External Validation of a Risk Score Model for Predicting Major Clinical Events in Adults After Atrial Switch.

BACKGROUND: A risk model has been proposed to provide a patient individualized estimation of risk for major clinical events (heart failure events, ventricular arrhythmia, all-cause mortality) in patients with transposition of the great arteries and atrial switch surgery. We aimed to externally validate the model. METHODS AND RESULTS: A retrospective, multicentric, longitudinal cohort of 417 patients with transposition of the great arteries (median age, 24 years at baseline [interquartile range, 18-30]; 63% men) independent of the model development and internal validation cohort was studied. The performance of the prediction model in predicting risk at 5 years was assessed, and additional predictors of major clinical events were evaluated separately in our cohort. Twenty-five patients (5.9%) met the major clinical events end point within 5 years. Model validation showed good discrimination between high and low 5-year risk patients (Harrell C index of 0.73 [95% CI, 0.65-0.81]) but tended to overestimate this risk (calibration slope of 0.20 [95% CI, 0.03-0.36]). In our population, the strongest independent predictors of major clinical events were a history of heart failure and at least mild impairment of the subpulmonary left ventricle function. CONCLUSIONS: We reported the first external validation of a major clinical events risk model in a large cohort of adults with transposition of the great arteries. The model allows for distinguishing patients at low risk from those at intermediate to high risk. Previous episode of heart failure and subpulmonary left ventricle dysfunction appear to be key markers in the prognosis of patients. Further optimizing risk models are needed to individualize risk predictions in patients with transposition of the great arteries.

An Overview of Arrhythmias in Pregnancy.

Cardiovascular disease significantly jeopardizes pregnancies in the United States, impacting 1% to 4% of pregnancies annually. Among complications, cardiac arrhythmias are prevalent, posing concerns for maternal and fetal health. The incidence of arrhythmias during pregnancy is rising, partly due to advances in congenital heart surgery and a growing population of women with structural heart disease. While most arrhythmias are benign, the increasing prevalence of more serious arrhythmias warrants a proactive approach. Guidance and reassurance suffice in many cases, but persistent symptoms require cautious use of antiarrhythmic drugs or other therapies for a safe outcome. Managing more serious arrhythmias requires a comprehensive, multidisciplinary approach involving specialists, including maternal-fetal medicine physicians, cardiologists, electrophysiologists, and anesthesiologists.

Impact of artificial intelligence arrhythmia mapping on time to first ablation, procedure duration, and fluoroscopy use.

INTRODUCTION: Artificial intelligence (AI) ECG arrhythmia mapping provides arrhythmia source localization using 12-lead ECG data; whether this information impacts procedural efficiency is unknown. We performed a retrospective, case-control study to evaluate the hypothesis that AI ECG mapping may reduce time to ablation, procedural duration, and fluoroscopy. MATERIALS AND METHODS: Cases in which system output was used were retrospectively enrolled according to IRB-approved protocols at each site. Matched control cases were enrolled in reverse chronological order beginning on the last day for which the technology was unavailable. Controls were matched based upon physician, institution, arrhythmia, and a predetermined complexity rating. Procedural metrics, fluoroscopy data, and clinical outcomes were assessed from time-stamped medical records. RESULTS: The study group consisted of 28 patients (age 65 ± 11 years, 46% female, left atrial dimension 4.1 ± 0.9 cm, LVEF 50 ± 18%) and was similar to 28 controls. The most common arrhythmia types were atrial fibrillation (n = 10), premature ventricular complexes (n = 8), and ventricular tachycardia (n = 6). Use of the system was associated with a 19.0% reduction in time to ablation (133 ± 48 vs. 165 ± 49 min, p = 0.02), a 22.6% reduction in procedure duration (233 ± 51 vs. 301 ± 83 min, p < 0.001), and a 43.7% reduction in fluoroscopy (18.7 ± 13.3 vs. 33.2 ± 18.0 min, p < 0.001) versus controls. At 6 months follow-up, arrhythmia-free survival was 73.5% in the study group and 63.3% in the control group (p = 0.56). CONCLUSION: Use of forward-solution AI ECG mapping is associated with reductions in time to first ablation, procedure duration, and fluoroscopy without an adverse impact on procedure outcomes or complications.

Elevated Interleukin-6 Levels Are Associated With an Increased Risk of QTc Interval Prolongation in a Large Cohort of US Veterans.

BACKGROUND: Although accumulating data indicate that IL-6 (interleukin-6) can promote heart rate-corrected QT interval (QTc) prolongation via direct and indirect effects on cardiac electrophysiology, current evidence comes from basic investigations and small clinical studies only. Therefore, IL-6 is still largely ignored in the clinical management of long-QT syndrome and related arrhythmias. The aim of this study was to estimate the risk of QTc prolongation associated with elevated IL-6 levels in a large population of unselected subjects. METHODS AND RESULTS: An observational study using the Veterans Affairs Informatics and Computing Infrastructure was performed. Participants were US veterans who had an ECG and were tested for IL-6. Descriptive statistics and univariate and multivariate regression analyses were performed to study the relationship between IL-6 and QTc prolongation risk. Study population comprised 1085 individuals, 306 showing normal (<5 pg/mL), 376 moderately high (5-25 pg/mL), and 403 high (>25 pg/mL) IL-6 levels. Subjects with elevated IL-6 showed a concentration-dependent increase in the prevalence of QTc prolongation, and those presenting with QTc prolongation exhibited higher circulating IL-6 levels. Stepwise multivariate regression analyses demonstrated that increased IL-6 level was significantly associated with a risk of QTc prolongation up to 2 times the odds of the reference category of QTc (e.g. QTc >470 ms men/480 ms women ms: odds ratio, 2.28 [95% CI, 1.12-4.50] for IL-6 >25 pg/mL) regardless of the underlying cause. Specifically, the mean QTc increase observed in the presence of elevated IL-6 was quantitatively comparable (IL-6 >25 pg/mL:+6.7 ms) to that of major recognized QT-prolonging risk factors, such as hypokalemia and history of myocardial infarction. CONCLUSIONS: Our data provide evidence that a high circulating IL-6 level is a robust risk factor for QTc prolongation in a large cohort of US veterans, supporting a potentially important arrhythmogenic role for this cytokine in the general population.

Malignant arrhythmias detection using a synthesis-by-analysis modeling method of arterial blood pressure signal.

Extreme bradycardia, extreme tachycardia, ventricular flutter fib, and ventricular tachycardia are four malignant arrhythmias (MAs) that lead to sudden cardiac death. It is very important to detect them in daily life. The arterial blood pressure (ABP) signal contains abundant pathological information about four MAs and is easy to be recorded under domestic conditions. Thus, a synthesis-by-analysis (SA) modeling method for ABP signal was proposed to detect the four MAs in this study. The average models of MAs and healthy subjects were obtained by SA modeling, and the change of each ABP wave was quantitively described by twelve parameters of wave models. Then, the probabilistic neural network (PNN) and random forest (RF) are trained to detect the MAs. The experimental data were employed from Fantasia and the 2015 PhysioNet/CinC Challenge databases. The SA modeling results show that some pathological and physiological changes could be extracted from the average models. The two-sample ks-test results between different groups are markedly different (h = 1, p < 0.05). The detection results show that the performances of PPN classifiers are less than that of RF. The kappa coefficients (KC) for the RF classifiers are 97.167 ± 1.46 %, 97.888 ± 0.808 %, 99.895 ± 0.545 %, 98.575 ± 1.683 % and 92.241 ± 1.517 %, respectively. The mean KC is 97.083 ± 0.67 %. Compared to the performance of some existing studies, the proposed method has better performance and is potential to diagnose MAs in m-health.

Phenotypic Expression and Clinical Outcomes in Patients With Arrhythmogenic Cardiomyopathies.

BACKGROUND: In recent years, it has become evident that arrhythmogenic cardiomyopathy (ACM) displays a wide spectrum of ventricular involvement. Furthermore, the influence of various clinical phenotypes on the prognosis of the disease is currently being assessed. OBJECTIVES: The purpose of this study was to evaluate the impact of phenotypic expression in ACM on patient outcomes. METHODS: We conducted an analysis of 446 patients diagnosed with ACM. These patients were categorized into 3 groups based on their phenotype: arrhythmogenic right ventricular cardiomyopathy (ARVC) (right-dominant ACM), arrhythmogenic left ventricular cardiomyopathy (ALVC) (left-dominant ACM), and biventricular arrhythmogenic cardiomyopathy (BIV). We compared clinical, instrumental, and genetic findings among these groups and also evaluated their outcomes RESULTS: Overall, 44% of patients were diagnosed with ARVC, 23% with ALVC, and 33% with BIV forms. Subjects showing with ARVC and BIV phenotype had a significantly higher incidence of life-threatening ventricular arrhythmias compared with ALVC (P < 0.001). On the other hand, heart failure, heart transplantation, and death caused by cardiac causes were more frequent in individuals with BIV forms compared to those with ALVC and ARVC (P < 0.001). Finally, patients with an ALVC phenotype had a higher incidence of hot phases compared with those with ARVC and BIV forms (P = 0.013). CONCLUSIONS: The comparison of ACM phenotypes demonstrated that patients with right ventricular involvement, such as ARVC and BIV forms, exhibit a higher incidence of life-threatening ventricular arrhythmias. Conversely, ACM forms characterized by left ventricular involvement, such as ALVC and BIV, show a higher incidence of heart failure, heart transplantation, and hot phases.

Primary Electrical Heart Disease-Principles of Pathophysiology and Genetics.

Primary electrical heart diseases, often considered channelopathies, are inherited genetic abnormalities of cardiomyocyte electrical behavior carrying the risk of malignant arrhythmias leading to sudden cardiac death (SCD). Approximately 54% of sudden, unexpected deaths in individuals under the age of 35 do not exhibit signs of structural heart disease during autopsy, suggesting the potential significance of channelopathies in this group of age. Channelopathies constitute a highly heterogenous group comprising various diseases such as long QT syndrome (LQTS), short QT syndrome (SQTS), idiopathic ventricular fibrillation (IVF), Brugada syndrome (BrS), catecholaminergic polymorphic ventricular tachycardia (CPVT), and early repolarization syndromes (ERS). Although new advances in the diagnostic process of channelopathies have been made, the link between a disease and sudden cardiac death remains not fully explained. Evolving data in electrophysiology and genetic testing suggest previously described diseases as complex with multiple underlying genes and a high variety of factors associated with SCD in channelopathies. This review summarizes available, well-established information about channelopathy pathogenesis, genetic basics, and molecular aspects relative to principles of the pathophysiology of arrhythmia. In addition, general information about diagnostic approaches and management is presented. Analyzing principles of channelopathies and their underlying causes improves the understanding of genetic and molecular basics that may assist general research and improve SCD prevention.

Ten years of subcutaneous defibrillator therapy: Consolidated clinical evidence and future perspectives.

The subcutaneous implantable cardioverter defibrillator (S-ICD) was developed as an alternative to the traditional transvenous implantable cardioverter defibrillator (TV-ICD), aiming to provide easier implantation, simplified detection algorithm of malignant ventricular arrhythmias and prevention from placing components in the cardiovascular system. The S-ICD is implanted subcutaneously or intramuscularly with the generator placed in the left midaxillary line and the lead tunneled subcutaneously in the left para-sternal region. Preimplant electrocardiogram screening is recommended to prevent implantation in patients at high risk of T wave over-sensing. Currently, the S-ICD is unsuitable for patients requiring pacing or cardiac resynchronization. Since the beginning, the S-ICD underwent extensive preclinical investigation until the first prospective multicentre trial demonstrating high efficacy and safety led to market release. While earlier studies focused on younger patients with higher ejection fraction, more recent studies showed favorable outcomes even in patients with comorbidities similar to those typically observed in patients receiving TV-ICD. The development of second and third generation devices has contributed to reduce inappropriate shocks and overcome previous limitations. The aim of this paper is to review the evidence in the literature over the past decade supporting S-ICD as a valid alternative to TV-ICD in terms of safety and efficacy, highlighting the improvements in technology, as well as outcomes.

Metabolomics Profiling Predicts Ventricular Arrhythmia in Patients with an Implantable Cardioverter Defibrillator.

Implantable cardioverter defibrillators (ICDs) reduce sudden cardiac death (SCD) when patients experience life-threatening ventricular arrhythmias (LTVA). However, current strategies determining ICD patient selection and risk stratification are inefficient. We used metabolomics to assess whether dysregulated metabolites are associated with LTVA and identify potential biomarkers. Baseline plasma samples were collected from 72 patients receiving ICDs. Over a median follow-up of 524.0 days (range 239.0-705.5), LTVA occurred in 23 (31.9%) patients (22 effective ICD treatments and 1 SCD). After confounding risk factors adjustment for age, smoking, secondary prevention, and creatine kinase MB, 23 metabolites were significantly associated with LTVA. Pathway analysis revealed LTVA associations with disrupted metabolism of glycine, serine, threonine, and branched chain amino acids. Pathway enrichment analysis identified a panel of 6 metabolites that potentially predicted LTVA, with an area under the receiver operating characteristic curve of 0.8. Future studies are necessary on biological mechanisms and potential clinical use.

Myocardial strain is associated with adverse cardiac events in patients treated with chimeric antigen receptor (CAR) T-cell therapy.

BACKGROUND: Cardiovascular events, including heart failure and arrhythmias, following chimeric antigen receptor (CAR) T-cell therapy are increasingly recognized. Although global longitudinal strain (GLS) has demonstrated prognostic utility for other cancer therapy-related cardiac dysfunction, less is known regarding the association of GLS with adverse cardiac events following CAR T-cell therapy. OBJECTIVES: To determine the association of baseline GLS with adverse cardiovascular events in adults receiving CAR-T cell therapy. METHODS: Patients who had an echocardiogram within 6 months prior to receiving CAR T-cell therapy were retrospectively identified. Clinical data and cardiac events were collected via chart review. Echocardiograms were analyzed offline for GLS, left ventricular ejection fraction, and Doppler parameters. Multivariable logistic regression was used to determine the association between adverse cardiovascular events and echocardiographic parameters. RESULTS: Among 75 CAR T-cell therapy patients (mean age 63.9, 34.7% female), nine patients (12%) experienced cardiac events (CEs) including cardiovascular death, new/worsening heart failure, and new/worsening arrhythmia within 1 year of treatment. In univariable models, higher baseline GLS (OR 0.78 [0.63, 0.96], p = .021) was associated with a lower risk of CE and higher baseline mitral E/e' (OR 1.40 [1.08, 1.81], p = .012) was associated with a higher risk of CE. After adjusting for age and LDH, higher baseline GLS (OR 0.65 [0.48-0.88], p = <.01) was associated with a lower risk of CE and higher baseline mitral E/e' (OR 1.56 [1.06, 2.29], p = .024) was associated with a higher risk of CE. CONCLUSION: Lower GLS and higher mitral E/e' on a baseline echocardiogram were associated with higher risk for CEs in patients receiving CAR T-cell therapy.

Epidemiology of arrhythmogenic ventricular cardiomyopathy in China.

BACKGROUND: Arrhythmogenic ventricular cardiomyopathy (AVC) is a common cause of ventricular arrhythmias and mortality, but limited data are available from large Asian cohorts. Our aim was to explore the current status of AVC and second, we examined the prevalence of ventricular tachycardia (VT), heart failure (HF) and mortality in patients with AVC in the Chinese population. HYPOTHESIS: At present, some studies have reported that the incidence of AVC is on the rise, which may be due to the increasing number of diagnostic methods for AVC. However, there is no epidemiological data on AVC in the Chinese population, so we speculate that the incidence of AVC in the Chinese population is increasing. METHODS AND RESULTS: We studied 15 888 adults from the Beijing Municipal Health Commission Information Center (BMHCIC) registry database in China from January 2010 to December 2020, and calculated the average annual percentage change (AAPC). Second, we determined the incidence of VT, HF and mortality in patients with AVC. Of the 10 318 men and 5570 women who were screened by cardiac magnetic resonance or examined by myocardial biopsy, there were a total of 256 newly diagnosed AVC patients (mean [SD]: 37.54[17.10]; 39.45% female). The incidence of AVC increased from 7.60 (3.12-12.06) in 2010 to 19.62 (11.51-27.75) per 1000 person-years in 2020. Males had higher incidence of AVC than females. The AAPC for the rising incidence of AVC was 8.9 %. Males had similar VT prevalence (70.32% vs. 62.38%, p = 0.19) and mortality (1.94% vs. 1.98%, p = 0.98) but lower HF prevalence (42.58% vs. 60.40%, p = 0.006), when compared to females. Radiofrequency ablation (RFA) was more likely to be performed in males (p = 0.006). CONCLUSIONS: The rising trend in AVC incidence was evident, with two-fold increase by 2020. Males with AVC had similar VT prevalence and mortality rate, but HF prevalence were lower than females, perhaps impacted by RFA use.

Left bundle branch pacing lead for sensing ventricular arrhythmias in implantable cardioverter-defibrillator: A pilot study (LBBP-ICD study).

BACKGROUND: Left bundle branch pacing (LBBP) has been suggested as an alternative modality for biventricular pacing in cardiac resynchronization therapy (CRT)-eligible patients. As it provides stable R-wave sensing, LBBP has been recently used to provide sensing of ventricular arrhythmia in patients receiving implantable cardioverter-defibrillator (ICD) with CRT. OBJECTIVE: The aim of this study was to analyze the long-term safety and efficacy of the LBBP lead for appropriate detection of ventricular arrhythmia and delivery of antitachycardia pacing (ATP) in patients requiring defibrillator therapy with CRT. METHODS: CRT-eligible patients who underwent successful LBBP-optimized ICD and LBBP-optimized CRT with defibrillator were enrolled. The LBBP lead was connected to the right ventricular-P/S port after capping the IS-1 connector plug of the DF-1-ICD lead. LBBP-optimized ICD or LBBP-optimized CRT with defibrillator was decided on the basis of correction of conduction system disease. Documented arrhythmic episodes and therapy delivered were analyzed. RESULTS: Thirty patients were enrolled. The mean age was 59.7 ± 10.5 years. LBBP resulted in an increase in left ventricular ejection fraction from 29.9% ± 4.6% to 43.9% ± 11.2% (P < .0001). During a mean follow-up of 22.9 ± 12.5 months, 254 ventricular arrhythmic events were documented. Appropriate events (n = 225 [89%]) included nonsustained ventricular tachycardia (VT) (n = 212 episodes [94%]), VT (n = 8 [3.5%]), and ventricular fibrillation (n = 5 [2.5%]). ATP efficacy in terminating VT was 75%. Eleven percent of episodes (n = 29) were inappropriately detected because of T-wave oversensing. Inappropriate therapy (ATP) was delivered for 14 episodes (5.5%). Three patients (10%) had worsening of tricuspid regurgitation. CONCLUSION: Sensing from the LBBP lead for arrhythmia detection is safe as ∼90% of the episodes were detected appropriately. Future studies with a dedicated LBBP-defibrillator lead along with algorithms to avoid oversensing can help in combining defibrillation with conduction system pacing.

Dynamic prediction of malignant ventricular arrhythmias using neural networks in patients with an implantable cardioverter-defibrillator.

BACKGROUND: Risk stratification for ventricular arrhythmias currently relies on static measurements that fail to adequately capture dynamic interactions between arrhythmic substrate and triggers over time. We trained and internally validated a dynamic machine learning (ML) model and neural network that extracted features from longitudinally collected electrocardiograms (ECG), and used these to predict the risk of malignant ventricular arrhythmias. METHODS: A multicentre study in patients implanted with an implantable cardioverter-defibrillator (ICD) between 2007 and 2021 in two academic hospitals was performed. Variational autoencoders (VAEs), which combine neural networks with variational inference principles, and can learn patterns and structure in data without explicit labelling, were trained to encode the mean ECG waveforms from the limb leads into 16 variables. Supervised dynamic ML models using these latent ECG representations and clinical baseline information were trained to predict malignant ventricular arrhythmias treated by the ICD. Model performance was evaluated on a hold-out set, using time-dependent receiver operating characteristic (ROC) and calibration curves. FINDINGS: 2942 patients (61.7 ± 13.9 years, 25.5% female) were included, with a total of 32,129 ECG recordings during a mean follow-up of 43.9 ± 35.9 months. The mean time-varying area under the ROC curve for the dynamic model was 0.738 ± 0.07, compared to 0.639 ± 0.03 for a static (i.e. baseline-only model). Feature analyses indicated dynamic changes in latent ECG representations, particularly those affecting the T-wave morphology, were of highest importance for model predictions. INTERPRETATION: Dynamic ML models and neural networks effectively leverage routinely collected longitudinal ECG recordings for personalised and updated predictions of malignant ventricular arrhythmias, outperforming static models. FUNDING: This publication is part of the project DEEP RISK ICD (with project number 452019308) of the research programme Rubicon which is (partly) financed by the Dutch Research Council (NWO). This research is partly funded by the Amsterdam Cardiovascular Sciences (personal grant F.V.Y.T).

Proposed diagnostic criteria for arrhythmogenic cardiomyopathy: European Task Force consensus report.

Arrhythmogenic cardiomyopathy (ACM) is a heart muscle disease characterized by prominent "non-ischemic" myocardial scarring predisposing to ventricular electrical instability. Diagnostic criteria for the original phenotype, arrhythmogenic right ventricular cardiomyopathy (ARVC), were first proposed in 1994 and revised in 2010 by an international Task Force (TF). A 2019 International Expert report appraised these previous criteria, finding good accuracy for diagnosis of ARVC but a lack of sensitivity for identification of the expanding phenotypic disease spectrum, which includes left-sided variants, i.e., biventricular (ABVC) and arrhythmogenic left ventricular cardiomyopathy (ALVC). The ARVC phenotype together with these left-sided variants are now more appropriately named ACM. The lack of diagnostic criteria for the left ventricular (LV) phenotype has resulted in clinical under-recognition of ACM patients over the 4 decades since the disease discovery. In 2020, the "Padua criteria" were proposed for both right- and left-sided ACM phenotypes. The presently proposed criteria represent a refinement of the 2020 Padua criteria and have been developed by an expert European TF to improve the diagnosis of ACM with upgraded and internationally recognized criteria. The growing recognition of the diagnostic role of CMR has led to the incorporation of myocardial tissue characterization findings for detection of myocardial scar using the late­gadolinium enhancement (LGE) technique to more fully characterize right, biventricular and left disease variants, whether genetic or acquired (phenocopies), and to exclude other "non-scarring" myocardial disease. The "ring-like' pattern of myocardial LGE/scar is now a recognized diagnostic hallmark of ALVC. Additional diagnostic criteria regarding LV depolarization and repolarization ECG abnormalities and ventricular arrhythmias of LV origin are also provided. These proposed upgrading of diagnostic criteria represents a working framework to improve management of ACM patients.

Arrhythmic risk profile in mitral valve prolapse: A systematic review and metanalysis of 1715 patients.

INTRODUCTION: Mitral valve prolapse (MVP) is a common clinical condition in the general population. A subgroup of patients with MVP may experience ventricular arrhythmias and sudden cardiac death ("arrhythmic mitral valve prolapse" [AMVP]) but how to stratify arrhythmic risk is still unclear. Our meta-analysis aims to identify predictive factors for arrhythmic risk in patients with MVP. METHODS: We systematically searched Medline, Cochrane, Journals@Ovid, Scopus electronic databases for studies published up to December 28, 2022 and comparing AMVP and nonarrhythmic mitral valve prolapse (NAMVP) for what concerns history, electrocardiographic, echocardiographic and cardiac magnetic resonance features. The effect size was estimated using a random-effect model as odds ratio (OR) and mean difference (MD). RESULTS: A total of 10 studies enrolling 1715 patients were included. Late gadolinium enhancement (LGE) (OR: 16.67; p = .005), T-wave inversion (TWI) (OR: 2.63; p < .0001), bileaflet MVP (OR: 1.92; p < .0001) and mitral anulus disjunction (MAD) (OR: 2.60; p < .0001) were more represented among patients with AMVP than in NAMVP. Patients with AMVP were shown to have longer anterior mitral leaflet (AML) (MD: 2.63 mm; p < .0001), posterior mitral leaflet (MD: 2.96 mm; p < .0001), thicker AML (MD: 0.49 mm; p < .0001), longer MAD length (MD: 1.24 mm; p < .0001) and higher amount of LGE (MD: 1.41%; p < .0001) than NAMVP. AMVP showed increased mechanical dispersion (MD: 8.04 ms; 95% confidence interval: 5.13-10.96; p < .0001) compared with NAMVP. CONCLUSIONS: Our meta-analysis proved that LGE, TWI, bileaflet MVP, and MAD are predictive factors for arrhythmic risk in MVP patients.

Lack of temporal correlations between COVID pandemic waves and the occurrence of malignant ventricular arrhythmias.

AIMS: Correlations between malignant ventricular arrhythmias and the COVID waves have never been investigated. METHODS AND RESULTS: Prevalence of malignant ventricular arrhythmias/sudden cardiac death has been correlated to the four COVID waves between the onset of pandemic and end 2021. No significant correlation was present in the temporal evolution of both COVID patients/positive tests and incidence of malignant ventricular arrhythmias, which tended to decrease after vaccination onset. CONCLUSION: We present evidence of complex higher-order periodicities and the co-existence of such regions with stable non-chaotic areas in ex vivo human hearts. We infer that the oscillation of the calcium cycling machinery is the primary mechanism of higher-order dynamics. These higher-order regions may act as niduses of instability and may provide targets for substrate-based ablation of VF.

[Development of Human Vital Signs and Body Posture Monitoring and Positioning Alarm Systems].

In view of the high incidence of malignant diseases such as malignant arrhythmias in the elderly population, accidental injuries such as falls, and the problem of no witnesses when danger occurs, the study developed a human vital signs and body posture monitoring and positioning alarm system. Through the collection and analysis of electrocardiogram (ECG), respiration (RESP) and acceleration (ACC) signals, the system monitors human vital signs and body posture in real time, automatically judges critical states such as malignant arrhythmias and accidental falls on the local device side, and then issues alarm information, opens the positioning function, and uploads physiological information and patient location information through 4G communication. Experiments have shown that the system can accurately determine the occurrence of ventricular fibrillation and falls, and issue position and alarm information.

Arrhythmic risk stratification in arrhythmogenic right ventricular cardiomyopathy.

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a heritable cardiomyopathy characterized by a predominantly arrhythmic presentation. It represents the leading cause of sudden cardiac death (SCD) among athletes and poses a significant morbidity threat in the general population. As a causative treatment for ARVC is still not available, the placement of an implantable cardioverter defibrillator represents the current cornerstone for SCD prevention in this setting. Thanks to international ARVC-dedicated efforts, significant steps have been achieved in recent years towards an individualized, patient-centred risk stratification approach. A novel risk calculator algorithm estimating the 5-year risk of arrhythmias of patients with ARVC has been introduced in clinical practice and subsequently validated. The purpose of this article is to summarize the body of evidence that has allowed the development of this tool and to discuss the best way to implement its use in the care of an individual patient.