Automatic cardiac arrhythmias classification using CNN and attention-based RNN network

Cardiac disease has become a severe threat to public health according to the government report. In China, there are 0.29 billion cardiac patients and early diagnosis will greatly reduce mortality and improve life quality. Electrocardiogram (ECG) signal is a priority tool in the diagnosis of heart diseases because it is non-invasive and easily available with a simple diagnostic tool of low cost. The paper proposes an automatic classification model by combing convolutional neural network (CNN) and recurrent neural network (RNN) to distinguish different types of cardiac arrhythmias. Morphology features of the raw ECG signals are extracted by CNN blocks and fed into a bidirectional gated recurrent unit (GRU) network. Attention mechanism is used to highlight specific features of the input sequence and contribute to the performance improvement of classification. The model is evaluated with two datasets considering the class imbalance problem constructed with records from MIT-BIH arrhythmia database and China Physiological Signal Challenge 2018 database. Experimental results show that this model achieves good performance with an average F1 score of 0.9110 on public dataset and 0.9082 on subject-specific dataset, which may have potential practical applications.

Sarcopenia and cardiovascular diseases: A systematic review and meta-analysis

Sarcopenia is an age-related disease and is often accompanied by other diseases. Now, many studies have shown that cardiovascular diseases (CVDs) may raise the incidence rate of sarcopenia. Therefore, the purpose of this study was to conduct a systematic review and meta-analysis to investigate the prevalence of sarcopenia in patients with CVDs compared with the general population, defined as relatively healthy non-hospitalized subjects. The databases of PubMed, Embase, Medline and Web of Science were searched for eligible studies published up to 12 November 2022. Two assessment tools were used to evaluate study quality and the risk of bias. Statistical analysis was conducted using STATA 14.0 and R Version 4.1.2. Thirty-eight out of the 89 629 articles retrieved were included in our review. The prevalence of sarcopenia ranged from 10.1% to 68.9% in patients with CVDs, and the pooled prevalence was 35% (95% confidence interval [95% CI]: 28-42%). The pooled prevalence of sarcopenia was 32% (95% CI: 23-41%) in patients with chronic heart failure (CHF), 61% (95% CI: 49-72%) in patients with acute decompensated heart failure (ADHF), 43% (95% CI: 2-85%) in patients with coronary artery disease, 30% (95% CI: 25-35%) in patients with cardiac arrhythmia (CA), 35% (95% CI: 10-59%) in patients with congenital heart disease and 12% (95% CI: 7-17%) in patients with unclassed CVDs. However, in the general population, the prevalence of sarcopenia varied from 2.9% to 28.6% and the pooled prevalence was 13% (95% CI: 9-17%), suggesting that the prevalence of sarcopenia in patients with CVDs was about twice compared with the general population. The prevalence of sarcopenia was significantly higher only in patients with ADHF, CHF and CA compared with the general population. There is a positive correlation between CVDs and sarcopenia. The prevalence of sarcopenia is higher in patients with CVDs than that in the general population. With global aging, sarcopenia has brought a heavy burden to individuals and society. Therefore, it is important to identify the populations with high-risk or probable sarcopenia in order to do an early intervention, such as exercise, to counteract or slow down the progress of sarcopenia.

Brain Connectivity Correlates of Breathing and Cardiac Irregularities in SUDEP: A Resting-State fMRI Study

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of premature mortality among people with epilepsy. Evidence from witnessed and monitored SUDEP cases indicate seizure-induced cardiovascular and respiratory failures; yet, the underlying mechanisms remain obscure. SUDEP occurs often during the night and early morning hours, suggesting that sleep or circadian rhythm-induced changes in physiology contribute to the fatal event. Resting-state fMRI studies have found altered functional connectivity between brain structures involved in cardiorespiratory regulation in later SUDEP cases and in individuals at high-risk of SUDEP. However, those connectivity findings have not been related to changes in cardiovascular or respiratory patterns. Here, we compared fMRI patterns of brain connectivity associated with regular and irregular cardiorespiratory rhythms in SUDEP cases with those of living epilepsy patients of varying SUDEP risk, and healthy controls. We analysed resting-state fMRI data from 98 patients with epilepsy (9 who subsequently succumbed to SUDEP, 43 categorized as low SUDEP risk (no tonic-clonic seizures (TCS) in the year preceding the fMRI scan), and 46 as high SUDEP risk (>3 TCS in the year preceding the scan)) and 25 healthy controls. The global signal amplitude (GSA), defined as the moving standard deviation of the fMRI global signal, was used to identify periods with regular ('low state') and irregular ('high state') cardiorespiratory rhythms. Correlation maps were derived from seeds in twelve regions with a key role in autonomic or respiratory regulation, for the low and high states. Following principal component analysis, component weights were compared between the groups. We found widespread alterations in connectivity of precuneus/posterior cingulate cortex in epilepsy compared to controls, in the low state (regular cardiorespiratory activity). In the low state, and to a lesser degree in the high state, reduced anterior insula connectivity (mainly with anterior and posterior cingulate cortex) in epilepsy appeared, relative to healthy controls. For SUDEP cases, the insula connectivity differences were inversely related to the interval between the fMRI scan and death. The findings suggest that anterior insula connectivity measures may provide a biomarker of SUDEP risk. The neural correlates of autonomic brain structures associated with different cardiorespiratory rhythms may shed light on the mechanisms underlying terminal apnea observed in SUDEP.

Myofibroblast senescence promotes arrhythmogenic remodeling in the aged infarcted rabbit heart

Progressive tissue remodeling after myocardial infarction (MI) promotes cardiac arrhythmias. This process is well studied in young animals, but little is known about pro-arrhythmic changes in aged animals. Senescent cells accumulate with age and accelerate age-associated diseases. Senescent cells interfere with cardiac function and outcome post-MI with age, but studies have not been performed in larger animals, and the mechanisms are unknown. Specifically, age-associated changes in timecourse of senescence and related changes in inflammation and fibrosis are not well understood. Additionally, the cellular and systemic role of senescence and its inflammatory milieu in influencing arrhythmogenesis with age is not clear, particularly in large animal models with cardiac electrophysiology more similar to humans than previously studied animal models. Here, we investigated the role of senescence in regulating inflammation, fibrosis, and arrhythmogenesis in young and aged infarcted rabbits. Aged rabbits exhibited increased peri-procedural mortality and arrhythmogenic electrophysiological remodeling at the infarct border zone (IBZ) compared to young rabbits. Studies of the aged infarct zone revealed persistent myofibroblast senescence and increased inflammatory signaling over a 12-week timecourse. Senescent IBZ myofibroblasts in aged rabbits appear to be coupled to myocytes, and our computational modeling showed that senescent myofibroblast-cardiomyocyte coupling prolongs action potential duration (APD) and facilitates conduction block permissive of arrhythmias. Aged infarcted human ventricles show levels of senescence consistent with aged rabbits, and senescent myofibroblasts also couple to IBZ myocytes. Our findings suggest that therapeutic interventions targeting senescent cells may mitigate arrhythmias post-MI with age.

Occurrence of Severe Arrhythmias in Patients with Non-ST Elevation Acute Coronary Syndrome (NSTE-ACS): A Retrospective Study

BACKGROUND

Non-ST elevation acute coronary syndrome (NSTE-ACS) is one of the most frequent manifestations of coronary artery disease. The occurrence of serious heart rhythm disorders (SHRDs) in NSTE-ACS is not well documented. However, continuous heart rhythm monitoring is recommended during the initial management of NSTE-ACS. The targeted monitoring of patients at greater risk for SHRDs could facilitate patients' care in emergency departments (EDs) where the flow of patients is continuously increasing.

METHODS

This retrospective single-center study included 480 patients from emergency and cardiology departments within the Strasbourg University Hospital between 1 January 2019 and 31 December 2020. The objective was to estimate the frequency of the occurrence of SHRDs among patients with NSTE-ACS. The secondary objective was to highlight the factors associated with a higher risk of SHRDs.

RESULTS

The proportion of SHRDs during the first 48 h of hospital care was 2.3% (CI95%: 1.2-4.1%, n = 11). Two time periods were considered: before coronary angiography (1.0%), and during, or after coronary angiography (1.3%). In the first group, two patients required immediate treatment (0.4% of the patients) and no death occurred. In the univariate analysis, the variables significantly associated with SHRDs were age, anticoagulant medication, a decrease in glomerular filtration rate, plasmatic hemoglobin, and left ventricle ejection fraction (LVEF), and an increase in plasmatic troponin, BNP, and CRP levels. In the multivariable analysis, plasmatic hemoglobin > 12 g/dL seemed to be a protective factor for SHRDs.

CONCLUSIONS

In this study, SHRDs were rare and, most often, spontaneously resolved. These data challenge the relevance of systematic rhythm monitoring during the initial management of patients with NSTE-ACS.

Gut microbiota and cardiac arrhythmia

One of the most prevalent cardiac diseases is cardiac arrhythmia, however the underlying causes are not entirely understood. There is a lot of proof that gut microbiota (GM) and its metabolites have a significant impact on cardiovascular health. In recent decades, intricate impacts of GM on cardiac arrythmia have been identified as prospective approaches for its prevention, development, treatment, and prognosis. In this review, we discuss about how GM and its metabolites might impact cardiac arrhythmia through a variety of mechanisms. We proposed to explore the relationship between the metabolites produced by GM dysbiosis including short-chain fatty acids(SCFA), Indoxyl sulfate(IS), trimethylamine N-oxide(TMAO), lipopolysaccharides(LPS), phenylacetylglutamine(PAGln), bile acids(BA), and the currently recognized mechanisms of cardiac arrhythmias including structural remodeling, electrophysiological remodeling, abnormal nervous system regulation and other disease associated with cardiac arrythmia, detailing the processes involving immune regulation, inflammation, and different types of programmed cell death etc., which presents a key aspect of the microbial-host cross-talk. In addition, how GM and its metabolites differ and change in atrial arrhythmias and ventricular arrhythmias populations compared with healthy people are also summarized. Then we introduced potential therapeutic strategies including probiotics and prebiotics, fecal microbiota transplantation (FMT) and immunomodulator etc. In conclusion, the GM has a significant impact on cardiac arrhythmia through a variety of mechanisms, offering a wide range of possible treatment options. The discovery of therapeutic interventions that reduce the risk of cardiac arrhythmia by altering GM and metabolites is a real challenge that lies ahead.

Does Enhanced Structural Maturity of hiPSC-Cardiomyocytes Better for the Detection of Drug-Induced Cardiotoxicity?

Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) are currently used following the Comprehensive in vitro Proarrhythmic Assay (CiPA) initiative and subsequent recommendations in the International Council for Harmonization (ICH) guidelines S7B and E14 Q&A, to detect drug-induced cardiotoxicity. Monocultures of hiPSC-CMs are immature compared to adult ventricular cardiomyocytes and might lack the native heterogeneous nature. We investigated whether hiPSC-CMs, treated to enhance structural maturity, are superior in detecting drug-induced changes in electrophysiology and contraction. This was achieved by comparing hiPSC-CMs cultured in 2D monolayers on the current standard (fibronectin matrix, FM), to monolayers on a coating known to promote structural maturity (CELLvo™ Matrix Plus, MM). Functional assessment of electrophysiology and contractility was made using a high-throughput screening approach involving the use of both voltage-sensitive fluorescent dyes for electrophysiology and video technology for contractility. Using 11 reference drugs, the response of the monolayer of hiPSC-CMs was comparable in the two experimental settings (FM and MM). The data showed no functionally relevant differences in electrophysiology between hiPSC-CMs in standard FM and MM, while contractility read-outs indicated an altered amplitude of contraction but not changes in time course. RNA profiling for cardiac proteins shows similarity of the RNA expression across the two forms of 2D culture, suggesting that cell-to-matrix adhesion differences may explain account for differences in contraction amplitude. The results support the view that hiPSC-CMs in both 2D monolayer FM and MM that promote structural maturity are equally effective in detecting drug-induced electrophysiological effects in functional safety studies.

Noncoding RNAs as Key Regulators for Cardiac Development and Cardiovascular Diseases

Noncoding RNAs (ncRNAs) play fundamental roles in cardiac development and cardiovascular diseases (CVDs), which are a major cause of morbidity and mortality. With advances in RNA sequencing technology, the focus of recent research has transitioned from studies of specific candidates to whole transcriptome analyses. Thanks to these types of studies, new ncRNAs have been identified for their implication in cardiac development and CVDs. In this review, we briefly describe the classification of ncRNAs into microRNAs, long ncRNAs, and circular RNAs. We then discuss their critical roles in cardiac development and CVDs by citing the most up-to-date research articles. More specifically, we summarize the roles of ncRNAs in the formation of the heart tube and cardiac morphogenesis, cardiac mesoderm specification, and embryonic cardiomyocytes and cardiac progenitor cells. We also highlight ncRNAs that have recently emerged as key regulators in CVDs by focusing on six of them. We believe that this review concisely addresses perhaps not all but certainly the major aspects of current progress in ncRNA research in cardiac development and CVDs. Thus, this review would be beneficial for readers to obtain a recent picture of key ncRNAs and their mechanisms of action in cardiac development and CVDs.

The opportunities and challenges of using Drosophila to model human cardiac diseases

The Drosophila heart tube seems simple, yet it has notable anatomic complexity and contains highly specialized structures. In fact, the development of the fly heart tube much resembles that of the earliest stages of mammalian heart development, and the molecular-genetic mechanisms driving these processes are highly conserved between flies and humans. Combined with the fly's unmatched genetic tools and a wide variety of techniques to assay both structure and function in the living fly heart, these attributes have made Drosophila a valuable model system for studying human heart development and disease. This perspective focuses on the functional and physiological similarities between fly and human hearts. Further, it discusses current limitations in using the fly, as well as promising prospects to expand the capabilities of Drosophila as a research model for studying human cardiac diseases.

Prolonged Piezo1 Activation Induces Cardiac Arrhythmia

The rhythmical nature of the cardiovascular system constantly generates dynamic mechanical forces. At the centre of this system is the heart, which must detect these changes and adjust its performance accordingly. Mechanoelectric feedback provides a rapid mechanism for detecting even subtle changes in the mechanical environment and transducing these signals into electrical responses, which can adjust a variety of cardiac parameters such as heart rate and contractility. However, pathological conditions can disrupt this intricate mechanosensory system and manifest as potentially life-threatening cardiac arrhythmias. Mechanosensitive ion channels are thought to be the main proponents of mechanoelectric feedback as they provide a rapid response to mechanical stimulation and can directly affect cardiac electrical activity. Here, we demonstrate that the mechanosensitive ion channel PIEZO1 is expressed in zebrafish cardiomyocytes. Furthermore, chemically prolonging PIEZO1 activation in zebrafish results in cardiac arrhythmias. indicating that this ion channel plays an important role in mechanoelectric feedback. This also raises the possibility that PIEZO1 gain of function mutations could be linked to heritable cardiac arrhythmias in humans.

Systemic AAV9.BVES delivery ameliorates muscular dystrophy in a mouse model of LGMDR25

Limb-girdle muscular dystrophy type R25 (LGMDR25) is caused by recessive mutations in BVES encoding a cAMP-binding protein, characterized by progressive muscular dystrophy with deteriorating muscle function and impaired cardiac conduction in patients. There is currently no therapeutic treatment for LGMDR25 patients. Here we report the efficacy and safety of recombinant adeno-associated virus 9 (AAV9)-mediated systemic delivery of human BVES driven by a muscle-specific promoter MHCK7 (AAV9.BVES) in BVES-knockout (BVES-KO) mice. AAV9.BVES efficiently transduced the cardiac and skeletal muscle tissues when intraperitoneally injected into neonatal BVES-KO mice. AAV9.BVES dramatically improved body weight gain, muscle mass, muscle strength, and exercise performance in BVES-KO mice regardless of sex. AAV9.BVES also significantly ameliorated the histopathological features of muscular dystrophy. The heart rate reduction was also normalized in BVES-KO mice under exercise-induced stress following systemic AAV9.BVES delivery. Moreover, intravenous AAV9.BVES administration into adult BVES-KO mice after the disease onset also resulted in substantial improvement in body weight, muscle mass, muscle contractility, and stress-induced heart rhythm abnormality. No obvious toxicity was detected. Taken together, these results provide the proof-of-concept evidence to support the AAV9.BVES gene therapy for LGMDR25.

iPSC-Derived Cardiomyocytes in Inherited Cardiac Arrhythmias: Pathomechanistic Discovery and Drug Development

With the discovery of induced pluripotent stem cell (iPSCs) a wide range of cell types, including iPSC-derived cardiomyocytes (iPSC-CM), can now be generated from an unlimited source of somatic cells. These iPSC-CM are used for different purposes such as disease modelling, drug discovery, cardiotoxicity testing and personalised medicine. The 2D iPSC-CM models have shown promising results, but they are known to be more immature compared to in vivo adult cardiomyocytes. Novel approaches to create 3D models with the possible addition of other (cardiac) cell types are being developed. This will not only improve the maturity of the cells, but also leads to more physiologically relevant models that more closely resemble the human heart. In this review, we focus on the progress in the modelling of inherited cardiac arrhythmias in both 2D and 3D and on the use of these models in therapy development and drug testing.

A New Approach to Detecting Atrial Fibrillation Using Count Statistics of Relative Changes between Consecutive RR Intervals

BACKGROUND

The ratio of the difference between neighboring RR intervals to the length of the preceding RR interval (x%) represents the relative change in the duration between two cardiac cycles. We investigated the diagnostic properties of the percentage of relative RR interval differences equal to or greater than x% (pRRx%) with x% in a range between 0.25% and 25% for the distinction of atrial fibrillation (AF) from sinus rhythm (SR).

METHODS

We used 1-min ECG segments with RR intervals with either AF (32,141 segments) or SR (32,769 segments) from the publicly available Physionet Long-Term Atrial Fibrillation Database (LTAFDB). The properties of pRRx% for different x% were analyzed using the statistical procedures and metrics commonly used to characterize diagnostic methods.

RESULTS

The distributions of pRRx% for AF and SR differ significantly over the whole studied range of x% from 0.25% to 25%, with particularly outstanding diagnostic properties for the x% range of 1.5% to 6%. However, pRR3.25% outperformed other pRRx%. Firstly, it had one of the highest and closest to perfect areas under the curve (0.971). For pRR3.25%, the optimal threshold for distinction AF from SR was set at 75.32%. Then, the accuracy was 95.44%, sensitivity was 97.16%, specificity was 93.76%, the positive predictive value was 93.85%, the negative predictive value was 97.11%, and the diagnostic odds ratio was 514. The excellent diagnostic properties of pRR3.25% were confirmed in the publicly available MIT-BIH Atrial Fibrillation Database. In a direct comparison, pRR3.25% outperformed the diagnostic properties of pRR31 (the percentage of successive RR intervals differing by at least 31 ms), i.e., so far, the best single parameter differentiating AF from SR.

CONCLUSIONS

A family of pRRx% parameters has excellent diagnostic properties for AF detection in a range of x% between 1.5% and 6%. However, pRR3.25% outperforms other pRRx% parameters and pRR31 (until now, probably the most robust single heart rate variability parameter for AF diagnosis). The exquisite pRRx% diagnostic properties for AF and its simple computation make it well-suited for AF detection in modern ECG technologies (mobile/wearable devices, biopatches) in long-term monitoring. The diagnostic properties of pRRx% deserve further exploration in other databases with AF.

Calmodulin variant E140G associated with long QT syndrome impairs CaMKIIδ autophosphorylation and L-type calcium channel inactivation

Long QT syndrome (LQTS) is a human inherited heart condition that can cause life-threatening arrhythmia including sudden cardiac death. Mutations in the ubiquitous Ca²⁺-sensing protein calmodulin (CaM) are associated with LQTS, but the molecular mechanism by which these mutations lead to irregular heartbeats is not fully understood. Here, we use a multidisciplinary approach including protein biophysics, structural biology, confocal imaging, and patch-clamp electrophysiology to determine the effect of the disease-associated CaM mutation E140G on CaM structure and function. We present novel data showing that mutant-regulated CaMKIIδ kinase activity is impaired with a significant reduction in enzyme autophosphorylation rate. We report the first high-resolution crystal structure of a LQTS-associated CaM variant in complex with the CaMKIIδ peptide, which shows significant structural differences, compared to the WT complex. Furthermore, we demonstrate that the E140G mutation significantly disrupted Ca_v1.2 Ca²⁺/CaM-dependent inactivation, while cardiac ryanodine receptor (RyR2) activity remained unaffected. In addition, we show that the LQTS-associated mutation alters CaM's Ca²⁺-binding characteristics, secondary structure content, and interaction with key partners involved in excitation-contraction coupling (CaMKIIδ, Ca_v1.2, RyR2). In conclusion, LQTS-associated CaM mutation E140G severely impacts the structure-function relationship of CaM and its regulation of CaMKIIδ and Ca_v1.2. This provides a crucial insight into the molecular factors contributing to CaM-mediated arrhythmias with a central role for CaMKIIδ.

This is Your Brain, and This is Your Brain on Atrial Fibrillation: The Roles of Cardiac Malperfusion Events and Vascular Dysfunction in Cognitive Impairment

AF is an independent and strong predictor of long-term cognitive decline. However, the mechanism for this cognitive decline is difficult to define and likely multifactorial, leading to many different hypotheses. Examples include macro- or microvascular stroke events, biochemical changes to the blood-brain barrier related to anticoagulation, or hypo-hyperperfusion events. This review explores and discusses the hypothesis that AF contributes to cognitive decline and dementia through hypo-hyperperfusion events occurring during cardiac arrhythmias. We briefly explain several brain perfusion imaging techniques and further examine the novel findings associated with changes in brain perfusion in patients with AF. Finally, we discuss the implications and areas requiring more research to further understand and treat patients with cognitive decline related to AF.

Arrhythmia and Heart Rate Variability during Long Interdialytic Periods in Patients on Maintenance Hemodialysis: Prospective Observational Cohort Study

Sudden cardiac death among hemodialysis patients is related to the hemodialysis schedule. Mortality is highest within 12 h before and after the first hemodialysis sessions of a week. We investigated the association of arrhythmia occurrence and heart rate variability (HRV) using an electrocardiogram (ECG) monitoring patch during the long interdialytic interval in hemodialysis patients. This was a prospective observational study with 55 participants on maintenance hemodialysis for at least six months. A patch-type ECG monitoring device was applied to record arrhythmia events and HRV during 72 h of a long interdialytic period. Forty-nine participants with sufficient ECG data out of 55 participants were suitable for the analysis. The incidence of supraventricular tachycardia and ventricular tachycardia did not significantly change over time. The square root of the mean squared differences of successive NN intervals (RMSSD), the proportion of adjacent NN intervals differing by >50 ms (pNN50), and high-frequency (HF) increased during the long interdialytic interval. The gap in RMSSD, pNN50, HF, and the low-frequency/high-frequency (LF/HF) ratio between patients with and without significant arrhythmias increased significantly over time during the long interdialytic interval. The daily changes in RMSSD, pNN50, HF, and the LF/HF ratio were more prominent in patients without significant arrhythmias than in those with significant arrhythmias. The electrolyte fluctuation between post-hemodialysis and subsequent pre-hemodialysis was not considered in this study. The study results suggest that the decreased autonomic response during interdialytic periods in dialysis patients is associated with poor cardiac arrhythmia events.

Cardiotoxicity of pyrethroids: molecular mechanisms and therapeutic options for acute and long-term toxicity

Pyrethroids (PY) are synthetic pesticides used in many applications ranging from large-scale agriculture to household maintenance. Their classical mechanisms of action are associated with binding to the sodium channel of insect neurons, disrupting its inactivation, ensuring their use as insecticides. However, PY can also lead to toxicity in vertebrates, including humans. In most toxicological studies, the impact of PY on heart function is neglected. Acute exposure to a high dose of PY causes enhancement of the late sodium current (INaL), which impairs the action potential waveform and can cause severe cardiac arrhythmias. Moreover, long-term, low-dose exposure to PY displays oxidative stress in the heart, which could induce tissue remodeling and impairment. Isolated and preliminary evidence supports that, for acute exposure to PY, an antiarrhythmic therapy with ranolazine (an INaL blocker), can be a promising therapeutic approach. Besides, heart tissue remodeling associated with low doses and long-term exposure to PY seems to benefit from antioxidant therapy. Despite significant leaps in understanding the mechanical details of PY intoxication, currently, few studies are focusing on the heart. In this review, we present what is known and what are the gaps in the field of cardiotoxicity induced by PY.

Prevalence of Baseline Cardiac Arrhythmias in Participants with Overweight or Obesity in Phase 1 Clinical Trials: Analysis of 24-Hour Holter Electrocardiogram Recordings

Although estimates of the prevalence of cardiac arrhythmias in healthy volunteers exist, there is a lack of baseline data in other specific populations, such as people living with overweight and obesity, who are increasingly involved in clinical trials. This study investigated the baseline prevalence of arrhythmias in participants with overweight or obesity in 2 phase 1 trials of weight management medications (NCT03661879, NCT03308721). Participants aged 18-55 years, without a history of cardiovascular disease, and with body mass index (BMI) of 25.0-39.9 kg/m² , were screened for abnormalities in vital signs, electrocardiogram (ECG) recordings, and electrolytes. Baseline 24-hour ECG (Holter) data were collected and manually reviewed by a cardiologist. The primary endpoint was the proportion of participants with ≥1 episode of the predefined cardiac arrhythmias. Continuous 12-lead ECG data were obtained from 207 participants. Most arrhythmias occurred in <3% of participants. Atrioventricular blocks and other potentially malignant arrhythmias were uncommon. There were no associations with age, sex, or BMI. Prevalence of atrioventricular blocks, nonsustained ventricular tachycardia, and other potentially malignant arrhythmias mirrored those reported in healthy participants with normal weight. In clinical trials of weight management medication, knowledge of the baseline prevalence of arrhythmias in people with overweight and obesity may inform trial eligibility criteria, improve on-trial decisions, and could be useful in discussions with health authorities. Baseline Holter readings and real-time ECG telemetry monitoring should be considered in such trials if arrhythmia risk is intrinsic to the molecule, or when signals have been observed in preclinical studies.

In Silico Modelling to Assess the Electrical and Thermal Disturbance Provoked by a Metal Intracoronary Stent during Epicardial Pulsed Electric Field Ablation

Background: Pulsed Electric Field (PEF) ablation has been recently proposed to ablate cardiac ganglionic plexi (GP) aimed to treat atrial fibrillation. The effect of metal intracoronary stents in the vicinity of the ablation electrode has not been yet assessed. Methods: A 2D numerical model was developed accounting for the different tissues involved in PEF ablation with an irrigated ablation device. A coronary artery (with and without a metal intracoronary stent) was considered near the ablation source (0.25 and 1 mm separation). The 1000 V/cm threshold was used to estimate the ‘PEF-zone’. Results: The presence of the coronary artery (with or without stent) distorts the E-field distribution, creating hot spots (higher E-field values) in the front and rear of the artery, and cold spots (lower E-field values) on the sides of the artery. The value of the E-field inside the coronary artery is very low (~200 V/cm), and almost zero with a metal stent. Despite this distortion, the PEF-zone contour is almost identical with and without artery/stent, remaining almost completely confined within the fat layer in any case. The mentioned hot spots of E-field translate into a moderate temperature increase (<48 °C) in the area between the artery and electrode. These thermal side effects are similar for pulse intervals of 10 and 100 μs. Conclusions: The presence of a metal intracoronary stent near the ablation device during PEF ablation simply ‘amplifies’ the E-field distortion already caused by the presence of the vessel. This distortion may involve moderate heating (<48 °C) in the tissue between the artery and ablation electrode without associated thermal damage.

A Possible Explanation for the Low Penetrance of Pathogenic KCNE1 Variants in Long QT Syndrome Type 5

Long QT syndrome (LQTS) is an inherited cardiac rhythm disorder associated with increased incidence of cardiac arrhythmias and sudden death. LQTS type 5 (LQT5) is caused by dominant mutant variants of KCNE1, a regulatory subunit of the voltage-gated ion channels generating the cardiac potassium current I_Ks. While mutant LQT5 KCNE1 variants are known to inhibit I_Ks amplitudes in heterologous expression systems, cardiomyocytes from a transgenic rabbit LQT5 model displayed unchanged I_Ks amplitudes, pointing towards the critical role of additional factors in the development of the LQT5 phenotype in vivo. In this study, we demonstrate that KCNE3, a candidate regulatory subunit of I_Ks channels minimizes the inhibitory effects of LQT5 KCNE1 variants on I_Ks amplitudes, while current deactivation is accelerated. Such changes recapitulate I_Ks properties observed in LQT5 transgenic rabbits. We show that KCNE3 accomplishes this by displacing the KCNE1 subunit within the I_Ks ion channel complex, as evidenced by a dedicated biophysical assay. These findings depict KCNE3 as an integral part of the I_Ks channel complex that regulates I_Ks function in cardiomyocytes and modifies the development of the LQT5 phenotype.

A robust multiple heartbeats classification with weight-based loss based on convolutional neural network and bidirectional long short-term memory

Background: Analysis of electrocardiogram (ECG) provides a straightforward and non-invasive approach for cardiologists to diagnose and classify the nature and severity of variant cardiac diseases including cardiac arrhythmia. However, the interpretation and analysis of ECG are highly working-load demanding, and the subjective may lead to false diagnoses and heartbeats classification. In recent years, many deep learning works showed an excellent role in accurate heartbeats classification. However, the imbalance of heartbeat classes is universal in most of the available ECG databases since abnormal heartbeats are always relatively rare in real life scenarios. In addition, many existing approaches achieved prominent results by removing noise and extracting features in data preprocessing, which relies heavily on powerful computers. It is a pressing need to develop efficient and automatic light weighted algorithms for accurate heartbeats classification that can be used in portable ECG sensors. Objective: This study aims at developing a robust and efficient deep learning method, which can be embedded into wearable or portable ECG monitors for classifying heartbeats. Methods: We proposed a novel and light weighted deep learning architecture with weight-based loss based on a convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM) that can automatically identify five types of ECG heartbeats according to the AAMI EC57 standard. It was also true that the raw ECG signals were simply segmented without noise removal and other feature extraction processing. Moreover, to tackle the challenge of classification bias due to imbalanced ECG datasets for different types of arrhythmias, we introduced a weight-based loss function to reduce the influence of over-weighted categories in the ECG dataset. For avoiding the influence of the division of validation dataset, k-fold method was adopted to improve the reliability of the model. Results: The proposed algorithm is trained and tested on MIT-BIH Arrhythmia Database, and achieves an average of 99.33% accuracy, 93.67% sensitivity, 99.18% specificity, 89.85% positive prediction, and 91.65% F₁ score.

Pulsed Electric Field Ablation of Epicardial Autonomic Ganglia: Computer Analysis of Monopolar Electric Field across the Tissues Involved

BACKGROUND AND OBJECTIVES

Pulsed Electric Field (PEF) ablation has been proposed as a non-thermal energy to treat atrial fibrillation (AF) by epicardial ablation of ganglionated plexi (GP), which are embedded within epicardial fat. Our objective was to study the distribution of the electric field through the involved tissues (fat, GPs, myocardium and blood) during epicardial PEF ablation.

METHODS

A two-dimensional model was built considering different tissue layers below the ablation device which consists of an irrigated electrode. The 1000 V/cm threshold was used to estimate the 'PEF-zone'.

RESULTS

The PEF-zone was almost 100% circumscribed in the epicardial fat layer, with very little incidence in the myocardium. The presence of the saline on the epicardial fat causes the PEF-zone to spread laterally around the electrode from ~5 mm to ~15 mm, relatively independently of how embedded the electrode is in the saline layer. For a saline layer well spread over the tissue surface and an electrode fully embedded in the saline layer, the PEF-zone width decreases as the fat layer thickens: from ~15 mm for fat thickness of 1 and 2 mm, down to ~10 mm for fat thickness of 5 mm. The presence of a GP in the center of the fat layer hardly affects the size of the PEF-zone, but significantly alters the distribution of the electric field around the GP, resulting in progressively lower values than in the surrounding adipose tissue as the fat layer thickness increased.

CONCLUSIONS

Our results suggest how some procedural (irrigation) and anatomical parameters (fat thicknesses and presence of GPs) could be relevant in terms of the size of the tissue area affected by pulsed field ablation.

Adenosine reduces sinoatrial node cell action potential firing rate by uncoupling its membrane and calcium clocks

The spontaneous action potential (AP) firing rate of sinoatrial nodal cells (SANC) is regulated by a system of intracellular Ca²⁺ and membrane ion current clocks driven by Ca²⁺-calmodulin-activated adenylyl cyclase-protein kinase-A signaling. The mean AP-cycle length (APCL) and APCL variability inform on the effectiveness of clock coupling. Endogenous ATP metabolite adenosine binds to adenosine receptors (A₁, A₃) that couple to G_i protein-coupled receptors, reducing spontaneous AP firing rate via G_βγ signaling that activates I_KAch,Ado. Adenosine also inhibits adenylyl cyclase activity via G_αi signaling, impacting cAMP-mediated protein kinase-A-dependent protein phosphorylation. We hypothesize that in addition to I_KAch,Ado activation, adenosine impacts also Ca²⁺ via G_αi signaling and that both effects reduce AP firing rate by reducing the effectiveness of the Ca²⁺ and membrane clock coupling. To this end, we measured Ca²⁺ and membrane potential characteristics in enzymatically isolated single rabbit SANC. 10 µM adenosine substantially increased both the mean APCL (on average by 43%, n = 10) and AP beat-to-beat variability from 5.1 ± 1.7% to 7.2 ± 2.0% (n = 10) measured via membrane potential and 5.0 ± 2.2% to 10.6 ± 5.9% (n = 40) measured via Ca²⁺ (assessed as the coefficient of variability = SD/mean). These effects were mediated by hyperpolarization of the maximum diastolic membrane potential (membrane clock effect) and suppression of diastolic local Ca²⁺releases (LCRs) (Ca²⁺-clock effect): as LCR size distributions shifted to smaller values, the time of LCR occurrence during diastolic depolarization (LCR period) became prolonged, and the ensemble LCR signal became reduced. The tight linear relationship of coupling between LCR period to the APCL in the presence of adenosine "drifted" upward and leftward, i.e. for a given LCR period, APCL was prolonged, becoming non-linear indicating clock uncoupling. An extreme case of uncoupling occurred at higher adenosine concentrations (>100 µM): small stochastic LCRs failed to self-organize and synchronize to the membrane clock, thus creating a failed attempt to generate an AP resulting in arrhythmia and cessation of AP firing. Thus, the effects of adenosine to activate G_βγ and I_KACh,Ado and to activate G_αi, suppressing adenylyl cyclase activity, both contribute to the adenosine-induced increase in the mean APCL and APCL variability by reducing the fidelity of clock coupling and AP firing rate.

ER stress and calcium-dependent arrhythmias

The sarcoplasmic reticulum (SR) plays the key role in cardiac function as the major source of Ca²⁺ that activates cardiomyocyte contractile machinery. Disturbances in finely-tuned SR Ca²⁺ release by SR Ca²⁺ channel ryanodine receptor (RyR2) and SR Ca²⁺ reuptake by SR Ca²⁺-ATPase (SERCa2a) not only impair contraction, but also contribute to cardiac arrhythmia trigger and reentry. Besides being the main Ca²⁺ storage organelle, SR in cardiomyocytes performs all the functions of endoplasmic reticulum (ER) in other cell types including protein synthesis, folding and degradation. In recent years ER stress has become recognized as an important contributing factor in many cardiac pathologies, including deadly ventricular arrhythmias. This brief review will therefore focus on ER stress mechanisms in the heart and how these changes can lead to pro-arrhythmic defects in SR Ca²⁺ handling machinery.

Safety of Electrotherapy Treatment in Patients with Knee Osteoarthritis and Cardiac Diseases

OBJECTIVE: To assess the safety of electrotherapy applied in the knee area in patients with known atrial arrhythmias or ischemic heart disease, as it is not known whether this treatment induces or aggravates arrhythmias during or immediately after therapy. MATERIAL AND METHODS: The analytical and transversal study involved 46 patients with degenerative knee osteoarthritis (OA), with or without cardiac diseases, from the Clinical Rehabilitation Hospital inpatient center, Cluj-Napoca, Romania. All patients underwent a 10-day physical therapy program for knee OA (electrotherapy, massage and kinesiotherapy). Heart rate and the total number of ventricular and supraventricular extrasystoles were evaluated before and after treatment, by 24 h Holter ECG monitoring. RESULTS: There was no significant increase in heart rate or in the number of ventricular or supraventricular extrasystoles before or after electrotherapy treatment, regardless of the positive or negative history of arrhythmia or ischemic heart disease (all p > 0.05). Mean values during day 1 were: 35.15 (95% CI [9.60−60.75]) for ventricular ones extrasystoles and 91.7 (95% CI [51.69−131.7]) for supraventricular ones, which during day 2 were 38.09 (95% CI [3.68−72.50]), 110.48 (95% CI [48.59−172.36]), respectively. CONCLUSION: One of the most important things to consider when dealing with an OA patient is that they are most likely older than 65 years, which increases the chance of having a cardiac disease. This raises the need for viable interventions regarding the management of this disease in patients that probably have multiple comorbidities, and where pharmacological and surgical management are not possible, limited or have multiple side effects. Electrotherapy used for treating knee OA did not cause a significant increase in heart rate or number of ventricular and supraventricular extrasystoles in this category of patients.

The Effect of COVID-19 on QTc Prolongation

Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses angiotensin-converting enzyme-2 receptors on host cells to enter the cells. These receptors are expressed on heart muscle tissue and the tissues of other major organs, which supports the primary accepted theory for the direct cardiac cell injury of coronavirus disease 2019 (COVID-19) and the associated cardiorespiratory manifestations. The SARS-CoV-2 infection leads to unstable myocardial cell membranes due to hypoxia, myocarditis, myocardial ischemia, and abnormal host immune response. This is the main reason behind arrhythmia and electrocardiogram (ECG) changes during COVID-19. However, the specific effect on QTc has not been studied well. Therefore, this study aimed to examine the association between COVID-19 and QTc changes. Methodology We conducted an observational, retrospective review of hospital medical records of 320 adult participants diagnosed with COVID-19 at our facility. After applying the exclusion criteria, 130 participants were included and distributed into two groups. One group had long QTc, and one group had normal QTc. Data were collected and recorded using Microsoft Excel. We used SPSS Statistics for Windows, Version 20.0. (IBM Corp., Armonk, NY, USA) to analyze the data. Student's t-tests were performed for independent groups. Quantitative data were summarized using mean and standard deviation. Statistical significance was taken as p < 0.05. Results A total of 63 (48.4%) participants met the criteria for long QTc, and 67 (51.5%) participants had normal QTc (p < 0.001). There was no statistically significant difference in mortality outcomes between long QTc and normal QTc (0.8% vs. 3.8%, respectively; p = 0.21). Conclusions This study aimed to examine the association between COVID-19 and QTc changes. Nearly half of the participants had an increased QTc with COVID-19, and QTc length was not associated with mortality outcomes. Our results indicate that COVID-19 is an independent risk factor for QTc prolongation on ECG. Identifying COVID-19 as an independent risk factor for QTc prolongation is a clinically significant finding, and physicians should consider this when treating cardiac patients and possible COVID-19-positive patients.

Protein Kinase D1 Regulates Cardiac Hypertrophy, Potassium Channel Remodeling, and Arrhythmias in Heart Failure

Background Structural and electrophysiological remodeling characterize heart failure (HF) enhancing arrhythmias. PKD1 (protein kinase D1) is upregulated in HF and mediates pathological hypertrophic signaling, but its role in K+ channel remodeling and arrhythmogenesis in HF is unknown. Methods and Results We performed echocardiography, electrophysiology, and expression analysis in wild-type and PKD1 cardiomyocyte-specific knockout (cKO) mice following transverse aortic constriction (TAC). PKD1-cKO mice exhibited significantly less cardiac hypertrophy post-TAC and were protected from early decline in cardiac contractile function (3 weeks post-TAC) but not the progression to HF at 7 weeks post-TAC. Wild-type mice exhibited ventricular action potential duration prolongation at 8 weeks post-TAC, which was attenuated in PKD1-cKO, consistent with larger K+ currents via the transient outward current, sustained current, inward rectifier K+ current, and rapid delayed rectifier K+ current and increased expression of corresponding K+ channels. Conversely, reduction of slowly inactivating K+ current was independent of PKD1 in HF. Acute PKD inhibition slightly increased transient outward current in TAC and sham wild-type myocytes but did not alter other K+ currents. Sham PKD1-cKO versus wild-type also exhibited larger transient outward current and faster early action potential repolarization. Tachypacing-induced action potential duration alternans in TAC animals was increased and independent of PKD1, but diastolic arrhythmogenic activities were reduced in PKD1-cKO. Conclusions Our data indicate an important role for PKD1 in the HF-related hypertrophic response and K+ channel downregulation. Therefore, PKD1 inhibition may represent a therapeutic strategy to reduce hypertrophy and arrhythmias; however, PKD1 inhibition may not prevent disease progression and reduced contractility in HF.

A Parallel Cross Convolutional Recurrent Neural Network for Automatic Imbalanced ECG Arrhythmia Detection with Continuous Wavelet Transform

Automatic detection of arrhythmia using electrocardiogram (ECG) and deep learning (DL) is very important to reduce the global death rate from cardiovascular diseases (CVD). Previous studies on automatic arrhythmia detection relied largely on various ECG features and have achieved considerable classification accuracy using DL-based models. However, most previous research has ignored multi-class imbalanced problems in ECG arrhythmia detection. Therefore, it remains a challenge to improve the classification performance of the DL-based models. This paper proposes a novel parallel cross convolutional recurrent neural network in order to improve the arrhythmia detection performance of imbalanced ECG signals. The proposed model incorporates a recurrent neural network and a two-dimensional (2D) convolutional neural network (CNN) and can effectively learn temporal characteristics and rich spatial information of raw ECG signals. Continuous wavelet transform (CWT) is used to transform the ECG signals into a 2D scalogram composed of time-frequency components, and subsequently, the 2D-CNN can learn spatial information from the 2D scalogram. The proposed model is not only efficient in learning features with imbalanced samples but can also significantly improve model convergence with higher accuracy. The overall performance of our proposed model is evaluated based on the MIT-BIH arrhythmia dataset. Detailed analysis of evaluation metrics reveals that the proposed model is very effective in arrhythmia detection and significantly better than the existing hierarchical network models.

Kv Channel Ancillary Subunits: Where Do We Go from Here?

Voltage-gated potassium (Kv) channels each comprise four pore-forming α-subunits that orchestrate essential duties such as voltage sensing and K+ selectivity and conductance. In vivo, however, Kv channels also incorporate regulatory subunits-some Kv channel specific, others more general modifiers of protein folding, trafficking, and function. Understanding all the above is essential for a complete picture of the role of Kv channels in physiology and disease.

Frequency of Arrhythmias and Postural Orthostatic Tachycardia Syndrome in Patients With Marfan Syndrome: A Nationwide Inpatient Study

Background Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder affecting multiple systems, particularly the cardiovascular system. The leading causes of death in MFS are aortopathies and valvular disease. We wanted to identify the frequency of arrhythmia and postural orthostatic tachycardia syndrome, length of hospital stay, health care-associated costs (HAC), and in-hospital mortality in patients with MFS. Methods and Results The National Inpatient Sample database from 2005 to 2014 was queried using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes for MFS and arrhythmias. Patients were classified into subgroups: supraventricular tachycardia, ventricular tachycardia (VT), atrial fibrillation, atrial flutter, and without any type of arrhythmia. Data about length of stay, HAC, and in-hospital mortality were also abstracted from National Inpatient Sample database. Adjusted HAC was calculated as multiplying HAC and cost-to-charge ratio; 12 079 MFS hospitalizations were identified; 1893 patients (15.7%) had an arrhythmia; and 4.9% of the patients had postural orthostatic tachycardia syndrome. Median values of length of stay and adjusted HAC in VT group were the highest among the groups (VT: 6 days, $18 975.8; supraventricular tachycardia: 4 days, $11 906.6; atrial flutter: 4 days, $11 274.5; atrial fibrillation: 5 days, $10431.4; without any type of arrhythmia: 4 days, $8336.6; both P=0.0001). VT group had highest in-patient mortality (VT: 5.3%, atrial fibrillation: 4.1%, without any type of arrhythmia: 2.1%, atrial flutter: 1.7%, supraventricular tachycardia: 0%; P<0.0001) even after adjustment for potential confounders (without any type of arrhythmia versus VT; odds ratio [95% CI]: 3.18 [1.62-6.24], P=0.001). Conclusions Arrhythmias and postural orthostatic tachycardia syndrome in MFS were high and associated with increased length of stay, HAC, and in-hospital mortality especially in patients with VT.

Thermal ablation effects on rotors that characterize functional re-entry cardiac arrhythmia

Thermal ablation is a well-established successful treatment for cardiac arrhythmia, but it still presents limitations that require further studies and developments. In the rotor-driven functional re-entry arrhythmia, tissue heterogeneity results on the generation of spiral/scroll waves and wave break dynamics that may cause dangerous sustainable fibrillation. The selection of the target region to perform thermal ablation to mitigate this type of arrhythmia is challenging, since it considerably affects the local electrophysiology dynamics. This work deals with the numerical simulation of the thermal ablation of a cardiac muscle tissue and its effects on the dynamics of rotor-driven functional re-entry arrhythmia. A non-homogeneous two-dimensional rectangular region is used in the present numerical analysis, where radiofrequency ablation is performed. The electrophysiology problem for the propagation of the action potential in the cardiac tissue is simulated with the Fenton-Karma model. Thermal damage caused to the tissue by the radiofrequency heating is modeled by the Arrhenius equation. The effects of size and position of a heterogeneous region in the original muscle tissue were first analyzed, in order to verify the possible existence of the functional re-entry arrhythmia during the time period considered in the simulations. For each case that exhibited re-entry arrhythmia, six different ablation procedures were analyzed, depending on the position of the radiofrequency electrode and heating time. The obtained results revealed the effects of different model parameters on the existence and possible mitigation of the functional re-entry arrhythmia.

K2P1 leak cation channels contribute to ventricular ectopic beats and sudden death under hypokalemia

Hypokalemia causes ectopic heartbeats, but the mechanisms underlying such cardiac arrhythmias are not understood. In reduced serum K⁺ concentrations that occur under hypokalemia, K2P1 two-pore domain K⁺ channels change ion selectivity and switch to conduct inward leak cation currents, which cause aberrant depolarization of resting potential and induce spontaneous action potential of human cardiomyocytes. K2P1 is expressed in the human heart but not in mouse hearts. We test the hypothesis that K2P1 leak cation channels contribute to ectopic heartbeats under hypokalemia, by analysis of transgenic mice, which conditionally express induced K2P1 specifically in hearts, mimicking K2P1 channels in the human heart. Conditional expression of induced K2P1 specifically in the heart of hypokalemic mice results in multiple types of ventricular ectopic beats including single and multiple ventricular premature beats as well as ventricular tachycardia and causes sudden death. In isolated mouse hearts that express induced K2P1, sustained ventricular fibrillation occurs rapidly after perfusion with low K⁺ concentration solutions that mimic hypokalemic conditions. These observed phenotypes occur rarely in control mice or in the hearts that lack K2P1 expression. K2P1-expressing mouse cardiomyocytes of transgenic mice much more frequently fire abnormal single and/or rhythmic spontaneous action potential in hypokalemic conditions, compared to wild type mouse cardiomyocytes without K2P1 expression. These findings confirm that K2P1 leak cation channels induce ventricular ectopic beats and sudden death of transgenic mice with hypokalemia and imply that K2P1 leak cation channels may play a critical role in human ectopic heartbeats under hypokalemia.

Successful cerebral intravascular thrombectomy stops the heart stopping

A 65-year-old man presented with an acute ischaemic stroke due to right posterior cerebral artery occlusion, complicated by episodes of sinus arrest in the absence of intrinsic cardiac disease. His neurological deficits and sinus node dysfunction resolved following mechanical thrombectomy. We believe this to be a novel case where thrombectomy resulted in successful treatment of cerebral ischaemia mediated cardiac autonomic dysfunction.

Heartbeat Classification and Arrhythmia Detection Using a Multi-Model Deep-Learning Technique

Cardiac arrhythmias pose a significant danger to human life; therefore, it is of utmost importance to be able to efficiently diagnose these arrhythmias promptly. There exist many techniques for the detection of arrhythmias; however, the most widely adopted method is the use of an Electrocardiogram (ECG). The manual analysis of ECGs by medical experts is often inefficient. Therefore, the detection and recognition of ECG characteristics via machine-learning techniques have become prevalent. There are two major drawbacks of existing machine-learning approaches: (a) they require extensive training time; and (b) they require manual feature selection. To address these issues, this paper presents a novel deep-learning framework that integrates various networks by stacking similar layers in each network to produce a single robust model. The proposed framework has been tested on two publicly available datasets for the recognition of five micro-classes of arrhythmias. The overall classification sensitivity, specificity, positive predictive value, and accuracy of the proposed approach are 98.37%, 99.59%, 98.41%, and 99.35%, respectively. The results are compared with state-of-the-art approaches. The proposed approach outperformed the existing approaches in terms of sensitivity, specificity, positive predictive value, accuracy and computational cost.

Differences in Treating Patients with Palpitations at the Primary Healthcare Level Using Telemedical Device Savvy before and during the COVID-19 Pandemic

Background: Palpitations are one of most common reasons why a patient visits a general practitioner (GP) and is referred to a cardiologist. Coronavirus disease 2019 (COVID-19) has been associated with new-onset arrhythmias, which are difficult to diagnose at the primary healthcare level during pandemic-related lockdown periods. Methods: A total of 151 patients with a complaint of heart rhythm disorder were included from before and during the COVID-19 pandemic, as well as after the start of vaccination, in this cohort retrospective study. We used a telemedical device—namely, a personal electrocardiographic (ECG) sensor called Savvy—to investigate heart rhythm in patients. The primary outcome of the study was to evaluate the number of actual heart rhythm disorder patients and any differences that infection with or vaccination for COVID-19 had on patients handled in a primary healthcare setting. Results: We found a heart rhythm disorder in 8.6% of patients before the COVID-19 pandemic and in 15.2–17.9% of patients during the COVID-19 pandemic, where the difference was statistically significant (p = 0.002). During the COVID-19 pandemic, we found a heart rhythm disorder in almost 50% of patients that had tested positive for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus) more than one month ago. After the vaccinations started, we also found a heart rhythm disorder in almost 50% of non-vaccinated patients. Conclusions: Using a telemedical approach or remote consultation is a useful method, at the primary healthcare level, for diagnosing and treating patients with palpitations during times of lockdown.

Cardiac ion channel expression in the equine model - In-silico prediction utilising RNA sequencing data from mixed tissue samples

Understanding cardiomyocyte ion channel expression is crucial to understanding normal cardiac electrophysiology and underlying mechanisms of cardiac pathologies particularly arrhythmias. Hitherto, equine cardiac ion channel expression has rarely been investigated. Therefore, we aim to predict equine cardiac ion channel gene expression. Raw RNAseq data from normal horses from 9 datasets was retrieved from ArrayExpress and European Nucleotide Archive and reanalysed. The normalised (FPKM) read counts for a gene in a mix of tissue were hypothesised to be the average of the expected expression in each tissue weighted by the proportion of the tissue in the mix. The cardiac-specific expression was predicted by estimating the mean expression in each other tissues. To evaluate the performance of the model, predicted gene expression values were compared to the human cardiac gene expression. Cardiac-specific expression could be predicted for 91 ion channels including most expressed Na+ channels, K+ channels and Ca2+ -handling proteins. These revealed interesting differences from what would be expected based on human studies. These differences included predominance of NaV 1.4 rather than NaV 1.5 channel, and RYR1, SERCA1 and CASQ1 rather than RYR2, SERCA2, CASQ2 Ca2+ -handling proteins. Differences in channel expression not only implicate potentially different regulatory mechanisms but also pathological mechanisms of arrhythmogenesis.

Knockout of Sorbin And SH3 Domain Containing 2 (Sorbs2) in Cardiomyocytes Leads to Dilated Cardiomyopathy in Mice

Background

Sorbin and SH3 domain containing 2 (Sorbs2) protein is a cytoskeletal adaptor with an emerging role in cardiac biology and disease; yet, its potential relevance to adult‐onset cardiomyopathies remains underexplored. Sorbs2 global knockout mice display lethal arrhythmogenic cardiomyopathy; however, the causative mechanisms remain unclear. Herein, we examine Sorbs2 dysregulation in heart failure, characterize novel Sorbs2 cardiomyocyte‐specific knockout mice (Sorbs2‐cKO), and explore associations between Sorbs2 genetic variations and human cardiovascular disease.

Methods and Results

Bioinformatic analyses show myocardial Sorbs2 mRNA is consistently upregulated in humans with adult‐onset cardiomyopathies and in heart failure models. We generated Sorbs2‐cKO mice and report that they develop progressive systolic dysfunction and enlarged cardiac chambers, and they die with congestive heart failure at about 1 year old. After 3 months, Sorbs2‐cKO mice begin to show atrial enlargement and P‐wave anomalies, without dysregulation of action potential–associated ion channel and gap junction protein expressions. After 6 months, Sorbs2‐cKO mice exhibit impaired contractility in dobutamine‐treated hearts and skinned myofibers, without dysregulation of contractile protein expressions. From our comprehensive survey of potential mechanisms, we found that within 4 months, Sorbs2‐cKO hearts have defective microtubule polymerization and compensatory upregulation of structural cytoskeletal and adapter proteins, suggesting that this early intracellular structural remodeling is responsible for contractile dysfunction. Finally, we identified genetic variants that associate with decreased Sorbs2 expression and human cardiac phenotypes, including conduction abnormalities, atrial enlargement, and dilated cardiomyopathy, consistent with Sorbs2‐cKO mice phenotypes.

Conclusions

Our studies show that Sorbs2 is essential for maintaining structural integrity in cardiomyocytes, likely through strengthening the interactions between microtubules and other cytoskeletal proteins at cross‐link sites.

COSMOS: Computational Shaping and Modeling of Musical Structures

This position paper makes the case for an innovative, multi-disciplinary methodological approach to advance knowledge on the nature and work of music performance, driven by a novel experiential perspective, that also benefits analysis of electrocardiographic sequences. Music performance is considered by many to be one of the most breathtaking feats of human intelligence. It is well accepted that music performance is a creative act, but the nature of its work remains elusive. Taking the view of performance as an act of creative problem solving, ideas in citizen science and data science, optimization, and computational thinking provide means through which to deconstruct the process of music performance in scalable ways. The method tackles music expression's lack of notation-based data by leveraging listeners' perception and experience of the structures elicited by the performer, with implications for data collection and processing. The tools offer ways to parse a musical sequence into coherent structures, to design a performance, and to explore the space of possible interpretations of the musical sequence. These ideas and tools can be applied to other music-like sequences such as electrocardiographic recordings of arrhythmias (abnormal heart rhythms). Leveraging musical thinking and computational approaches to performance analysis, variations in expressions of cardiac arrhythmias can be more finely characterized, with implications for tailoring therapies and stratifying heart rhythm disorders.

A deep residual inception network with channel attention modules for multi-label cardiac abnormality detection from reduced-lead ECG

OBJECTIVE

Most arrhythmias due to cardiovascular diseases alter the electrical activity, resulting in morphological alterations in electrocardiogram (ECG) recordings. ECG acquisition is a low-cost, non-invasive process and is commonly used for continuous monitoring as a diagnostic tool for cardiac abnormality identification. Our objective is to diagnose twenty-nine cardiac abnormalities and sinus rhythm using varied lead ECG signals.

APPROACH

This work proposes a deep residual inception network with channel attention mechanism (RINCA) for twenty-nine cardiac arrhythmia classification (CAC) along with normal ECG from multi-label ECG signal with different lead combinations. The RINCA architecture employing the Inception-based convolutional neural network backbone uses residual skip connections with the channel attention mechanism. The Inception model facilitates efficient computation and prevents overfitting while exploring deeper networks through dimensionality reduction and stacked 1-dimensional convolutions. The residual skip connections alleviate the vanishing gradient problem. The attention modules selectively leverage the temporally significant segments in a sequence and predominant channels for multi-lead ECG signals, contributing to the decision-making.

MAIN RESULTS

Exhaustive experimental evaluation on the large-scale 'PhysioNet/Computing in Cardiology Challenge (2021)' dataset demonstrates RINCA efficacy. On the hidden test data set, RINCA achieves the challenge metric score of 0.55, 0.51, 0.53, 0.51, and 0.53 (ranked 2nd, 5th, 4th, 5th and 4th) for the twelve-lead, six-lead, four-lead, three-lead, and two-lead combination cases, respectively.

SIGNIFICANCE

The proposed RINCA model is more robust against varied sampling frequency, recording time, and data with heterogeneous demographics than the existing art. The explainability analysis shows RINCA potential in clinical interpretations.

Electrocardiographic characteristics of trained and untrained standardbred racehorses

Background

Long‐term exercise induces cardiac remodeling that potentially influences the electrical properties of the heart.

Hypothesis/objectives

We assessed whether training alters cardiac conduction in Standardbred racehorses.

Animals

Two hundred one trained and 52 untrained Standardbred horses.

Methods

Cross‐sectional study. Resting ECG recordings were analyzed to assess heart rate (HR) along with standard ECG parameters and for identification of atrial and ventricular arrhythmias. An electrophysiological study was performed in 13 horses assessing the effect of training on sinoatrial (SA) and atrioventricular (AV) nodal function by sinus node recovery time (SNRT) and His signal recordings. Age and sex adjustments were implemented in multiple and logistic regression models for comparison.

Results

Resting HR in beats per minute (bpm) was lower in trained vs untrained horses (mean, 30.8 ± 2.6 bpm vs 32.9 ± 4.2 bpm; P = .001). Trained horses more often displayed second‐degree atrioventricular block (2AVB; odds ratio, 2.59; P = .04). No difference in SNRT was found between groups (n = 13). Mean P‐A, A‐H, and H‐V intervals were 71 ± 20, 209 ± 41, and 134 ± 41 ms, respectively (n = 7). We did not detect a training effect on AV‐nodal conduction intervals. His signals were present in 1 horse during 2AVB with varying H‐V interval preceding a blocked beat.

Conclusions and Clinical Importance

We identified decreased HR and increased frequency of 2AVB in trained horses. In 5 of 7 horses, His signal recordings had variable H‐V intervals within each individual horse, providing novel insight into AV conduction in horses.

Whole blood drug levels do not correlate with QTc intervals in hydroxychloroquine-treated systemic lupus erythematosus patients

OBJECTIVES

HCQ is recommended for all patients with SLE, but reports of cardiac toxicity in severe acute respiratory syndrome coronavirus 2 patients raised concerns. We aimed to study the relationship between HCQ blood levels and QTc intervals.

METHODS

A retrospective review of 90 SLE patients (cohort 1) was conducted with data collected regarding demographics, QTc interval and chronic kidney disease (CKD). A prospective study of 84 SLE patients (cohort 2) was conducted with data collected regarding demographics, dose of HCQ, duration of HCQ treatment, presence of echocardiographic abnormalities and CKD simultaneous with whole blood HCQ levels measured by HPLC. Statistical analysis utilized one-way analysis of variance, Pearson's correlation coefficient and t tests.

RESULTS

In cohort 1 there was no significant difference in mean QTc based on 75 HCQ-treated [437.91 msec (s.d. 20.02)] as compared with 15 untreated patients [434.6 msec (s.d. 27.49)]. In patients with CKD, the mean QTc in HCQ users [448 (s.d. 23.37)] as compared with non-users [444.5 msec (s.d. 24.61)] also had no significant difference. In cohort 2, HCQ levels did not correlate with QTc interval (r = 0.017) and this applied regardless of the dose prescribed (r = 0.113 for 400 mg and r = 0.06 for 200 mg), duration of exposure (P = 0.36 for 0-5, >5-10 or >10 years), CKD (r = 0.482) or underlying cardiac abnormalities (r = 0.430).

CONCLUSIONS

This is the first study relying on measured blood levels demonstrating the absence of a clinically consequential increase in QTc levels in HCQ-treated SLE patients.

Rare SUDEP SCN5A variants cause changes in channel function implicating cardiac arrhythmia as a cause of death

Sudden Unexpected Death in Epilepsy (SUDEP) is a leading cause of premature death in epilepsy. The underlying pathological mechanisms are likely to be multi-factorial. Cardiac arrhythmia has been suggested as a cause of death in some patients with SUDEP. SCN5A encodes the cardiac Na_v 1.5 sodium channel. SCN5A variants that result in either loss or gain of channel function cause cardiac arrhythmias. Rare SCN5A variants have been reported in SUDEP cases but the impact of these variants on channel function is unknown. Here we use whole-cell voltage clamp recordings to perform functional analyses of rare SCN5A SUDEP variants, p.V223G, p.I397V and p.R523C. Expression and biophysical properties including activation, inactivation and recovery from inactivation were probed. Each SCN5A variant significantly impacted human Na_V 1.5 channel function indicating that they could cause cardiac arrhythmias. The patient carrying the p.R523C variant was on lamotrigine, an antiseizure medication implicated in SUDEP. Therapeutic concentration of lamotrigine caused a slowing of the rate of recovery from inactivation and a hyperpolarizing shift in the voltage of inactivation of human Na_V 1.5 wild-type, but not p.R523C channels, implicating a gene-by-drug interaction. These data suggest that SCN5A arrhythmogenic variants may confer increased risk of sudden death in individuals with epilepsy.

Electrocardiographic abnormalities and psychotropic polypharmacy in schizophrenia and schizoaffective disorders

BACKGROUND

Sudden cardiac death (SCD) is a significant cause for increased mortality in people with schizophrenia and schizoaffective disorders. Cardiac arrhythmia is one cause of SCD. Electrocardiographic (ECG) abnormalities predictive of arrhythmias are associated with antipsychotic drug use.

METHOD

This chart audit examined the types and frequency of ECG abnormalities (ECG-Abs) in 169 patients with schizophrenia and schizoaffective disorder in a long-stay inpatient unit. We examined the association of ECG-Abs with demographic details and psychotropic drug prescription using chi-square test, Fisher's Exact test, independent two-sample t-test, Pearson's correlation, and one-way ANOVA.

RESULTS

Eighty-eight patients (52.1%) recorded at least one ECG-Ab, and 20.7% had two or more ECG-Abs. The use of multiple antipsychotics, with or without other psychotropic drugs, did not associate significantly with the presence or number of ECG-Abs.

CONCLUSION

A significant proportion of patients with schizophrenia and schizoaffective disorder have ECG-Abs other than prolonged QTc interval, which can predispose them to cardiac arrhythmias. The abnormalities were not limited to patients on psychotropic polypharmacy. ECG evaluation is indicated for all patients and should consider various electrical abnormalities to identify arrhythmia risk.

Impact of obesity on acute complications of catheter ablation for cardiac arrhythmia

BACKGROUND

The prevalence of obesity is increasing. However, data on the periprocedural complication rate of catheter ablation for arrhythmia in patients stratified by body mass index (BMI) is scarce.

METHODS AND RESULTS

This study included 1000 consecutive patients (age 62.0±14.4 years) undergoing catheter ablation for cardiac arrhythmia. The primary study endpoint was any periprocedural major complication (cardiac tamponade, pseudoaneurysm, arteriovenous fistula, transient ischemic attack, stroke, valve damage, myocardial infarction or death). The mean BMI was 27.6±5.1 kg/m² and the majority of patients were overweight (BMI 25.0-29.9 kg/m² , 43.4%). A BMI of 30.0-34.9 kg/m² (Class I obesity) was present in 177 (17.7%) of patients, a BMI of 35.0-39.9 kg/m² (Class II obesity) in 67 (6.7%) and a BMI ≥40 kg/m² (Class III obesity) in 16 (1.6%). There were 31 major complications (3.1%) and one fatality (0.1%) due to terminal heart failure in a patient undergoing palliative ventricular tachycardia ablation. There was no significant impact of the BMI on the rate of major complications (p= 0.495). Compared to normal weight patients, odds ratios for complications in overweight patients, as well as class I, II and III obesity were 1.1 (95% confidence interval (CI) 0.8; 1.7), 1.3 (CI 0.6; 2.6), 1.4 (CI 0.5; 4.1) and 1.6 (CI 0.4; 6.3), respectively. Radiation exposure and procedure duration were significantly increased in obese patients (p<0.001 and p=0.001 respectively).

CONCLUSION

In this study, obesity did not have a significant impact on the incidence of periprocedural complications after CA for cardiac arrhythmia. This article is protected by copyright. All rights reserved.

Late-Onset Ictal Asystole and Falls Related to Severe Coronary Artery Stenosis: A Case Report

Introduction: Ictal asystole (IA) is a rare, underestimated, and life-threatening cause of transient loss of consciousness and fall. Current treatment options for seizures associated with IA usually include cardiac pacemaker implantation. We report, for the first time, a case of IA that is related to coronary stenosis, which was resolved after coronary angioplasty.

Case Presentation: A 73-year-old man had a 2-year history of focal seizures with impaired awareness. Three months before our observation, he started to have sudden falls resulting in injury on several occasions. General and neurological examinations, as well as brain MRI, were unremarkable. Interictal electroencephalography (EEG) showed bitemporal spiking. Ictal video-polygraphy revealed a diffuse electrodecrement, followed by a buildup of rhythmic 4–6 Hz sharp activity, which was more evident in the left temporal region. After the seizure onset, the ECG showed sinus bradycardia, followed by sinus arrest that was associated with the patient's fall from the standing position. Afterwards, sinus rhythm returned spontaneously. A diagnosis of IA was made. A comprehensive cardiologic evaluation revealed a sub-occlusive stenosis of the left anterior descending artery. Successful coronary angioplasty resolved IA, levetiracetam was added, and no seizure or fall has occurred in the following 20 months. Moreover, he underwent a 7-day Holter ECG monitoring, and no asystole was depicted.

Conclusion: The present case was unique as it shows the potential association between IA and coronary stenosis, also suggesting a possible therapeutic role for coronary angioplasty. It also highlights the importance of carefully investigating epilepsy patients with falls, especially in the elderly, since IA-related falls can be easily misdiagnosed in older age. Thus, if IA is identified, a deeper cardiac evaluation should be considered. As seen in our patient, non-invasive diagnostic examination including routine, prolonged, and exercise ECG, as well as echocardiogram, were readily available and were informative in diagnosing cardiac abnormalities that are amenable to specific treatment.