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Pulmonary arterial hypertension (PAH) is characterized by an increase of a pressure in the pulmonary circulation; PAH is accompanied by activation of the sympathetic (SNS) and the renin-angiotensin-aldosterone system (RAAS). However, PAH-associated changes in baroreceptor regulation of systemic circulation, which is tightly interwoven with SNS and RAAS, have not been studied. The baroreceptor response (BRR) was studied in a chronic monocrotaline (MCT) model of PAH in rats (Wistar, 290 ± 30 g, 2–4 months). Phenylephrine as an agonist of α1-adrenergic receptor and sodium nitroprusside as NO donor were gradually administered to chronically catheterized, non-anesthetized control animals and animals with PAH (4 weeks after MCT administration) to induce vasomotor responses. Mean arterial pressure and heart rate (HR) were recorded under the action of vasoactive compounds alone or under the action of vasoactive compounds in presence of angiotensin-II (ATII), atropine. The parameters characterizing baroreceptor change in HR including maximal and minimal heart rate (HRmax, HRmin), reflex tachycardia (TBRR) and bradycardia (BBRR), range (ABRR) and the baroreceptor response sensitivity index (SIBRR) were calculated. A significant decrease in HRmax, TBRR, ABBR (but not BBRR), as well as the sensitivity index of BRR was observed in rats with PAH. ATII induces significant and different changes in the BRR parameters in control rats and in rats with PAH if administered 4 weeks after the start of the experiment. In rats with PAH, ATII causes less pronounced changes in HRmax, TBRR, and BBRR than in control animals. ATII insignificantly affects parasympathetic component of the baroreceptor reflex in rats with PAH. Thus, at least in the MCT-mediated model in rats, PAH significantly deteriorates the baroreceptor regulation of HR. This effect manifests in a decrease in the range and sensitivity of the baroreceptor response. Also, PAH unequally affects the sympathetic and parasympathetic control of the baroreceptor regulation of HR. On the other hand, ATII exhibits weak ability to alter BRR in rats with HAP. In conclusion, PAH leads to a disfunction of immediate, reflex mechanisms HR and systemic circulation control. [ABSTRACT FROM AUTHOR]

In recent decades, much work has been implemented in heart rate (HR) analysis using electrocardiographic (ECG) signals. We propose that algorithms developed to calculate HR based on detected R-peaks using ECG can be applied to seismocardiographic (SCG) signals, as they utilize common knowledge regarding heart rhythm and its underlying physiology. We implemented the experimental framework with methods developed for ECG signal processing and peak detection to be applied and evaluated on SCGs. Furthermore, we assessed and chose the best from all combinations of 15 peak detection and 6 preprocessing methods from the literature on the CEBS dataset available on Physionet. We then collected experimental data in the lab experiment to measure the applicability of the best-selected technique to the real-world data; the abovementioned method showed high precision for signals recorded during sitting rest (HR difference between SCG and ECG: 0.12 ± 0.35 bpm) and a moderate precision for signals recorded with interfering physical activity—reading out a book loud (HR difference between SCG and ECG: 6.45 ± 3.01 bpm) when compared to the results derived from the state-of-the-art photoplethysmographic (PPG) methods described in the literature. The study shows that computationally simple preprocessing and peak detection techniques initially developed for ECG could be utilized as the basis for HR detection on SCG, although they can be further improved. [ABSTRACT FROM AUTHOR]

Background: Unlike tachyarrhythmias, which are common in pregnancy, there is a paucity of data regarding maternal bradycardias. Our objective was to describe the characteristics, associated conditions, and prognosis of women who develop bradycardia post-partum. Method: We conducted a retrospective chart review of patients referred to the Obstetrical Medicine service at British Columbia Women's Hospital from January 2012 to May 2020 for post-partum maternal bradycardia. Results: Twenty-four patients with post-partum bradycardia were included (age 34.2 ± 4.8 years; heart rate 40.4 ± 8.1 beats per minute; blood pressure 131/72 mm Hg). Sinus bradycardia (79.2%) was the most common rhythm. Dyspnea (29.4%) and chest pain (23.5%) were common symptoms. Mean time to resolution of bradycardia was 3.6 ± 3.8 days. Associated conditions potentially explaining the bradycardia were preeclampsia (54.1%), underlying (16.7%), medications (8.3%), and neuraxial anesthesia (8.3%). Conclusions: Maternal bradycardia is an uncommon condition complicating the post-partum period, that is generally self-limiting, with the majority only require clinical observation. [ABSTRACT FROM AUTHOR]

New‐onset atrial fibrillation (NOAF) in COVID‐19 raises significant clinical and public health issues. This systematic review and meta‐analysis aims to compile and analyze the current literature on NOAF in COVID‐19 and give a more comprehensive understanding of the prevalence and outcomes of NOAF in COVID‐19. A comprehensive literature search was carried out using several databases. The random effect model using inverse variance method and DerSimonian and Laird estimator of Tua2 was used to calculate the pooled prevalence and associated 95% confidence interval (CI). Results for outcome analysis were presented as odds ratios (ORs) with 95% CI and pooled using the Mantel‐Haenszel random‐effects model. The pooled prevalence of NOAF in COVID‐19 was 7.8% (95% CI: 6.54%–9.32%),a pooled estimate from 30 articles (81 929 COVID‐19 patients). Furthermore, our analysis reported that COVID‐19 patients with NOAF had a higher risk of developing severe disease compared with COVID‐19 patients without a history of atrial fibrillation (OR = 4.78, 95% CI: 3.75–6.09) and COVID‐19 patients with a history of pre‐existing atrial fibrillation (OR = 2.75, 95% CI: 2.10–3.59). Similarly, our analysis also indicated that COVID‐19 patients with NOAF had a higher risk of all‐cause mortality compared with, COVID‐19 patients without a history of atrial fibrillation (OR = 3.83, 95% CI: 2.99–4.92) and COVID‐19 patients with a history of pre‐existing atrial fibrillation (OR = 2.32, 95% CI: 1.35–3.96). The meta‐analysis did not reveal any significant publication bias. The results indicate a strong correlation between NOAF and a higher risk of severe illness and mortality. These results emphasize the importance of careful surveillance, early detection, and customized NOAF management strategies to improve clinical outcomes for COVID‐19 patients. [ABSTRACT FROM AUTHOR]

Abstract Aims Heart failure is a serious condition that often goes undiagnosed in primary care due to the lack of reliable diagnostic tools and the similarity of its symptoms with other diseases. Non‐invasive monitoring of heart rate variability (HRV), which reflects the activity of the autonomic nervous system, could offer a novel and accurate way to detect and manage heart failure patients. This study aimed to assess the feasibility of using machine learning techniques on HRV data as a non‐invasive biomarker to classify healthy adults and those with heart failure. Methods and results We used digitized electrocardiogram recordings from 54 adults with normal sinus rhythm and 44 adults categorized into New York Heart Association classes 1, 2, and 3, suffering from congestive heart failure. All recordings were sourced from the PhysioNet database. Following data pre‐processing, we performed time‐domain HRV analysis on all individual recordings, including root mean square of the successive difference in adjacent RR interval (RRi) (RMSSD), the standard deviation of RRi (SDNN, the NN stands for natural or sinus intervals), the standard deviation of the successive differences between successive RRi (SDSD), the number or percentage of RRi longer than 50 ms (NN50 and pNN50), and the average value of RRi [mean RR interval (mRRi)]. In our experimental classification performance evaluation, on the computed HRV parameters, we optimized hyperparameters and performed five‐fold cross‐validation using four machine learning classification algorithms: support vector machine, k‐nearest neighbour (KNN), naïve Bayes, and decision tree (DT). We evaluated the prediction accuracy of these models using performance criteria, namely, precision, recall, specificity, F1 score, and overall accuracy. For added insight, we also presented receiver operating characteristic (ROC) plots and area under the ROC curve (AUC) values. The overall best performance accuracy of 77% was achieved when KNN and DT were trained on computed HRV parameters with a 5 min time window. KNN obtained an AUC of 0.77, while DT attained 0.78. Additionally, in the classification of severe congestive heart failure, KNN and DT had the best accuracy of 91%, with KNN achieving an AUC of 0.88 and DT obtaining 0.92. Conclusions The results show that HRV can accurately predict severe congestive heart failure. The findings of this study could inform the use of machine learning approaches on non‐invasive HRV, to screen congestive heart failure individuals in primary care.

In veterinary medicine, hyperbaric oxygen chamber treatment (HBOT) is gaining popularity. Therefore, an increasing number of patients referred for this therapy are being recorded, mainly due to ischemic events, wound healing support, and a high risk of reperfusion damage. During the HBOT procedure, several changes occur in the body’s micro- and macroenvironments. This study involved 34 dogs of various ages and health statuses. The atmospheric conditions in the test hyperbaric chamber included a pressure of 1.5 atmosphere absolute (ATA) at 100% oxygenation. The individuals were divided into three groups: (1) individuals with degenerative mitral valve disease (DMVD), (2) individuals with diseases other than cardiac issues, and (3) healthy individuals who qualified for the HBOT procedure. The period of measurement using the Holter apparatus was divided into four stages: 30 min before the subject’s placement in the hyperbaric chamber; a 4-min compression period (setting chamber conditions); a 90 min HBOT period; and a 1 min decompression period of the hyperbaric chamber. During the HBOT, there was a statistically significant decrease in heart rate in groups 2 and 3 compared to group 1. The heart rate in group 1 remained unchanged through every period of the study. In addition, some of the dogs developed respiratory arrhythmia; in two dogs, premature ventricle beats occurred. The changes observed during the ventricular period indicate that the HBOT procedure causes a significant change in heart rate in dogs without cardiac diseases.

Although aging is known to be associated with an increased incidence of both atrial and ventricular arrhythmias, there is limited knowledge about how Schwann cells (SC) and the intracardiac nervous system (iCNS) remodel with age. Here we investigate the differences in cardiac SC, parasympathetic nerve fibers, and muscarinic acetylcholine receptor M2 (M2R) expression in young and old mice. Additionally, we examine age-related changes in cardiac responses to sympathomimetic and parasympathomimetic drugs. Lower SC density, lower SC proliferation and fewer parasympathetic nerve fibers were observed in cardiac and, as a control sciatic nerves from old (20–24 months) compared to young mice (2–3 months). In old mice, chondroitin sulfate proteoglycan 4 (CSPG4) was increased in sciatic but not cardiac nerves. Expression of M2R was lower in ventricular myocardium and ventricular conduction system from old mice compared to young mice, while no significant difference was seen in M2R expression in sino-atrial or atrio-ventricular node pacemaker tissue. Heart rate was slower and PQ intervals were longer in Langendorff-perfused hearts from old mice. Ventricular tachycardia and fibrillation were more frequently observed in response to carbachol administration in hearts from old mice versus those from young mice. On the background of reduced presence of SC and parasympathetic nerve fibers, and of lower M2R expression in ventricular cardiomyocytes and conduction system of aged hearts, the propensity of ventricular arrhythmogenesis upon parasympathomimetic drug application is increased. Whether this is caused by an increase in heterogeneity of iCNS structure and function remains to be elucidated. [Display omitted] • Reduced Schwann cell density and proliferation are observed in aged intracardiac and peripheral nervous systems. • Deposits of acidic polysaccharides, for example CSPG4, can be found in sciatic nerves from old but not young mice. • Less parasympathetic nerve fibers are detected in aged peripheral nerves and cardiac nerves. • Less muscarininc acetylcholine receptor M2 expression is found in aged ventricular cardiomyocytes and conduction system. • Langendorff-perfused hearts from old mice are more prone to ventricular arrhythmias upon carbachol stimulation. [ABSTRACT FROM AUTHOR]

Aims: Heart failure is a serious condition that often goes undiagnosed in primary care due to the lack of reliable diagnostic tools and the similarity of its symptoms with other diseases. Non‐invasive monitoring of heart rate variability (HRV), which reflects the activity of the autonomic nervous system, could offer a novel and accurate way to detect and manage heart failure patients. This study aimed to assess the feasibility of using machine learning techniques on HRV data as a non‐invasive biomarker to classify healthy adults and those with heart failure. Methods and results: We used digitized electrocardiogram recordings from 54 adults with normal sinus rhythm and 44 adults categorized into New York Heart Association classes 1, 2, and 3, suffering from congestive heart failure. All recordings were sourced from the PhysioNet database. Following data pre‐processing, we performed time‐domain HRV analysis on all individual recordings, including root mean square of the successive difference in adjacent RR interval (RRi) (RMSSD), the standard deviation of RRi (SDNN, the NN stands for natural or sinus intervals), the standard deviation of the successive differences between successive RRi (SDSD), the number or percentage of RRi longer than 50 ms (NN50 and pNN50), and the average value of RRi [mean RR interval (mRRi)]. In our experimental classification performance evaluation, on the computed HRV parameters, we optimized hyperparameters and performed five‐fold cross‐validation using four machine learning classification algorithms: support vector machine, k‐nearest neighbour (KNN), naïve Bayes, and decision tree (DT). We evaluated the prediction accuracy of these models using performance criteria, namely, precision, recall, specificity, F1 score, and overall accuracy. For added insight, we also presented receiver operating characteristic (ROC) plots and area under the ROC curve (AUC) values. The overall best performance accuracy of 77% was achieved when KNN and DT were trained on computed HRV parameters with a 5 min time window. KNN obtained an AUC of 0.77, while DT attained 0.78. Additionally, in the classification of severe congestive heart failure, KNN and DT had the best accuracy of 91%, with KNN achieving an AUC of 0.88 and DT obtaining 0.92. Conclusions: The results show that HRV can accurately predict severe congestive heart failure. The findings of this study could inform the use of machine learning approaches on non‐invasive HRV, to screen congestive heart failure individuals in primary care. [ABSTRACT FROM AUTHOR]

In recent decades, much work has been implemented in heart rate (HR) analysis using electrocardiographic (ECG) signals. We propose that algorithms developed to calculate HR based on detected R-peaks using ECG can be applied to seismocardiographic (SCG) signals, as they utilize common knowledge regarding heart rhythm and its underlying physiology. We implemented the experimental framework with methods developed for ECG signal processing and peak detection to be applied and evaluated on SCGs. Furthermore, we assessed and chose the best from all combinations of 15 peak detection and 6 preprocessing methods from the literature on the CEBS dataset available on Physionet. We then collected experimental data in the lab experiment to measure the applicability of the best-selected technique to the real-world data; the abovementioned method showed high precision for signals recorded during sitting rest (HR difference between SCG and ECG: 0.12 ± 0.35 bpm) and a moderate precision for signals recorded with interfering physical activity—reading out a book loud (HR difference between SCG and ECG: 6.45 ± 3.01 bpm) when compared to the results derived from the state-of-the-art photoplethysmographic (PPG) methods described in the literature. The study shows that computationally simple preprocessing and peak detection techniques initially developed for ECG could be utilized as the basis for HR detection on SCG, although they can be further improved.

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Among the various sleep modulation methods for improving sleep, three methods using noninvasive stimulation during sleep have been reviewed and summarized. The first method involves noninvasive direct brain stimulation to induce a current directly in the brain cortex. Electrically or magnetically applied stimulations trigger electrical events such as slow oscillations or sleep spindles, which can also be recorded by an electroencephalogram. The second method involves sensory stimulation during sleep, which provides stimulation through the sensory pathway to invoke equivalent brain activity like direct brain stimulation. Olfactory, vestibular, and auditory stimulation methods have been used, resulting in several sleep-modulating effects, which are characteristic and depend on the experimental paradigm. The third method is to modulate sleep by shifting the autonomic balance affecting sleep homeostasis. To strengthen parasympathetic dominance, stimulation was applied to decrease heart rate by synchronizing the heart rhythm. These noninvasive stimulation methods can strengthen slow-wave sleep, consolidate declarative or procedural memory, and modify sleep macrostructure. These stimulation methods provide evidence and possibility for sleep modulation in our daily life as an alternative method for the treatment of disturbed sleep and enhancing sleep quality and performance beyond the average level. [ABSTRACT FROM AUTHOR]

In the last 30 years, the field of cyclic adenosine 3′,5′-monophosphate (cAMP) signalling has witnessed a transformative development with the realization that cAMP is compartmentalized and that spatial regulation of cAMP is critical for faithful signal propagation and hormonal specificity. This recognition has changed our understanding of cAMP signalling from the canonical model, where a linear pathway connects a plasma membrane receptor to intracellular effectors and their targets, to a model where signal transduction occurs within a complex network of alternative branches and where an individual receptor leads to activation of a limited fraction of the network, enabled by local regulation of independent signalling units, resulting in a specific functional outcome. The cardiac myocyte has served as the cell model for many of the original findings leading to this paradigm. In this review, we cover some of the evidence supporting this new perspective and discuss how this model is providing novel mechanistic insight into cardiac myocyte physiology. With a focus on the regulation of cardiac rhythm, we consider how this model can provide an original framework for the identification of disease mechanisms. This article is part of the theme issue 'The heartbeat: its molecular basis and physiological mechanisms'. [ABSTRACT FROM AUTHOR]

Rhythms of electrical activity in all regions of the heart can be influenced by a variety of intracellular membrane bound organelles. This is true both for normal pacemaker activity and for abnormal rhythms including those caused by early and delayed afterdepolarizations under pathological conditions. The influence of the sarcoplasmic reticulum (SR) on cardiac electrical activity is widely recognized, but other intracellular organelles including lysosomes and mitochondria also contribute. Intracellular organelles can provide a timing mechanism (such as an SR clock driven by cyclic uptake and release of Ca2+, with an important influence of intraluminal Ca2+), and/or can act as a Ca2+ store involved in signalling mechanisms. Ca2+ plays many diverse roles including carrying electric current, driving electrogenic sodium–calcium exchange (NCX) particularly when Ca2+ is extruded across the surface membrane causing depolarization, and activation of enzymes which target organelles and surface membrane proteins. Heart function is also influenced by Ca2+ mobilizing agents (cADP-ribose, nicotinic acid adenine dinucleotide phosphate and inositol trisphosphate) acting on intracellular organelles. Lysosomal Ca2+ release exerts its effects via calcium/calmodulin-dependent protein kinase II to promote SR Ca2+ uptake, and contributes to arrhythmias resulting from excessive beta-adrenoceptor stimulation. A separate arrhythmogenic mechanism involves lysosomes, mitochondria and SR. Interacting intracellular organelles, therefore, have profound effects on heart rhythms and NCX plays a central role. This article is part of the theme issue 'The heartbeat: its molecular basis and physiological mechanisms'. [ABSTRACT FROM AUTHOR]

Rhythms of electrical activity in all regions of the heart can be influenced by a variety of intracellular membrane bound organelles. This is true both for normal pacemaker activity and for abnormal rhythms including those caused by early and delayed afterdepolarizations under pathological conditions. The influence of the sarcoplasmic reticulum (SR) on cardiac electrical activity is widely recognized, but other intracellular organelles including lysosomes and mitochondria also contribute. Intracellular organelles can provide a timing mechanism (such as an SR clock driven by cyclic uptake and release of Ca2+, with an important influence of intraluminal Ca2+), and/or can act as a Ca2+ store involved in signalling mechanisms. Ca2+ plays many diverse roles including carrying electric current, driving electrogenic sodium–calcium exchange (NCX) particularly when Ca2+ is extruded across the surface membrane causing depolarization, and activation of enzymes which target organelles and surface membrane proteins. Heart function is also influenced by Ca2+ mobilizing agents (cADP-ribose, nicotinic acid adenine dinucleotide phosphate and inositol trisphosphate) acting on intracellular organelles. Lysosomal Ca2+ release exerts its effects via calcium/calmodulin-dependent protein kinase II to promote SR Ca2+ uptake, and contributes to arrhythmias resulting from excessive beta-adrenoceptor stimulation. A separate arrhythmogenic mechanism involves lysosomes, mitochondria and SR. Interacting intracellular organelles, therefore, have profound effects on heart rhythms and NCX plays a central role. This article is part of the theme issue 'The heartbeat: its molecular basis and physiological mechanisms'. [ABSTRACT FROM AUTHOR]

Research of the psychological and physiological status of the medical students before and after solving the multiple choice questions were explored. Individual psychological and physiological parameters were studied in 2 groups of students (18–22 years old): 1 group — men and women; 2 – students who solved and not solved the tasks. It was shown that the dynamics of heart rhythm and parameters of haemodynamics illustrate vegetative maintenance of the intellectual activity of the students during solving computer teaching questions.

Purpose: Cardiac radioablation (cRA) using a stereotactic single-session radioablative approach has recently been described as a possible treatment option for patients with otherwise untreatable recurrent ventricular tachycardia (VT). There is very limited experience in cRA for patients undergoing left ventricular assist device (LVAD) therapy. We present clinical experiences of two patients treated with cRA for incessant VT under long-term LVAD therapy. Methods: Two male patients (54 and 61 years old) with terminal heart failure under LVAD therapy (both patients for 8 years) showed incessant VT despite extensive antiarrhythmic drug therapy and repeated catheter ablation. cRA with a single dose of 25 Gy was applied as a last resort strategy under compassionate use in both patients following an electroanatomical mapping procedure. Results: Both patients displayed ongoing VT during and after the cRA procedure. Repeated attempts at post-procedural rhythm conversion failed in both patients; however, one patient was hemodynamically stabilized and could be discharged home for several months before falling prey to a fatal bleeding complication. The second patient initially stabilized for a few days following cRA before renewed acceleration of running VT required bilateral ablation of the stellate ganglion; the patient died 50 days later. No immediate side effects of cRA were detected in either patient. Conclusion: cRA might serve as a last resort strategy for patients with terminal heart failure undergoing LVAD therapy and displaying incessant VT. Intermediate- and long-term outcomes of these seriously ill patients often remain poor; therefore, best supportive care strategies should also be evaluated as long as no clear beneficial effects of cRA procedures can be shown. For patients treated with cRA under running ventricular rhythm abnormality, strategies for post-procedural generation of stabilized rhythm have to be established. [ABSTRACT FROM AUTHOR]

ECG wave recognition is one of the new topics where only one of the ECG beat waves (P-QRS-T) was used to detect heart diseases. Normal, tachycardia, and bradycardia heart rhythm are hard to detect using either time-domain or frequency-domain features solely, and a time-frequency analysis is required to extract representative features. This paper studies the performance of two different spectrum representations, iris-spectrogram and scalogram, for different ECG beat waves in terms of recognition of normal, tachycardia, and bradycardia classes. These two different spectra are then sent to two different deep convolutional neural networks (CNN), i.e., Resnet101 and ShuffleNet, for deep feature extraction and classification. The results show that the best accuracy for detection of beats rhythm was using ResNet101 and scalogram of T-wave with an accuracy of 98.3%, while accuracy was 94.4% for detection using iris-spectrogram using also ResNet101 and QRS-Wave. Finally, based on these results we note that using deep features from time-frequency representation using one wave of ECG beat we can accurately detect basic rhythms such as normal, tachycardia, and bradycardia. [ABSTRACT FROM AUTHOR]

Temperature effects play an important role in the functioning of the cardiac cell. In this work we simulated the influence of temperature on calcium dynamics properties such as spontaneous calcium release frequency and amplitude while taking into account the experimental data on the response of various protein complexes to the temperature shift. We investigated temperature effects of protein complexes involved in calcium dynamics: calsequestrin and sarco-endoplasmic reticulum ATPase. The contribution of each of them to the temperature effect was explored. Furthermore, we introduced a novel approach of modelling the ryanodine receptors (RyRs) temperature effects and the contribution of RyRs thermal fluctuations to the whole cell temperature dependence was evaluated. The main result of our research is a generalization of the facts of the temperature influence on various calcium cycling proteins in the cardiac cell. Our main assumption is that calsequestrin makes the main contribution to the increase of calcium release frequency and in the increase of calcium concentration in sarcoplasmic reticulum. [ABSTRACT FROM AUTHOR]

The study aimed to systematically review the existing literature and assess the effects of percutaneous balloon mitral valvuloplasty (PBMV) in patients with mitral stenosis and atrial fibrillation (AF) as opposed to sinus rhythm (SR). Eligible studies were identified from six electronic databases before June 2021. The primary outcome was mitral valve area (MVA), and secondary outcomes were hemodynamic measurements, in-hospital complications, and long-term outcomes. Relative risks (RRs) or weighted mean differences (WMDs) with 95% confidence intervals (CIs) were used as effect sizes. Fifteen studies were included involving 6351 patients. For the primary outcome, the AF group obtained less favourable changes in MVA (WMD: −0.10, 95%CI: −0.14, −0.06) and a significantly smaller postoperative and long-term MVA (WMD: −0.13, 95%CI: −0.18, −0.08 and WMD: −0.10, 95%CI: −0.17, −0.03, respectively) compared to the SR group. For secondary outcome, the AF group was associated with suboptimal outcomes as following (WMD/RR, [95%CI]): higher LAP (1.37, [0.86, 1.87]), more embolism (2.85, [1.44, 5.63]), lower event-free survival (0.89, [0.80, 1.00]), higher incidences of mitral valve replacement (2.20, [1.40, 3.46]), re-PBMV (2.28, [1.63, 3.19]), and mortality (3.28, [2.42, 4.44]). No significant differences were found in other outcomes. The currently available evidence suggests that PBMV may be less effective in patients with AF than in those with SR. However, early treatment and appropriate management of AF patients undergoing PBMV may benefit the immediate and long-term outcomes. [ABSTRACT FROM AUTHOR]

It has been noticed that heartbeats can display different patterns according to situations faced by a human. It has been indicated that, those passages from one pattern to another cannot be modelled using a single differential operator, either classical, fractional, or stochastic. In 2021, alternative concepts were introduced and called piecewise differentiation and integration, these concepts were applied in several complex problems with great insight. It is strongly believed that such will be leading concepts to modelling real-world problems with crossover behaviors. Crossover behaviors have been observed in heart rhythm, therefore, in this paper, the well-known van Der Pol equation will be subjected to piecewise analysis. Several simulations will be obtained using a numerical scheme based on Newton polynomial interpolation. Obtained figures show real world behaviors of heart rhythm with piecewise patterns.

Patients with advanced heart failure have a high incidence of atrial fibrillation (AF) and develop into heart failure with reduced ejection fraction (HFrEF), and require higher doses of inotropes. However, it is uncertain about the differences in the effects of levosimendan in HFrEF patients with sinus rhythm or AF. A total of 63 advanced HFrEF subjects (ejection fraction 0.05). The NYHA classification improved in the SR group but not in the AF group. There was no significant difference between patients with different rHRs (≤70 bpm vs. >70 bpm) in the SR group (p > 0.05) or in the AF group (rHR ≤ 90 bpm vs. rHR >90 bpm) (p > 0.05). This study showed no difference in the therapeutic effect of intermittent repeated levosimendan infusion on advanced HFrEF with different heart rhythms (SR or AF); Advanced HFrEF patients receive levosimendan treatment without taking the inference of heart rhythm.

Plasma membrane calcium ATPase 1 (PMCA1, Atp2b1) is emerging as a key contributor to cardiac physiology, involved in calcium handling and myocardial signalling. In addition, genome wide association studies have associated PMCA1 in several areas of cardiovascular disease including hypertension and myocardial infarction. Here, we investigated the role of PMCA1 in basal cardiac function and heart rhythm stability. Cardiac structure, heart rhythm and arrhythmia susceptibility were assessed in a cardiomyocyte-specific PMCA1 deletion (PMCA1CKO) mouse model. PMCA1CKO mice developed abnormal heart rhythms related to ventricular repolarisation dysfunction and displayed an increased susceptibility to ventricular arrhythmias. We further assessed the levels of cardiac ion channels using qPCR and found a downregulation of the voltage-dependent potassium channels, K v 4.2, with a corresponding reduction in the transient outward potassium current which underlies ventricular repolarisation in the murine heart. The changes in heart rhythm were found to occur in the absence of any structural cardiomyopathy. To further assess the molecular changes occurring in PMCA1CKO hearts, we performed proteomic analysis. Functional characterisation of differentially expressed proteins suggested changes in pathways related to metabolism, protein-binding, and pathways associated cardiac function including β-adrenergic signalling. Together, these data suggest an important role for PMCA1 in basal cardiac function in relation to heart rhythm control, with reduced cardiac PMCA1 expression resulting in an increased risk of arrhythmia development. [Display omitted] • PMCA1 is important in maintaining normal cardiac rhythms • Loss of PMCA1 in cardiomyocytes increases susceptibility to ventricular arrhythmias • PMCA1 cardiomyocyte-deletion impacts signalling pathways associated with cardiac rhythm [ABSTRACT FROM AUTHOR]

Recent discoveries in the physiology and pathology of myocardial progenitor cells have allowed researchers to better understand a variety of cardiac pathologies and look at the pathophysiology of arrhythmias from a different perspective. Since the myocardium is composed of a syncytium of electrically interconnected cells, the process of incorporation of newly formed or imported cells into its structure is particularly important. Progenitor cells are stimulated by spontaneous electrical activity, a lengthy action potential, and easily induced triggering activity. All these can lead to arrhythmias development via the three classical mechanisms (reentrancy, automatism, or triggering activity). Transplanted stem cells can influence the electrophysiological properties of cardiomyocytes, thus creating a proarrhythmic substrate. The islets of unbound cells can form an anatomical block, causing unidirectional blockages and recurrent arrhythmias. Similarly, stem cells are capable of establishing heterotopic excitation foci with cardiac stimulatory activity. Finally, the paracrine factors produced by stem cells can also cause proarrhythmic effects. The review examines the factors that influence the proarrhythmic properties of administered stem cells and the mechanisms of arrhythmia development. The results indicate that further research should be carried out to establish the possible impact of stem cells on the development of arrhythmias. [ABSTRACT FROM AUTHOR]

Background: The initial rhythm is a known predictor of survival in extracorporeal cardiopulmonary resuscitation (ECPR) patients. However, the effect of the rhythm at hospital admission on outcomes in these patients is less clear., Methods: This observational, single-center study assessed the influence of the rhythm at hospital admission on 30-day survival and neurological outcomes at discharge in patients who underwent ECPR for out-of-hospital cardiac arrest (OHCA)., Results: Between January 2012 and December 2023, 1,219 OHCA patients were admitted, and 210 received ECPR. Of these, 196 patients were analyzed. The average age was 52.9 years (±13), with 80.6 % male. The median time to ECPR initiation was 61 min (IQR 54-72). Patients with ventricular fibrillation as both the initial and admission rhythm had the highest 30-day survival rate (52 %: 35/67), while those with asystole in both instances had the lowest (6 %: 1/17, log-rank p < 0.00001). After adjusting for age, sex, initial rhythm, resuscitation time, location, bystander, and witnessed status, asystole at admission was linked to higher 30-day mortality (OR 4.03, 95 % CI 1.49-12.38, p = 0.009) and worse neurological outcomes (Cerebral Performance Category 3-5) at discharge (OR 4.61, 95 % CI 1.49-17.62, p = 0.013)., Conclusions: The rhythm at hospital admission affects ECPR outcomes. Patients presenting with and maintaining ventricular fibrillation have a higher chance of favorable neurological survival, whereas those presenting with or converting to asystole have poor outcomes. The rhythm at hospital admission appears to be a valuable criterion for deciding on ECPR initiation., Competing Interests: Declaration of competing interest The corresponding author (JB) has received lecture honoraria from the Abiomed, Getinge, Xenios, Resuscitec, Novartis, Astra-Zeneca, Boegringer-Ingelheim.The remaining authors report no conflict of interest., (Copyright © 2024. Published by Elsevier B.V.)

Atrial fibrillation (AF) with multiple complications, high morbidity and mortality, and low cure rates, has become a global public health problem. Although significant progress has been made in the treatment methods represented by anti-AF drugs and radiofrequency ablation, the therapeutic effect is not as good as expected. The reason is mainly because of our lack of understanding of AF mechanisms. This field has benefited from mechanistic and (or) statistical methodologies. Recent renewed interest in digital twin techniques by synergizing between mechanistic and statistical models has opened new frontiers in AF analysis. In the review, we briefly present findings that gave rise to the AF pathophysiology and current therapeutic modalities. We then summarize the achievements of digital twin technologies in three aspects: understanding AF mechanisms, screening anti-AF drugs and optimizing ablation strategies. Finally, we discuss the challenges that hinder the clinical application of the digital twin heart. With the rapid progress in data reuse and sharing, we expect their application to realize the transition from AF description to response prediction. [ABSTRACT FROM AUTHOR]

Cardiovascular disease is one of the leading causes of death worldwide. Long-term and real-time monitoring of cardiovascular indicators is required to detect abnormalities and conduct early intervention in time. To this end, the development of flexible wearable/implantable sensors for real-time monitoring of various vital signs has aroused extensive interest among researchers. Among the different kinds of sensors, mechanical sensors can reflect the direct information of pressure fluctuations in the cardiovascular system with the advantages of high sensitivity and suitable flexibility. Herein, we first introduce the recent advances of four kinds of mechanical sensors for cardiovascular system monitoring, based on capacitive, piezoresistive, piezoelectric, and triboelectric principles. Then, the physio-mechanical mechanisms in the cardiovascular system and their monitoring are described, including pulse wave, blood pressure, heart rhythm, endocardial pressure, etc. Finally, we emphasize the importance of real-time physiological monitoring in the treatment of cardiovascular disease and discuss its challenges in clinical translation. [ABSTRACT FROM AUTHOR]

Juvenile myoclonic epilepsy (JME) is the most common form of genetic generalized epilepsy. Patients with JME are at risk of life-threatening heart rhythm and conduction disorders as well as sudden death syndrome due to several potential mechanisms: genetic, clinical, neuroanatomical, pharmacological, psychological, comorbid. This lecture reviews important elements of knowledge about the pharmacological predictors of cerebral-cardiac syndrome and sudden unexpected death in epilepsy. The arrhythmogenic potential of antiepileptic drugs most often used in JME (valproic acid, levetiracetam, lamotrigine, topiramate and zonisamide) is considered, none of which can be classified as class A (drug without risk of QT interval prolongation or TdP) regarding a risk of QT interval prolongation and cardiac arrhythmias. Patients with JME require dynamic video-electroencephalographic monitoring and 24-hour electrocardiographic monitoring to reduce a risk of life-threatening cardiac arrhythmias.

Abstract This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health (“mHealth”) technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self‐management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

Non-shockable initial rhythm is a known risk factor for high mortality at cardiac arrest (CA). However, knowledge on its association with self-reported health in CA survivors is still incomplete. To examine the associations between initial rhythm and self-reported health in CA survivors. This nationwide study used data from the Swedish Register for Cardiopulmonary Resuscitation 3–6 months post CA. Health status was measured using EQ-5D-5L and psychological distress by the Hospital Anxiety and Depression Scale (HADS). Kruskal-Wallis test was used to examine differences in self-reported health between groups of different initial rhythms. To control for potential confounders, age, sex, place of CA, aetiology, witnessed status, time to CPR, time to defibrillation, and neurological function were included as covariates in multiple regression analyses for continuous and categorical outcomes. The study included 1783 adult CA survivors. Overall, the CA survivors reported good health status and symptoms of anxiety or depression were uncommon (13.7% and 13.9% respectively). Survivors with PEA and asystole reported significantly more problems in all dimensions of health status (p = 0.037 to p < 0.001), anxiety (p = 0.034), and depression (p = 0.017) compared to VT/VF. Overall, these differences did not remain in the adjusted regression analyses. Initial rhythm is not associated with self-reported health when potential confounders are controlled. Initial rhythm seems to be an indicator of unfavourable factors causing the arrest, or factors related to characteristics and treatment. Therefore, initial rhythm may be used as a proxy for identifying patients at risk for poor outcomes such as worse health status and psychological distress. [ABSTRACT FROM AUTHOR]

General practitioners, therapists, and cardiologists do not have formal education (training) regarding cerebrocardial syndrome, primarily heart rhythm and conduction disorders in epilepsy and sudden unexpected death in epilepsy (SUDEP), as well as the potential arrhythmogenic effect of antiepileptic drugs. This lecture presents important elements of knowledge about the genetic predictors of cerebrocardial syndrome and SUDEP in juvenile myoclonic epilepsy, which is the most common form of genetic generalized epilepsy.

Background: Many bacterial and viral infections may cause sepsis or/and systemic or local proinflammatory responses that lead to life-threatening cardiovascular system failure. Severe bradycardia and/or bradyarrhythmias frequently accompany systemic inflammation and contribute to hemodynamic insufficiency. Markers for immunocompetent cells have been shown to be present in the tissue of the primary heart pacemaker, the sinoatrial node (SAN). However, the role of the resident cardiac immune cells in inflammation-induced bradycardia and SAN automaticity have still not been elucidated. Materials and methods: Confocal and bright field microscopy were used to identify toluidine blue-positive cells (TPC) in the SAN. Standard microelectrode technique and optical mapping were used to record action potentials (AP) and analyze activation pattern in the SAN tissue preparation from rats in presence of secretagogue C48/80. Results: Numerous TPC, which exhibit toluidine-accumulating granules, typical for mast cells, are revealed in the SAN region of the right atrium. The activation and degranulation of the resident mast cells by C48/80 leads to biphasic changes of the pacemaker AP rate in the SAN – an initial acceleration is followed by rate reduction. The activation of the resident mast cells causes an increase of the primary activation area in the SAN that probably underlies the AP rate increase in response to C48/80. In addition, the application of C48/80 causes the primary/leading activation point migration in the SAN and AP rate decrease is probably mediated by the shift of the primary pacemaker site to the region surrounding the coronary sinus. Moreover, inexcitable zones and conduction blocks induced in the central SAN myocardium by C48/80 underlie the suppression of automaticity. Conclusion: The degranulation of resident mast cells affects the pacemaker cardiomyocytes’ ability to generate spontaneous AP in the SAN tissue and causes shift of the dominant pacemaker site. Therefore, the activation of the resident mast cells in the SAN can be considered as a new mechanism of inflammatory induced bradyarrhythmias.

Objectives: Resistant hypertension (RHT) identifies a high-risk population; however, the effect of concomitant atrial fibrillation (AF) in this patient group is understudied. The present study aimed to investigate the effect of heart rhythm (HR) in this population. Materials and Methods: The study was designed as a retrospective, single-center, closed cohort archive screening study in a given time and outpatient data were reviewed. Patients with secondary hypertension, pseudo-RHT and heart failure were eliminated. Consecutive 101 RHT patients were included in the study and divided into two groups according to HR, sinus rhythm (SR) or AF. Baseline demographics were compared, and the correlation between N-terminal pro-brain natriuretic peptide (NT-proBNP), left atrial diameter (LAD) and age were investigated. Results: When comparing RHT patients according to HR, AF patients were older (mean age: 73.5±7.6 vs. 61.7±11.2 years, p<0.001), LAD was larger (50.0±3.5 vs. 40.9±4.0 mm, p<0.001), LVEF was lower (53.5±2.7 vs. 57.3±2.8%, p<0.001) and they had higher levels of NT-proBNP (1704.5±868.9 vs. 330.3±394.9 pg/mL) than the RHT patients in SR. The correlation between LAD and NT-proBNP level was found only in RHT patients with SR, not with AF. Conclusion: The co-presence of AF in RHT may indicate an advanced stage of the disease, not a simple arrhythmia, and the patients should be treated accordingly. Likewise, present study's findings indicate the need to specify the cut-off levels of NT-proBNP in AF in the absence of heart failure. [ABSTRACT FROM AUTHOR]

Objective: to study heart rate variability in university students engaged in competitive sports at the beginning of a training season. Materials and Methods: the study summarizes the results of 141 participants. The study group consisted of 61 athletes (22.7±1.3 years), 31 men (22.3±1.3 years) and 30 women (23.1±2.1 years). The control group included 80 students not involved in sports (23.6±1.5 years), 34 men (23.7±1.5 years) and 46 women (23.6±1.5 years). Heart rate variability was assessed by a cardiointervalogramm registration in the background recording of rest for 5 minutes, as well as during an active orthostatic test. A spectral analysis of heart rate wave structure included registration HF, LF, VLF-components, LF/HF ration, and the total power of all waves – TP; complex indices were determined, namely the index of vegetative balance (AMO/SD index) and C30:15 coefficient. Results: we found higher level total spectrum power, parasympathetic activity and reactivity regulation in the study group. We revealed higher spectral indices, as well as C30:15 during active orthostatic tests in the group of athletes. HRV indices of male athletes are higher, both at rest and in orthostasis. HRV indices of female athletes significantly differed only in orthostasis, demonstrating a higher level of regulation. Conclusions: at the beginning of a training season, we found high level of regulatory indices in the functional state of competitive athletes, both male and female. A variety of significant differences in HRV in the studied groups can be used for a dynamic monitoring of changes in regulatory processes during the training cycle.

Abstract Cardiac arrhythmia is an irregular heart rhythm that can lead to serious heart conditions and various organ disorders, and may cause sudden cardiac death. Catalpol belongs to the iridoid glycoside family and is highly abundant in Rehmannia glutinosa Libosch. The study included five groups such as group I (normal control), group II (treatment control), group III (low-dose treatment), group IV (medium-dose treatment) and group V (high-dose treatment). We investigated the therapeutic effects of catalpol on cardiac arrhythmia in human-induced pluripotent stem cells (iPSCs). Cell viability, lactate dehydrogenase (LDH) levels, lipid peroxidation, antioxidant activity, and caspase-3 and caspase-9 activities and protein levels were measured in normal control, treatment control, and treated (1, 10, and 100 µM) iPSC groups. Compared with the treatment control group, catalpol supplementation (1, 10, and 100 µM) increased iPSC cell viability by 7.5, 27.3, and 65.8%, respectively; reduced the LDH levels by 10.4, 31.3, and 75.2%, respectively; and reduced the lipid peroxidation levels by 7.7, 33.0, and 62.6%, respectively. The antioxidant levels were significantly higher in the treatment control group than in the normal control group. Catalpol (100 µM) reduced the caspase-3 and caspase-9 activities by more than 30% and increased expression of the corresponding proteins by more than 50%. These findings suggest that the naturally occurring iridoid glycoside catalpol is effective against aconitine-induced cardiac arrhythmia in iPSCs.

Background Electrocardiogram (ECG) signal classification plays a critical role in the automatic diagnosis of heart abnormalities. While most ECG signal patterns cannot be recognized by a human interpreter, they can be detected with precision using artificial intelligence approaches, making the ECG a powerful non-invasive biomarker. However, performing rapid and accurate ECG signal classification is difficult due to the low amplitude, complexity, and non-linearity. The widely-available deep learning (DL) method we propose has presented an opportunity to substantially improve the accuracy of automated ECG classification analysis using rhythm or beat features. Unfortunately, a comprehensive and general evaluation of the specific DL architecture for ECG analysis across a wide variety of rhythm and beat features has not been previously reported. Some previous studies have been concerned with detecting ECG class abnormalities only through rhythm or beat features separately. Methods This study proposes a single architecture based on the DL method with one-dimensional convolutional neural network (1D-CNN) architecture, to automatically classify 24 patterns of ECG signals through both rhythm and beat. To validate the proposed model, five databases which consisted of nine-class of ECG-base rhythm and 15-class of ECG-based beat were used in this study. The proposed DL network was applied and studied with varying datasets with different frequency samplings in intra and inter-patient scheme. Results Using a 10-fold cross-validation scheme, the performance results had an accuracy of 99.98%, a sensitivity of 99.90%, a specificity of 99.89%, a precision of 99.90%, and an F1-score of 99.99% for ECG rhythm classification. Additionally, for ECG beat classification, the model obtained an accuracy of 99.87%, a sensitivity of 96.97%, a specificity of 99.89%, a precision of 92.23%, and an F1-score of 94.39%. In conclusion, this study provides clinicians with an advanced methodology for detecting and discriminating heart abnormalities between different ECG rhythm and beat assessments by using one outstanding proposed DL architecture.

The cardiac conduction system (CCS) orchestrates the electrical impulses that enable coordinated contraction of the cardiac chambers. The T-box transcription factors TBX3 and TBX5 are required for cardiac conduction system development and associated with overlapping and distinct human cardiac conduction system diseases. We evaluated the coordinated role of Tbx3 and Tbx5 in the murine ventricular conduction system (VCS). We engineered a compound Tbx3:Tbx5 conditional knockout allele for both genes located in cis on mouse chromosome 5. Conditional deletion of both T-box transcriptional factors in the ventricular conduction system, using the VCS-specific Mink:Cre, caused loss of VCS function and molecular identity. Combined Tbx3 and Tbx5 deficiency in the adult VCS led to conduction defects, including prolonged PR and QRS intervals and elevated susceptibility to ventricular tachycardia. These electrophysiologic defects occurred prior to detectable alterations in cardiac contractility or histologic morphology, indicative of a primary conduction system defect. Tbx3:Tbx5 double knockout VCS cardiomyocytes revealed a transcriptional shift towards non-CCS-specialized working myocardium, suggesting reprogramming of their cellular identity. Furthermore, optical mapping revealed a loss of VCS-specific conduction system propagation. Collectively, these findings indicate that Tbx3 and Tbx5 coordinate to control VCS molecular fate and function, with implications for understanding cardiac conduction disorders in humans., Competing Interests: Conflict of Interest Statement None declared.

40 years ago a single experiment upset a decade of painstaking research on the mechanisms of rhythm generation in the heart. It did so by turning a theory of pacemaker activity upside down. Instead of attributing rhythm to decaying potassium current carrying outward current, it attributed the pacemaker depolarization to the slow activation of a channel conducting sodium ions into cardiac cells. But this was no standard upset of a theory. Like the replacement of Newtonian mechanics by relativity theory, the new theory explained every minute detail of the experimental observations that had established the theory it was replacing. Computational modelling of the heart achieved one of the major successes, the complete mapping of one theory onto another without challenging the correctness of any of the experimental findings. This review details the way in which this transition occurred and draws some important lessons for modelling of biological processes today. [ABSTRACT FROM AUTHOR]

Abstract—In this paper we focus on a meta-analysis where the data from studies using rat models are combined to evaluate the effects of hypothermia and hyperthermia on the cardiovascular function. For this meta-analysis, 25 articles from the PubMed database were selected. The research aim of these reports was to investigate how whole-body hypothermia and hyperthermia in normotensive conscious adult rats affect hemodynamic parameters (systemic blood pressure and heart rate). The effects of short-term severe hyperthermia (40–43°C), prolonged moderate hyperthermia (32–34°C), and short-term and prolonged hypothermia (4–9°C, sudden and gradual, with and without any changes in photoperiod) were investigated. It has been shown that the blood pressure and heart rate patterns in normotensive conscious rats in response to a change in the ambient temperature are determined according not only to the vector field showing the direction of temperature change, but also to the amplitude, suddenness, duration of the change, and concomitant conditions (e.g., the duration of photoperiod). [ABSTRACT FROM AUTHOR]

Spurred by federal legislation, professional organizations, and patients themselves, patient access to data from electronic cardiac devices is increasingly transparent. Patients can collect data through consumer devices and access data traditionally shared only with health care providers. These data may improve screening, self-management, and shared decision-making for cardiac arrhythmias, but challenges remain, including patient comprehension, communication with providers, and sustained engagement. Ways to address these challenges include leveraging visualizations that support comprehension, involving patients in designing and developing patient-facing digital tools, and establishing clear practices and goals for data exchange with health care providers. [ABSTRACT FROM AUTHOR]