Ventricular Tachycardia Detection Research Articles

Ventricular Arrhythmia Classification Using Similarity Maps and Hierarchical Multi-Stream Deep Learning.

Ventricular arrhythmias are the primary arrhythmias that cause sudden cardiac death. We address the problem of classification between ventricular tachycardia (VT), ventricular fibrillation (VF) and non-ventricular rhythms (NVR). To address the challenging problem of the discrimination between VT and VF, we develop similarity maps - a novel set of features designed to capture regularity within an ECG trace. These similarity maps are combined with features extracted through learnable Parzen band-pass filters and derivative features to discriminate between VT, VF, and NVR. To combine the benefits of these different features, we propose a hierarchical multi-stream ResNet34 architecture. Our empirical results demonstrate that the similarity maps significantly improve the accuracy of distinguishing between VT and VF. Overall, the proposed approach achieves an average class sensitivity of 89.68%, and individual class sensitivities of 81.46% for VT, 89.29% for VF, and 98.28% for NVR. The proposed method achieves a high accuracy of ventricular arrhythmia detection and classification. Correct detection and classification of ventricular fibrillation and ventricular tachycardia are essential for effective intervention and for the development of new therapies and translational medicine.

Catecholaminergic polymorphic ventricular tachycardia (CPVT): an insidious disease that can often lead to sudden cardiac death in young people

The first symptoms of catecholaminergic polymorphic ventricular tachycardia (CPVT) usually occur in childhood and adolescence. 60% of patients experience syncope before the age of 40. Sudden cardiac death (SCD) is the first symptom of the disease in 30-50% of patients with CPVT. Early diagnosis is therefore crucial for the patient's prognosis. The diagnosis of CPVT is confirmed by a normal resting ECG, exclusion of structural heart disease, detection of bidirectional or polymorphic ventricular tachycardia (VT) in the stress ECG and/or detection of a pathogenic mutant in a gene associated with CPVT. Up to 60% of CPVT patients carry changes in the RYR2 gene. This gene encodes the cardiac ryanodine receptor, the most important Ca2+-releasing channel of the sarcoplasmic reticulum, which plays a central role in the contraction and relaxation of the heart muscle. If the function of the ryanodine receptor is impaired, too much calcium enters the cells, which triggers life-threatening arrhythmias. The overactive ryanodine receptor is therefore the main target for gene therapy methods. Even though the development of gene therapy is progressing, there is still no causal therapy available and it is all the more important to make a diagnosis as early as possible, which enables appropriate behavior and adequate symptomatic therapy. The decisive factor here is the evaluation of the genetic analysis in the context of the clinical findings. Based on this, recommendations can be made for preventive measures and the avoidance of specific triggers that could lead to life-threatening arrhythmias.

Design of a low-area hardware architecture to predict early signs of sudden cardiac arrests

Sudden cardiac arrest (SCA) results in an unexpected and untimely death within minutes, and its early prediction can alert cardiac patients to a timely medical diagnosis. To detect early symptoms of an SCA, the detection and classification of ventricular tachycardias (VT) are of utmost importance. In this work, a low-area yet highly accurate hardware architecture for VT classification is proposed based on the detection of premature ventricular contraction (PVC) beats. After pre-processing of the ECG signals using a wavelet-based pre-processing unit, a characteristics-matching algorithm is used to detect the PVC beats, and a low-complexity adaptive decision-based logic classifier is used to classify them into four types of VTs, namely monomorphic, polymorphic, non-sustained VT (NSVT), and sustained VT (SVT). FPGA verification of the hardware architecture for the VT classifier using the Nexys 4 DDR Artix-7 board utilizes 10.4 % of the total available resources and displays the type of VT and the number of PVCs detected to help in determining the severity of SCA and the need for medical attention. The ASIC implementation of the proposed PVC-based VT classification using the SCL 180 nm CMOS technology results in an area overhead of 0.02 mm2 and a power consumption of 3.47 μW for a high accuracy rate of 98.2 %. When compared to the existing CA detection systems for wearable devices, the proposed one consumes the least area while achieving high detection rates.

An artificial intelligence-enabled Holter algorithm to identify patients with ventricular tachycardia by analysing their electrocardiogram during sinus rhythm.

Ventricular tachycardia (VT) is a dangerous cardiac arrhythmia that can lead to sudden cardiac death. Early detection and management of VT is thus of high clinical importance. We hypothesize that it is possible to identify patients with VT during sinus rhythm by leveraging a continuous 24 h Holter electrocardiogram and artificial intelligence. We analysed a retrospective Holter data set from the Rambam Health Care Campus, Haifa, Israel, which included 1773 Holter recordings from 1570 non-VT patients and 52 recordings from 49 VT patients. Morphological and heart rate variability features were engineered from the raw electrocardiogram signal and fed, together with demographical features, to a data-driven model for the task of classifying a patient as either VT or non-VT. The model obtained an area under the receiving operative curve of 0.76 ± 0.07. Feature importance suggested that the proportion of premature ventricular beats and beat-to-beat interval variability was discriminative of VT, while demographic features were not. This original study demonstrates the feasibility of VT identification from sinus rhythm in Holter.

Analysis of electrotherapy in patients with implantable cardioverter-defibrillator for primary prevention of sudden cardiac death according to remote monitoring data

Aim: To determine the factors associated with development of justified and inappropriate implantable cardioverter-defibrillator (ICD) activations in patients at high risk of sudden cardiac death based on the remote monitoring systemMaterial and Methods. We analyzed remote monitoring data from 2014 to 2022 in 132 patients with ICD for primary prevention of sudden cardiac death (SCD). Patients were divided into 2 groups 1 – patients with persistent paroxysmal tachyarrhythmias; 2 – patients without persistent paroxysms of ventricular tachycardia (VT) / ventricular fibrillation (VF). In case of inappropriate shocks, the causes and possible predictors of their development were analyzed.Results. Of 132 patients, 62 (46.9%) patients appeared to have persistent VT/VF. It was found that the probability of detecting persistent paroxysms of VT/VF decreased with a history of revascularization (p = 0.030) and increased in the absence of amiodarone therapy (p = 0.012), with increasing age (p = 0.035), with decreasing left ventricular ejection fraction (LVEF) less than 35% (p = 0.016). 71 arrhythmic episodes (17.9%) in 27 (20.4%) patients were considered as false detection of tachyarrhythmias. Analyzing the causes of inappropriate electrotherapy, different types of supraventricular tachyarrhythmias in the zone of VT detection (85.9%), including atrial fibrillation (25.4%), in smaller percentage of cases there was discovered T-wave detection 4.2%, noise on the electrode – 2.8%, 7.1% – double counter due to the operation of the cardiac contractility modulation device. When analyzing factors associated with the development of false detection, reliable results were obtained with regard to the presence of a history of atrial fibrillation (p = 0.036), implanted single-chamber ICD (p = 0.028).Conclusion. The development of persistent ventricular tachyarrhythmias was noted in 47% of patients with ICD as a part of primary prevention of sudden cardiac death, and 20.4% had the development of inappropriate detection and electrotherapy. Predictors of their occurrence have been identified, which can be used as development of strategies for shock minimization.

Efficacy of Ivabradine in Preventing Inappropriate Shock due to Sinus Tachycardia in a Patient with Cardiac Sarcoidosis.

We herein report a case of left ventricular dysfunction due to cardiac sarcoidosis following cardiac resynchronization therapy defibrillator (CRT-D) in an 87-year-old man. He presented to our hospital after receiving shock therapy while conscious. Device interrogation revealed that inappropriate shock occurred due to sinus tachycardia. Due to the setting of a low ventricular tachycardia (VT) detection rate because of a history of slow VT, increasing the VT detection rate was not feasible. After initiation of treatment with ivabradine, the sinus rate decreased and there was no recurrence of inappropriate shock during a 3-year follow-up period. Ivabradine was effective for preventing inappropriate shock due to sinus tachycardia.

New insertable cardiac monitors show high diagnostic yield and good safety profile in real-world clinical practice: results from the international prospective observational SMART Registry.

Insertable cardiac monitors (ICMs) are indicated for long-term monitoring of unexplained syncope or palpitations, and for detection of bradycardia, ventricular tachycardia, and/or atrial fibrillation (AF). The aim of our study was to evaluate the safety and clinical value associated with a new generation ICM (Confirm Rx™, Abbott, Illinois, USA), featuring a new remote monitoring system based on smartphone patient applications. The SMART Registry is an international prospective observational study. The main endpoints were ICM safety (incidence of serious adverse device and procedure-related events (SADEs) at 1 month), ICM clinical value (incidence of device-detected true arrhythmias and of clinical diagnoses and interventions), and patient-reported experience measurements (PREMs). A total of 1400 subjects were enrolled. ICM indications included syncope (49.1%), AF (18.8%), unexplained palpitations (13.6%), risk of ventricular arrhythmia (6.6%), and cryptogenic stroke (6.0%). Freedom from SADEs at 1 month was 99.4% (95% Confidence Interval: 98.8-99.7%). In the 6-month monitoring period, the ICM detected true cardiac arrhythmias in 45.7% of patients and led to clinical interventions in a relevant proportion of patients; in particular, a pacemaker implant was performed after bradycardia detection in 8.9% of subjects who received an ICM for syncope and oral anticoagulation therapy was indicated after AF detection in 15.7% of subjects with cryptogenic stroke. PREMs showed that 78.2% of subjects were satisfied with the remote monitoring patient app. The evaluated ICM is associated with an excellent safety profile and high diagnostic yield. Patients reported positive experiences associated with the use of their smartphone for the device remote monitoring.

Ventricular Fibrillation and Tachycardia Detection Using Features Derived from Topological Data Analysis

A rapid and accurate detection of ventricular arrhythmias is essential to take appropriate therapeutic actions when cardiac arrhythmias occur. Furthermore, the accurate discrimination between arrhythmias is also important, provided that the required shocking therapy would not be the same. In this work, the main novelty is the use of the mathematical method known as Topological Data Analysis (TDA) to generate new types of features which can contribute to the improvement of the detection and classification performance of cardiac arrhythmias such as Ventricular Fibrillation (VF) and Ventricular Tachycardia (VT). The electrocardiographic (ECG) signals used for this evaluation were obtained from the standard MIT-BIH and AHA databases. Two input data to the classify are evaluated: TDA features, and Persistence Diagram Image (PDI). Using the reduced TDA-obtained features, a high average accuracy near 99% was observed when discriminating four types of rhythms (98.68% to VF; 99.05% to VT; 98.76% to normal sinus; and 99.09% to Other rhythms) with specificity values higher than 97.16% in all cases. In addition, a higher accuracy of 99.51% was obtained when discriminating between shockable (VT/VF) and non-shockable rhythms (99.03% sensitivity and 99.67% specificity). These results show that the use of TDA-derived geometric features, combined in this case this the k-Nearest Neighbor (kNN) classifier, raises the classification performance above results in previous works. Considering that these results have been achieved without preselection of ECG episodes, it can be concluded that these features may be successfully introduced in Automated External Defibrillation (AED) and Implantable Cardioverter Defibrillation (ICD) therapies.

Training Convolutional Neural Networks on Simulated Photoplethysmography Data: Application to Bradycardia and Tachycardia Detection

Objective: To develop a method for detection of bradycardia and ventricular tachycardia using the photoplethysmogram (PPG). Approach: The detector is based on a dual-branch convolutional neural network (CNN), whose input is the scalograms of the continuous wavelet transform computed in 5-s segments. Training and validation of the CNN is accomplished using simulated PPG signals generated from RR interval series extracted from public ECG databases. Manually annotated real PPG signals from the PhysioNet/CinC 2015 Challenge Database are used for performance evaluation. The performance is compared to that of a pulse-based reference detector. Results: The sensitivity/specificity were found to be 98.1%/97.9 and 76.6%/96.8% for the CNN-based detector, respectively, whereas the corresponding results for the pulse-based detector were 94.7%/99.8 and 67.1%/93.8%, respectively. Significance: The proposed detector may be useful for continuous, long-term monitoring of bradycardia and tachycardia using wearable devices, e.g., wrist-worn devices, especially in situations where sensitivity is favored over specificity. The study demonstrates that simulated PPG signals are suitable for training and validation of a CNN.

Methodology for the nocturnal cardiac arrhythmia ancillary study of the ADVENT-HF trial in patients with heart failure with reduced ejection fraction and sleep-disordered breathing.

Sleep disordered breathing (SDB) may trigger nocturnal cardiac arrhythmias (NCA) in patients with heart failure with reduced ejection fraction (HFrEF). The NCA ancillary study of the ADVENT-HF trial will test whether, in HFrEF-patients with SDB, peak-flow-triggered adaptive servo-ventilation (ASVpf) reduces NCA. To this end, accurate scoring of NCA from polysomnography (PSG) is required. To develop a method to detect NCA accurately from a single-lead electrocardiogram (ECG) recorded during PSG and assess inter-observer agreement for NCA detection. Quality assurance of ECG analysis included training of the investigators, development of standardized technical quality, guideline-conforming semi-automated NCA-scoring via Holter-ECG software and implementation of an arrhythmia adjudication committee. To assess inter-observer agreement, the ECG was analysed by two independent investigators and compared for agreement on premature ventricular complexes (PVC) /h, premature atrial complexes/h (PAC) as well as for other NCA in 62 patients from two centers of the ADVENT-HF trial. The intraclass correlation coefficients for PVC/h and PAC/h were excellent: 0.99 (95%- confidence interval [CI]: 0.99-0.99) and 0.99 (95%-CI: 0.97-0.99), respectively. No clinically relevant difference in inter-observer classification of other NCA was found. The detection of non-sustained ventricular tachycardia (18% versus 19%) and atrial fibrillation (10% versus 11%) was similar between the two investigators. No sustained ventricular tachycardia was detected. These findings indicate that our methods are very reliable for scoring NCAs and are adequate to apply for the entire PSG data set of the ADVENT-HF trial.

Implantable cardioverter defibrillator in arrhythmogenic cardiomyopathy: which role for antitachycardia pacing?

Abstract Funding Acknowledgements Type of funding sources: None. Background Arrhythmogenic Cardiomyopathy (ACM) is an inherited cardiomyopathy characterized by ventricular arrhythmias and sudden cardiac death. Implantable cardioverter defibrillator (ICD) remains the only proven therapy to reduce mortality in ACM. Purpose The objective of this study was to identify characteristics of ventricular arrhythmias and treatment in patients with ACM. Method Retrospective analysis of the data of consecutives patients with confirmed diagnosis of ACM based on the proposed Padua Criteria, who underwent implantation of transvenous ICD from January 1992 and October 2021. The clinical data and information about appropriate and inappropriate ICD therapies were obtained from medical records with the review of the available intra-cardiac electrograms (EGMs). Results We enrolled 52 patients (69% males, mean age at implant 48.9 ±14.8 years), 27 (52%) were implanted for primary prevention, 25 (48%) for secondary prevention. After a median follow-up of 7.52 years [IQR: 4.37 - 12.0], 32 patients (61.5%) had 914 sustained episodes of ventricular arrhythmias (VA). 25 patients (48%) had 309 episodes of life-threatening arrhythmias (LT-VA), defined as sustained ventricular tachycardia ≥200 beats/min. In 29/32 patients (91%) ATP treated at least one episode of VA and in 14/25 (56%) at least one episode of LT-VA. Ventricular tachycardia (VT) detection was programmed at least 20 seconds, while VF detection was at least 7 seconds. Among patients with appropriate ICD activation, the first treated episode was a LT-VA in 50% of cases. Out of 914 VA episodes, 735 (80.4%) were treated with ATP and 179 (19.6%) with shocks. Considering LT-VA (cycle length 248 ± 25 ms), 201/309 (65%) and 108/309 (35%) episodes were treated with ATP and shocks, respectively. In 13 patients (25%) there was an inappropriate ICD activation, mostly caused by atrial fibrillation, while in 8 patients (15%) there was a complication needing reintervention (in 3 cases there was a loss of ventricular sensing dictating lead revision). Conclusions ACM patients are at risk of VA and LT-VA. The majority of VA at follow-up are monomorphic at rate <200 beats/minute, however the first treated VA episode is a LT-VA in half of cases. ATP is highly successful in terminating VT and even LT-VA, which questions the use of non-transvenous ICD in this young patient population. Nevertheless, transvenous ICDs are burdened by a relevant rate of lead complications which should be weighed in the choice of the ICD type.

Performance and Integration of Smartphone Wireless ECG Monitoring into the Enterprise Electronic Health Record: First Clinical Experience.

Introduction:Patient initiated, remote cardiac monitoring has proved to be a significant advance in the diagnosis and management of arrhythmias. Further improvements in ease of use and access to results will further improve health outcomes and cost-effectiveness. Here we describe a proof-of-concept evaluation to assess the feasibility of successfully implementing a cloud-based management system using KardiaPro (KP) for remote electrocardiogram (ECG) monitoring to interface into EPIC, an enterprise electronic health record (EHR) system.Methods:The KP management system was embedded using hypertext markup language (HTML) code directly into the EHR. Encrypted credentials and patient data were bundled with an application programming interface key allowing linkage of remote monitoring from patients’ smartphones. During the time of implementation, a total of 322 patients and 32 179 ECGs were recorded.Results:The KP-EHR interface provided full functionality, allowing detection, interpretation and documentation of atrial fibrillation (AF), flutter events, ventricular tachycardia, and complete heart block. Our study focused on KP’s detection of AF, and 16.7% of tracings were classified as probable AF with only 2.3% of tracings not analyzed by the KP algorithm because of tracings that were too noisy or truncated. Enhanced management was facilitated with clinical information immediately accessible. Blinded physician ECG review validated the KP proprietary algorithm interpretation and ECGs.Conclusions:Direct integration of KP into EHR was successful and practical. It allows for historical, point of care and immediate retrieval of remote ambulatory monitoring data and documentation into the electronic health record. KP EHR integration warrants further study as it has the potential to improve cost-effectiveness and clinical diagnostic value, leading to improvements in delivery of patient care.

Effect of adipose graft transposition procedure (AGTP) on the ischemic arrhythmogenic substrate: an MRI study in a swine model of chronic myocardial infraction

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Instituto de Salud Carlos III BACKGROUND Cardiac regenerative therapy is a promising treatment for patients with myocardial infarction (MI) and heart failure. Nevertheless, previous ex-vivo studies have raised concern on the potential increased risk of arrhythmic events following certain cell therapies. Adipose graft transposition procedure (AGTP) is a cardiac reparative therapy consisting in transposing a vascularized adipose flap from the autologous pericardium and placing it over the epicardial scar area and has demonstrated to reduce infarct size and improve the left ventricular ejection fraction in preclinical and human studies. PURPOSE To assess the effect of the AGTP on the post-MI scar composition and image-based ventricular tachycardia (VT) corridors detection by means of late gadolinium enhanced cardiac magnetic resonance (LGE-CMR). METHODS A left circumflex artery (first marginal branch) MI was induced in 9 Landrace X Large White Pigs by delivering 1-3 coils. Two weeks post-MI, all subjects underwent a 3 Tesla LGE-CMR and randomized to the AGTP or sham group. LGE-CMR was repeated 30 days post-treatment (6 weeks post-MI). The arrhythmogenic substrate was characterized with an advanced image post-processing tool (ADAS 3D) and included quantification of dense scar and border zone (BZ) mass and detection of ventricular tachycardia (VT) corridors (including corridor scar mass). RESULTS The overall scar mass did not differ between scans in the overall population (7.6 ± 3.5 g vs 7.5 ± 2.2 g in the baseline and post-treatment scans, respectively; p = 0.9). Compared to the sham subjects, those receiving AGTP showed an absolute reduction of the total (-3.2 ± 1.4 g vs. +2.4 ± 1.7 g, p = 0.04) and dense scar (-0.9 ± 0.4 g vs. +0.7 ± 0.5 g, p = 0.03). BZ mass tended to decrease in the AGTP group (-2.2 vs 1.63 g; p = 0.06). The AGTP group showed a trend to reduce the number of VT corridors (-1 ± 0.7 vs. +0.4 ± 0.2, p = 0.078) and corridor scar mass (-0.3 ± 0.26 g vs. +0.1 ± 0.1 g, p = 0.11) (figure). CONCLUSIONS Cardiac reparative therapy of MI with AGTP reduced dense scar mass, compared to the increase observed in the sham group. The trend to reduce the BZ mass and the number/mass of VT corridors suggests a beneficial effect on the arrhythmic remodeling of the post-MI scar. Abstract Figure. Reduction in corridor"s number

Reassessing the role of antitachycardia pacing in fast ventricular arrhythmias in primary prevention implantable cardioverter-defibrillator recipients: Results from MADIT-RIT

In Multicenter Automatic Defibrillator Implantation Trial - Reduce Inappropriate Therapy (MADIT-RIT), high-rate cutoff (arm B) and delayed therapy (arm C) reduced the risk of inappropriate implantable cardioverter-defibrillator (ICD) interventions when compared with conventional programming (arm A); however, appropriate but unnecessary therapies were not evaluated. The purpose of this study was to assess the value of antitachycardia pacing (ATP) for fast ventricular arrhythmias (VAs) ≥ 200 beats/min in patients with primary prevention ICD. We compared ATP only, ATP and shock, and shock only rates in patients in MADIT-RIT treated for VAs ≥ 200 beats/min. The only difference between these randomized groups was the time delay between ventricular tachycardia detection and therapy (3.4 seconds vs 4.9 seconds vs 14.4 seconds). In arm A, 11.5% patients had events, the initial therapy was ATP in 10.5% and shock in 1%, and the final therapy was ATP in 8% and shock in 3.5%. In arm B, 6.6% had events, 4.2% were initially treated with ATP and 2.4% with shock, and the final therapy was ATP in 2.8% and shock in 3.8%. In arm C, 4.7% had events, 2.5% were initially treated with ATP and 2.3% with shock, and the final therapy was ATP in 1.4% and shock in 3.3%. The final shock rate was similar in arm A vs arm B (3.5% vs 3.8%; P = .800) and in arm A vs arm C (3.5% vs 3.3%; P = .855) despite the marked discrepancy in initial ATP therapy utilization. In MADIT-RIT, there was a significant reduction in ATP interventions with therapy delays due to spontaneous termination, with no difference in shock therapies, suggesting that earlier interventions for VAs ≥ 200 beats/min are likely unnecessary, leading to an overestimation of the value of ATP in primary prevention ICD recipients.

Detection of shockable ventricular cardiac arrhythmias from ECG signals using FFREWT filter-bank and deep convolutional neural network

Among various life-threatening cardiac disorders, ventricular tachycardia (VT) and ventricular fibrillation (VF) are shockable ventricular cardiac arrhythmias (SVCA) which require immediate defibrillation therapy for the survival of patients. Timely and accurate detection of rapid VT or VF episodes using ECG signals is extremely important before initiating external defibrillator (AED) and implantable cardioverter-defibrillator (ICD) therapies. In this paper, a novel approach for the detection of SVCA using ECG signals is proposed. The fixed frequency range empirical wavelet transform (EWT) (FFREWT) filter-bank is introduced for the multiscale analysis of ECG signals. The modes evaluated using FFREWT of ECG signals are used as input to a deep convolutional neural network (CNN) for the detection of SVCA. The architecture of the proposed deep CNN comprises of four convolution, two pooling, and four dense layers. The ECG signals from various public databases are used to evaluate the proposed FFREWT domain deep CNN approach. The results show that the proposed approach has obtained an accuracy of 99.036%, 99.800%, and 81.250% for the classification of shockable vs non-shockable, VF vs Non-VF, and VT vs VF, respectively using 8 s ECG frames with 10-fold cross-validation (CV) strategy. Our proposed approach has obtained an average accuracy value of 97.592% using 8 s ECG frames with subject-specific CV. The hardware implementation of the proposed SVCA detection approach can be done using an Internet of things (IoT) driven patient monitoring system.

Sudden Cardiac Death-Relevant Events of Hypertrophic Cardiomyopathy in a Regional Japanese Cohort - Results From the Kochi RYOMA Study.

Background: Sudden cardiac death (SCD) is a most devastating complication of hypertrophic cardiomyopathy (HCM). The aim of this study was to clarify the clinical features of HCM in patients who experienced SCD-relevant events in an aged Japanese community.Methods and Results: In 2004, we established a cardiomyopathy registration network in Kochi Prefecture, and herein report on 293 patients with HCM who are followed as part of the registry. The mean (±SD) age at registration and diagnosis was 63±14 and 56±16 years, respectively. SCD-relevant events occurred in 19 patients during a mean follow-up period of 6.1±3.2 years (incidence rate 1.0%/year): sudden death in 9 patients, successful recovery from cardiopulmonary arrest in 4 patients, and appropriate implantable cardioverter–defibrillator discharge in 6 patients. At registration, 13 patients were in the dilated phase of HCM (D-HCM). During the follow-up period, HCM developed to D-HCM in 21 patients; thus, 34 patients in total had D-HCM. Multivariate analysis revealed that D-HCM at registration or during follow-up and detection of non-sustained ventricular tachycardia (NSVT) during follow-up were significant predictors of SCD-relevant events.Conclusions: In this HCM population in an aged Japanese community, the annual rate of SCD-relevant events was 1.0%. HCM developed to D-HCM in a considerable number of patients, and D-HCM and NSVT were shown to be independently associated with an increased risk of SCD-relevant events.

Combined right and left ventricular mechanical dispersion enhance the arrhythmic risk stratification in hypertrophic cardiomyopathy

BackgroundVentricular arrhythmias are the most frequent cause of sudden cardiac death in individuals with hypertrophic cardiomyopathy (HCM). In the present study we investigated if combined left ventricular (LV) and right ventricular (RV) mechanical dispersion (MD) are correlated with ventricular arrhythmias. We aimed also to analyze if MD enhances the arrhythmic risk stratification in HCM. MethodsThe cohort included 47 subjects with HCM and 36 healthy individuals. All the studied population underwent clinical, 24-h electrocardiographic (ECG) monitoring for detection and description of non-sustained ventricular tachycardia (NSVT) in terms of number of events, maximal rate and length and comprehensive transthoracic echocardiography, including strain rate imaging. MD was calculated as standard deviation of time from the peak of R wave on ECG to maximum LV or RV shortening in 17 LV and 3 RV segments. ResultsHCM subjects with NSVT on ECG monitoring had increased LVMD (81±18ms vs 42±8ms) and RVMD (52±26 vs 25±23ms) compared with the HCM group without NSVT or compared with the healthy controls. On receiver operating characteristic curves the cut-off values associated with optimal specificity and sensitivity were 62ms for LVMD and 39ms for RVMD. LVMD (OR=1.86, 95% CI 1–1.06, p=0.01) and RVMD (OR=1.04, 95% CI 1.01–1.07, p=0.003) were the only independent variables that correlated with longer and faster NSVT and furthermore improved the risk stratification of NSVTs. ConclusionsIn a cohort of subjects with HCM, LVMD and RVMD correlates with the presence of NSVT on ECG monitoring. Combined LVMD and RVMD may improve the risk stratification of HCM with NSVT.

Analysis of electrotherapy of cardioverter defibrillators implanted for the primary prevention of sudden cardiac death

Aim. To assess various types of electrotherapy and the reasons for its use in patients with implanted cardioverter defibrillators (ICD) for primary prevention of sudden cardiac death (SCD).Material and methods. A retrospective single-site study of 308 patients with implanted cardioverter defibrillators was conducted. Patients were divided into 2 groups: 1 — patients with persistent paroxysmal ventricular tachycardia (VT)/ ventricular fibrillation (VF); 2 — patients without persistent paroxysms of VT/VF. The standard ICD programming protocol was carried out intraoperatively, at 3-4 days after the implantation, then 1 time in 12 months, as well as unscheduled on request. Primary data was collected about paroxysms of ventricular and supraventricular rhythm disturbances, episodes of unmotivated detection of tachyarrhythmias, adequacy of use and types of ICD electrotherapy. The period of dynamic observation was 7 years.Results. The group with an increased risk of persistent paroxysmal VT/VF is patients with ischemic genesis of chronic heart failure (CHF), repeated myocardial infarction, persistent atrial fibrillation (AF), as well as with recorde episodes of unstable VT and ventricular extrasystoles at programming visits. In 54,1% of cases with persistent paroxysms of VT/VF, unjustified detection of ventricular arrhythmias was established. Its causes were: 1) AF with a high heart rate; 2) T-wave detection; 3) sinus tachycardia in the area of detection of VT; 4) atrial flutter with a high heart rate.Conclusion. In patients with primary prophylaxis of SCD, the use of ICD electrotherapy takes place not only due to paroxysms of VT/VF, but also because of both paroxysms of supraventricular rhythm disturbances and other features of rhythm perception by the device. To reduce the number of unjustified triggers during the installation of ICD electrotherapy program in patients with AF/atrial flutter, it is advisable to use a dedicated area of monitor VT and programmed long-term tachycardia detection for adequate rhythm discrimination.

Clinical history of acute myocarditis in patients with preserved left ventricular ejection fraction

The aim – to investigate the dynamic changes of the structural and functional state of the heart and the persistence of cardiac rhythm disorders in patients with acute myocarditis with preserved left ventricular ejection fraction (LV EF) during 6 months of follow-up.Materials and methods. 54 patients with acute myocarditis and preserved LV EF (> 40 %) of the left ventricle (LV) were screened. The examination was performed twice: in the first month from the debut of myocarditis and in 6 months of follow-up. Results and discussion. According to data obtained by CMR, in the 1st month from the disease onset, the early contrast on T1-weighted images and/or the high intensity of the signal on T2 images were detected in all patients, with their percentage being 66.6 % and 62.9 % respectively, and late enhancement was observed in 14.8 % of cases. After 6 months of observation, edema and myocardial hyperemia were detected only in 7.4 and 9.2 % of cases, and fibrotic changes were in 37.0 % of patients, while 59.2 % of patients had no pathological changes on CMR at all. The average number of affected by inflammatory changes LV segments in the 1st month was 2.33±0.23, and after 6 months it decreased to 1.43±0.17 segments (р<0.01). The value of LV EF increased from 47.3±2.3 % in the 1st month to 56.2±2.5 % after 6 months (р<0.05) of follow-up, and detection of non-sustained ventricular tachycardia (NSVT) episodes decreased from 20.4 % cases in the 1st month to 7.4 % of cases after 6 months. According to the results of the correlation analysis, a strong direct correlation was established between the number of LV segments involved in the inflammatory process in the 1st month from the myocarditis onset (r=0.81, р<0.01) as also after 6 months (r=0.72; р<0.01) and the presence of NSVT episodes, that was also confirmed by determining the exact Fisher criterion (p=0.019), statistically reliable correlations of the same direction were also established between the presence of NSVT episodes and fibrotic changes on cardiac MRI.Conclusions. For patients with acute myocarditis with a preserved LV EF, the absence of severe violations of the LV contractile function is characterized by a small amount of inflammatory lesions of myocardium. Clinically significant cardiac rhythm disorders, in particular episodes of non-sustained ventricular tachycardia, can be observed in these patients in the absence of significant violations of the structural and functional heart state and are associated with a greater number of LV segments affected by inflammatory and fibrotic changes.

Markov Models for Detection of Ventricular Arrhythmia.

The advent of portable cardiac monitoring devices has enabled real-time analysis of cardiac signals. These devices can be used to develop algorithms for real-time detection of dangerous heart rhythms such as ventricular arrhythmias. This paper presents a Markov model based algorithm for real-time detection of ventricular tachycardia, ventricular flutter, and ventricular fibrillation episodes. The algorithm does not rely on any noise removal pre-processing or peak annotation of the original signal. When evaluated using ECG signals from three publicly available databases, the model resulted in an AUC of 0.96 and F1-score of 0.91 for 5-second long signals and an AUC of 0.97 and F1-score of 0.93 for 2-second long signals.