associated with HRV indices (SDNN: R² = 0.415; P < 0.001). SDNN and SDANN had obvious correlations with right ventricular systolic pressure (SDNN: R = − 0.370, p < 0.001; SDANN: R = − 0.360, p < 0.001).

Conclusions

Factors affecting HRV in patients with ASD include age, sex, heart rate, defect size and diabetes. Furthermore, right ventricular systolic pressure plays an important role in the change in HRV.