Type Of Arrhythmia Research Articles

Association of Cardiac Sub-Structure Radiation Dose with Bradyarrhythmias and Tachyarrhythmias after Lung Cancer Radiotherapy

<h3>Purpose/Objective(s)</h3> Arrhythmias are the most common cardiac events following radiotherapy (RT) for non-small cell lung cancer (NSCLC). However, data detailing types of arrhythmias and associated cardiac sub-structure dose-volume predictors is limited. <h3>Materials/Methods</h3> Retrospective analysis of 748 patients with locally advanced NSCLC treated with RT. Cardiac chambers and coronary arteries were manually segmented and dose-volume histogram (DVH) parameters (mean, max, and volume [V] receiving X Gy [in 5 Gy increments]) were calculated. 15 Common Terminology Criteria for Adverse Events (CTCAE) arrhythmia types were assessed. Receiver operating curve and cut-point analyses estimating grade ≥3 bradyarrhythmias, atrial flutter/fibrillation (AF), non-AF supraventricular tachyarrhythmias (other SVT), and ventricular tachyarrhythmias (VT) were performed. Cox and Fine and Gray regressions were performed (non-cardiac death as a competing risk). <h3>Results</h3> The median age was 65 years, 128/748 patients experienced ≥1 Grade ≥3 CTCAE arrhythmia (median onset, 1.6 years). The 2-year cumulative incidences were: 11.9% overall, 9.0% AF, 1.8% other SVT, 1.0% VT, 1.7% bradyarrhythmias. DVH parameters with highest AUC predicting each arrhythmia group are in Table 1. Adjusting for pre-existing arrhythmia and coronary heart disease: 1) left atrium (LA) V5 Gy ≥60 cc was associated with an increased risk of AF (subdistribution hazard ratio [SHR] 2.06, 95% CI 1.29-3.28; p=.002); 2) right atrium (RA) V60 Gy ≥0.03 cc was associated with an increased risk of other SVT (SHR 4.72, 95% CI 1.65-13.50; p=.004); 3) left main (LM) coronary artery V5 Gy ≥1 cc was associated with an increased risk of VT (SHR 7.4, 95% CI 1.72-31.71; p=.007); and 4) LM V10 Gy ≥1 cc was associated with an increased risk of bradyarrhythmias (SHR 2.27, 95% CI 1.04-4.96; p=.04). The 2-year estimates of AF for LA V5 Gy ≥ 60 cc vs. <60cc were 14.1% vs 5.5% (p<.001), respectively. On all-cause mortality (ACM) analysis, adjusting for lung cancer and cardiac prognostic factors, LA V5 Gy ≥60 cc was associated with an increased risk of ACM (HR 1.22, 95% CI 1.00-1.49; p=.046), while the other DVH variables were not (P>0.05). The 2-year ACM for LA V5Gy ≥60 cc vs <60 cc was 54% vs 46% (p=.010), respectively. <h3>Conclusion</h3> To our knowledge, this is the first report describing functionally distinct arrhythmia classes being associated with RT dose to discrete atrial and coronary sub-structures. Specifically, LA V5 Gy ≥60 cc is associated with an increased risk of AF and mortality. These observations build on our growing knowledge of sub-structure dose leading to localized cardiac dysfunction and guide potential mitigation approaches.

Incidence and Prevalence of Cardiac Arrhythmias in Pericardial Syndromes.

Arrhythmias in pericardial syndromes have been poorly investigated and available data are mainly obtained from relevant studies however having different endpoints from arrhythmias. Thus, the incidence and prevalence of any type of arrhythmias may be actually higher than generally considered. Atrial arrhythmias, mainly atrial fibrillation and flutter have been reported as the most common rhythm disturbances in the setting of acute pericarditis. Concerning pathophysiology of atrial arrhythmias, in contrast to earlier hypothesis that they occur exclusively in the presence of an underlying structural heart disease, recent data support an arrhythmogenic potential of acute pericardial inflammation regardless of the presence of heart disease. In cases of myopericarditis, namely primarily pericarditis with evidence of myocardial involvement (i.e., troponin elevation without however overt left ventricular dysfunction and/or segmental wall motion abnormalities), ventricular arrhythmias appear to prevail. With reference to the rest of pericardial syndromes data on arrhythmias development are even more sparce. In particular, in constrictive pericarditis atrial tachyarrhythmias are the most commonly detected and seem to be related to disease severity and possibly to the underlying etiology. In this review we have summarized the available information on the incidence and prevalence of arrhythmias in pericardial syndromes. We wish to emphasize that the clinical significance of arrhythmias in this setting in terms of prognosis and optimal medical treatment (including need and safety of anticoagulation in atrial fibrillation/flutter complicating acute pericarditis), should be further investigated.

Cardiac arrhythmia diagnosis applying machine learning techniques

Cardiac arrhythmia affects millions of people worldwide. Although commonly occurring, identifying and correctly diagnosing is not a simple task. In this context, this paper presents a study on the application of Machine Learning to the identification and diagnosis of cardiac arrhythmias. Classifiers were obtained using the k-NN and SVM algorithms, and tests were performed using data from the Arrhythmia dataset, which consists of information obtained from patients' ECG examinations, as well as information related to their lifestyles. Three tests were performed; in the first one, the ability of classifiers to identify whether or not an arrhythmia episode occurred. In the second one, the performance of the classifiers in the identification of the arrhythmia type was verified, and in the third one, the investigation was performed considering the gender of the individuals. The results indicate that the use of Machine Learning may, in fact, assist specialists in the diagnosis of arrhythmias. In all tests k-NN presented better performance when compared to SVM. The best result among all tests was obtained by gender classification, where k-NN presented a accuracy of 94.03% in identifying arrhythmia occurrences in female patients.

A life-threatening arrhythmia detection method based on pulse rate variability analysis and decision tree.

Extreme bradycardia (EB), extreme tachycardia (ET), ventricular tachycardia (VT), and ventricular flutter (VF) are the four types of life-threatening arrhythmias, which are symptoms of cardiovascular diseases. Therefore, in this study, a method of life-threatening arrhythmia recognition is proposed based on pulse rate variability (PRV). First, noise and interference are wiped out from the arterial blood pressure (ABP), and the PRV signal is extracted. Then, 19 features are extracted from the PRV signal, and 15 features with highly important and significant variation were selected by random forest (RF). Finally, the back-propagation neural network (BPNN), extreme learning machine (ELM), and decision tree (DT) are used to build, train, and test classifiers to detect life-threatening arrhythmias. The experimental data are obtained from the MIMIC/Fantasia and the 2015 Physiology Net/CinC Challenge databases. The experimental results show that the DT classifier has the best average performance with accuracy and kappa coefficient (kappa) of 98.76 ± 0.08% and 97.59 ± 0.15%, which are higher than those of the BPNN (accuracy = 94.85 ± 1.33% and kappa = 89.95 ± 2.62%) and ELM (accuracy = 95.05 ± 0.14% and kappa = 90.28 ± 0.28%) classifiers. The proposed method shows better performance in identifying four life-threatening arrhythmias compared to existing methods and has potential to be used for home monitoring of patients with life-threatening arrhythmias.

Decrease of glutathione peroxidase in arrhythmic cardiac pathology in young individuals and its therapeutic implications.

Glutathione peroxidase (GPx), as an antioxidant enzyme, is involved in the regulation of processes that cause cellular oxidative stress, with implications in various pathologies. The aim of the present study was to evaluate GPx variations in patients with arrhythmic, non-structural cardiac disorders. The research was performed on 120 patients, with a mean age of 33 years old, divided into 3 equal groups, of which 2 groups included patients with cardiac arrhythmias, the first group, associated with dyslipidemia and the second one, without dyslipidemia, and a control group consisting of healthy individuals. The method for determining GPx was based on the GPx enzyme catalysis reaction of the reduced glutathione (GSH) oxidation reaction by cumene hydroperoxide. The results revealed that GPx variation was decreased in patients with cardiac arrhythmias, with or without dyslipidemia, up to 66 and 74% of mean control values, respectively, the differences being statistically significant, showing the existence of an oxidative stress imbalance, that may be involved in triggering arrhythmogenic electrochemical mechanisms. The GPx deficiency determined in relation to cardiac arrhythmias was in dyslipidemic and non-lipidemic patients as follows: 29-35% in sinus bradycardia, 31-35% in associated cardiac arrhythmias, 30-33% in sinus tachycardia, 27-33% in atrial fibrillation, 32-33% in atrial flutter, 27-32% in atrial extrasystolic arrhythmia, 28-30% in ventricular extrasystolic arrhythmia and 18-26% in paroxysmal supraventricular tachycardia. Collectively, the results revealed that GPx, an antioxidant enzyme, is a specific biomarker, whose decrease indicated the existence of oxidative stress in young individuals with cardiac arrhythmias and its involvement in arrhythmogenic electrochemical processes. In addition, GPx deficiencies were between 18-35% in all types of cardiac arrhythmias, the highest being recorded in sinus bradycardia and the lowest in paroxysmal supraventircular tachycardia. Furthermore, the oxidative stress favored by the decrease of GPx induced lipid oxidation, regardless of the presence or absence of dyslipidemia, which triggered the formation of anti-lipid antibodies and a subclinical endothelial aggression, with early atherosclerotic potential. GPx evaluation may argue for the existence of oxidative stress in non-structural cardiac arrhythmias, and by its proper correction (antioxidants), prophylaxis of atherogenic dysfunction.

Smart Pacemaker: A Review.

Since the first pacemaker was implanted, nearly 60 years have passed. Since then, pacemaker technology has made major advancements that have increased both its safety and effectiveness in treating people with bradyarrhythmias. The repeated stimulation of cells in specialized "pacemaker" regions of the mammalian heart and the transmission of stimulus via the ventricles serve as evidence that the electrical function of the mammalian heart is necessary for a regular mechanical (pump) role. The development of action potentials in individual cardiac cells is linked to myocardial electrical activity and the heart's regular cooperative electrical functioning. A container or pulse initiator that houses the battery and electronics, as well as lines that connect to the myocardium to deliver a depolarizing pulse and detect intrinsic cardiac stimulation, are all parts of a pacemaker. Defibrillators could be used with artificial hearts that have electrical pacemakers integrated into them in order to treat arrhythmia, heart failure, and cardiac arrest. Modern pacemakers have units for supporting patients with other disorders like "heart failure," which happens when the heart does not pump as forcefully as it should. While many pacemakers are effective in treating different types of arrhythmias (irregular heartbeats), they also have units for treating them.

Various arrhythmia types and their day-by-day occurrence rates over a 14-day period using a P-wave sensitive ambulatory ECG monitored population

Abstract Background Many studies on ECG monitoring and arrhythmia detection use the term “diagnostic yield”, a vague term and one without the type of diagnostic precision that cardiologists value. Moreover, diagnostic yield of specific arrhythmias is not well understood on a day-by-day basis. Purpose We used a continuous 14-day ECG monitor to record the incremental occurrence of a broad variety of specific arrhythmias each day from a general outpatient population suspected of having an arrhythmia. Methods A total of 546 patients were monitored for 14±1 day in the absence of artifact that would otherwise obscure the rhythm. Without such stipulations, arrhythmias could not be truly categorized as a function of time. Patients were randomly selected who satisfied the aforementioned criteria. The studies were prescribed by the patient's managing physician for standard clinical indications, and they spanned across 237 distinct institutions. The recordings were interpreted by 3 serial readers clinically knowledgeable on electrophysiological principles of arrhythmia diagnostics. All reports were then confirmed in their entirety by a cardiac electrophysiologist. The daily diagnostic rate for specific arrhythmia occurrence was then tabulated. Of note, algorithmic and AI diagnostic approaches were not relied upon for arrhythmia diagnoses. Results Select arrhythmia/conduction abnormalities are shown in the attached Figure, demonstrating different arrhythmias manifesting at different rates. In 61% of pts, at least one rhythm disorder was found that could affect patient management over 14 days. In 28% of pts, two disorders were found while 12% had three or more disorders. P-wave specificity on the ECG aided in identifying 67.9% of those unique arrhythmias. When more than one arrhythmia type was identified, they typically occurred on different days. In contrast, the standard 1-day report, if implemented, would have diagnosed only 20% of patients and rarely would have found multiple rhythm abnormalities Conclusion Different arrhythmia categories manifest at different rates on a 14-day continuous ECG. Clinical abnormalities in rhythm and/or conduction occur in 61% of patients randomly selected from a broad array of institutions. Moreover, 28% had 2 disorders and 12% had &amp;gt;3 disorders, usually occurring on different days. Lastly, 67.9% of rhythms were identified due to a high fidelity P-wave ECG signal. These findings suggest that a 14-day P-wave sensitive ECG recording has substantive diagnostic value even if a suspected arrhythmia were to occur on day 1. Further, ECG recordings of 1 day (i.e., standard Holter monitor duration) severely diminish diagnostic value and should be avoided. Funding Acknowledgement Type of funding sources: None.

Can artificial intelligence prediction of successful atrial fibrillation catheter ablation therapy be interpretable?

Abstract Background Radiofrequency catheter ablation (RFCA) therapy is the first-line treatment for atrial fibrillation (AF), the most common type of cardiac arrhythmia globally. However, the procedure currently has low success rates in dealing with persistent AF, with a reoccurrence rate of ∼50% post-ablation. Therefore, artificial intelligence (AI), particularly deep learning (DL), has increasingly been applied to improve and optimise treatments for AF. However, AI is limited by its black-box nature. Therefore, a factor hindering the broad clinical application of DL in AF is the lack of assurance that the DL model is using physiological relevant features when making its prediction. In order to provide this assurance, its decision process needs to be interpretable and have biomedical relevance. Aim This study aims to explore interpretability in DL prediction of successful ablation therapy for AF and evaluate if pro-arrhythmogenic regions in the left atrium (LA) were used in its decision process. Methods LA models with segmented fibrotic tissue were derived from 122 late gadolinium-enhanced magnetic resonance (LGE MR) images of persistent AF patients. To increase the dataset size, an additional 199 synthetic LA tissue models were generated from the LGE MR images. Two ablation strategies were simulated: fibrosis-based ablation (FIBRO) and a rotor-based ablation (ROTOR). RFCA strategy success was determined by its ability to terminate persistent AF in 2s with less than 40% of the tissue ablated [1]. A convolutional neural network (CNN) was developed to predict the success of each RFCA strategy, and gradient weighted class activation maps (GradCAM) were used to assess if the CNN was using locations of pro-arrhythmogenic regions in its decision process on an independent test set of 50 LA tissue models. Results For predicting the success of the FIBRO strategy, the CNN model had an AUC (area under the receiver operating characteristic curve) of 0.92±0.02, recall of 0.89±0.03 and precision of 0.82±0.02. For the ROTOR strategy, the AUC was 0.77±0.02, the recall was 0.93±0.04 and the precision was 0.76±0.02. Finally, the independent test set's GradCAM saliency maps showed that 62±25% and 71±13% of ablation lesions (known from the LA model simulations, but unseen by the CNN during training) coincided with informative regions in the saliency maps for the FIBRO and ROTOR strategies, respectively (Figure 1). Conclusion The most informative regions of the saliency maps coincided with the successful ablation lesions, suggesting that the DL model was able to identify ablated pro-arrhythmogenic regions by leveraging structural features of LGE MR images. In the future, this technique could provide a clinician with a decision support tool and increase confidence in the AI prediction. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): UK Medical Research Council

Atrial-specific reduction of Kir2.1 channel pore diameter in addition to loss of inward-going rectification underlies inducible atrial fibrillation in a mouse model of short QT syndrome type 3

Abstract Introduction Short QT Syndrome Type 3 (SQTS3) is an extremely rare arrhythmogenic disease caused by gain-of-function mutations in the KCNJ2 gene coding the inward rectifier potassium channel Kir2.1. We investigated arrhythmogenic mechanisms associated with a de-novo mutation (E299V) in Kir2.1 in an 11-year-old boy presenting an extremely abbreviated QT interval, paroxysmal atrial fibrillation, and mild left ventricular dysfunction. Amino acid E299 in the Kir2.1 sequence is necessary for polyamine binding induced inward rectification. Purpose Test the hypothesis that Kir2.1E299V induces reduced conductance and lack of rectification that causes electrical defects in atrial cardiomyocytes, predisposing patients to atrial arrhythmias. Methods We used intravenous adeno-associated virus-mediated gene transfer to generate mice expressing wild-type (WT) and the E299V mutant protein. We used ECG, intracardiac stimulation, patch-clamp, molecular biology and computational modelling to characterize the models and study arrhythmia mechanisms in the atria and ventricles. Results We confirmed WT or mutant Kir2.1 gene expression specifically in the mouse heart. On ECG, the corrected QT (QTc) interval of Kir2.1E299V mice was significantly shorter than Kir2.1WT mice (p&amp;lt;0.0001). The PR interval in Kir2.1E299V was also significantly shorter than WT mice (p&amp;lt;0.0001). On intracardiac stimulation, the largest proportion of arrhythmic events occurred in the atria, as 7 out of 9 Kir2.1E299V mice presented &amp;gt;1 second atrial flutter/fibrillation, while only 2 out of 10 Kir2.1WT mice showed this type of arrhythmia (p=0.023). On patch clamping, both atrial and ventricular cardiomyocytes expressing Kir2.1E299V had extremely abbreviated action potential durations (APD90) at all frequencies studied (p&amp;lt;0.0001). The current/voltage relation of ventricular Kir2.1E299V cardiomyocytes revealed an absence of inward-going rectification and increased IK1 at voltages positive to −80 mV compared to Kir2.1WT cardiomyocytes (p&amp;lt;0.0001). In contrast, while in the atrial Kir2.1E299V cardiomyocytes the outward IK1 was increased at voltages positive to −80 mV with loss of rectification, IK1 was significantly reduced at voltages negative to −80 mV (p&amp;lt;0.0001), suggesting a loss of function leading to atrial arrhythmia inducibility. A higher proportion of Kir2.2 at atrial level and atomic in-silico 3D simulations suggested that the mutation impaired polyamine block of the Kir2.1E299V-Kir2.2 channel while reducing the pore diameter. Conclusions This first in-vivo mouse model of cardiac-specific SQTS3 recapitulates the electrophysiological phenotype of a patient with the Kir2.1E299V mutation. The mutation results in a Kir2.1 gain-of-function mediated by and absence of rectification. The predominant arrhythmias induced in these SQTS3 mice were supraventricular likely due to the combined lack of inward rectification and atrial-specific reduced pore diameter of the Kir2.1E299V-Kir2.2 channel. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): La Caixa FoundationLa Maratό TV3 Foundation

Arrhythmia in pregnant women: what management is better?

Abstract Background Arrhythmias in pregnant women are commonly seen but have not been extensively studied. Drug therapy or catheter ablation during pregnancy may be required in cases of maternal arrhythmias. However, the studies did not examine the outcomes of pregnancy in cases with different management of arrhythmias. Objective We aimed to determine if there are any differences in pregnancy outcomes in women with disparate types of arrhythmia treatment. Methods We conducted a prospective study of all pregnant patients who were admitted to our hospital with arrhythmias from 2017–2020. For patients with benign arrhythmias drug therapy was not required (n=11; 14.5%, 1st group). Antiarrhythmic treatment was justified in cases with frequent symptoms and haemodynamic instability (n=65; 85.5%). Patients with effective antiarrhythmic therapy were included in 2nd group (n=31; 40.8%). In patients with drug refractory and dangerous rhythm disturbances (n=34; 44.7%, 3d group) were performed zero-fluoroscopy catheter ablation. Results A total of 76 pregnant women were admitted with arrhythmias. Mean age was 27.24±5.15 years, mean gestation age 21.27±5.34 weeks. Supraventricular tachycardia was the most common arrhythmias (n=41; 53.9%) This was followed by premature contractions (n=27; 35.6%) and ventricular tachycardia (n=8; 10.5%). There was significant difference in frequency of performed catheter ablation for disparate types of arrhythmia: 70.7% for cases of supraventricular tachycardia, 25% - ventricular tachycardia and 11.1% - premature contractions (p=0.000). Ablations were effective in all cases without adverse outcome. All ablations were performed without fluoroscopy. Vaginal delivery was in the majority in all groups (75.6% vs 62.5% vs 74.1%, p=0.736). Similarly, no differences were noted in obstetric complication (14.6% vs 12.5% vs 18.5%, p=0.656). None of them had fetal mortality. Conclusions Some patients with arrhythmias needed catheter ablation during pregnancy. There was no significant difference in type of delivery and neonatal outcomes in women with separate management of arrhythmias. Funding Acknowledgement Type of funding sources: None.

Risk factors of early postoperative cardiac arrhythmia after pediatric cardiac surgery: A single-center experience.

To evaluate the incidence of arrhythmia in the early postoperative period and to identify its risk factors among pediatric patients following cardiac surgery at King Abdulaziz University Hospital (KAUH), Jeddah, Saudi Arabia, between 2015-2020. Out of 1242 patients, a total of 821 aged <18 years who underwent cardiac surgery were included in this retrospective cohort carried out in June 2021 at KAUH, Jeddah, Saudi Arabia. Information retrieved from the hospital medical records had patients' demographics, types of arrhythmias, hemodynamic stability, electrolyte disturbances, cardiopulmonary bypass (CPB), and aortic cross-clamp (AXC) durations. Univariate and multivariate logistic regression analyses were used to evaluate the possible risk factors associated with postoperative arrhythmia. Of the 821 patients, 140 (17.1%) developed arrhythmia postoperatively. The most common arrhythmias were junctional ectopic tachycardia (JET, 51.4%), atrioventricular block (27.1%), and supraventricular tachycardia (10%). The majority of cases occurred on the first day postoperatively (79.3%). Patients with postoperative arrhythmias had a more prolonged CPB (p=0.0001) and AXC (p=0.005) time, electrolytes disturbances (p=0.021), and hemodynamic instability (p=0.0001) than other patients. Postoperative arrhythmia, especially JET, is common after pediatric cardiac surgery. Prolonged cardiopulmonary bypass, prolonged aortic cross-clamping, electrolytes disturbances, and hemodynamic instability are possible risk factors for postoperative cardiac arrhythmias.

Traumatic Injuries Following Mechanical versus Manual Chest Compression.

ObjectiveSurvival after out-of-hospital cardiac arrest (OHCA) depends on multiple factors, mostly quality of chest compressions. Studies comparing manual compression with a mechanical active compression-depression device (ACD) have yielded controversial results in terms of outcomes and injury. The aim of the present study was to determine whether out-of-hospital ACD cardiopulmonary resuscitation (CPR) use is associated with more skeletal fractures and/or internal injuries than manual compression, with similar duration of cardiopulmonary resuscitation (CPR) between the groups.MethodsThe cohort included all patients diagnosed with out-of-hospital cardiac arrest (OHCA) at a tertiary medical center between January 2018 and June 2019 who achieved return of spontaneous circulation (ROSC). The primary outcome measure was the incidence of skeletal fractures and/or internal injuries in the two groups. Secondary outcome measures were clinical factors contributing to skeletal fracture/internal injuries and to achievement of ROSC during CPR.ResultsOf 107 patients enrolled, 45 (42%) were resuscitated with manual chest compression and 62 (58%) with a piston-based ACD device (LUCAS). The duration of chest compression was 46.0 minutes vs. 48.5 minutes, respectively (p=0.82). There were no differences in rates of ROSC (53.2% vs.50.8%, p=0.84), cardiac etiology of OHCA (48.9% vs.43.5%, p=0.3), major complications (ribs/sternum fracture, pneumothorax, hemothorax, lung parenchymal damage, major bleeding), or any complication (20.5% vs.12.1%, p=0.28). On multivariate logistic regression analysis, factors with the highest predictive value for ROSC were cardiac etiology (OR 1.94;CI 2.00–12.94) and female sex (OR 1.94;CI 2.00–12.94). Type of arrhythmia had no significant effect. Use of the LUCAS was not associated with ROSC (OR 0.73;CI 0.34–2.1).ConclusionThis is the first study to compare mechanical and manual out-of-hospital chest compression of similar duration to ROSC. The LUCAS did not show added benefit in terms of ROSC rate, and its use did not lead to a higher risk of traumatic injury. ACD devices may be more useful in cases of delayed ambulance response times, or events in remote locations.

Low-Cost ECG Analyzing System

As we are aware of the fact that a fully functional and a healthy heart is a key for a living being to remain alive. In order to monitor the proper functioning of the heart the primitive method of Electrocardiogram (ECG) can be adopted, which keeps the beats in check. The state of having an irregular heartbeat is known as Arrhythmia. The types of Arrhythmia can be apparent based on the factors that cause it. ECG signals consist of ‘PQRST’ waves. To identify the types of Arrhythmia it is vital to analyse the PQRST wave. In order to avoid fatality and to provide immediate medical assistance the ECG of the patient should be analyzed in real time. The project makes use of the AD8232 sensor alongside its interfacing with Arduino Nano to detect ECG signals. Arduino in this case is not only used as an Analog to Digital Converter (ADC) but also as a Sampler. Using Java APIs and Windowing Algorithm the intervals of the PQRST wave is thoroughly analyzed using Novel windowing algorithm. To conduct further analysis and detect the abnormalities in the captured waves it is compared with the standard ECG signals of a healthy person. The final results are shown on the system as well as on the cloud interface to improve the QoS in the healthcare system. The paper thus aims at reducing the overall treatment cost by introducing a low cost ECG Analysis System.

Impact of COVID-19 on the heart: Insight and current evidence based knowledge among Physicians

COVID 19 and its impact on the heart is a must to understand the disease in order to diagnose and manage the disease in time with a purpose of curbing down the fatality. This study aims to test and identify the gaps if any between the “Insight” and “current evidence based Knowledge” on the Impact of COVID-19 on the heart. A questionnaire based qualitative cross sectional descriptive study was conducted among Physicians all over Nepal directly or indirectly involved in COVID-19 management. Data was collected via google forms via email or viber/ whattsapp and laid in excel file. Proportion of response from each linked question in two sets containing 11 questions, was compared under the domain “Insight” versus “Current Evidenced based knowledge” having 5 various subtopics. One hundred doctors participated in the study. Overall positive difference of 19% was noted between insight and evidence based knowledge. The highest positive difference was noted regarding atrial fibrillation in COVID-19 (38%), rise in NT pro BNP and its prognosis in heart failure (35%), role of ACE-2 receptor in COVID-19 and acute lung injury (30%) and prevalence and type of arrhythmia in COVID-19 (25%) and lowest (-1%) in regard to preferred reperfusion therapy in STEMI in COVID-19. There were substantial gaps identified between insight and current evidence based knowledge which can be bridged by training, webinar, review article dissemination, peer clinical discussion at government and non-government level in all the states throughout the nation.

The prediction of cardiac abnormality and enhancement in minority class accuracy from imbalanced ECG signals using modified deep neural network models

Cardiovascular disease (CVD) is the most fatal disease in the world, so its accurate and automated detection in the early stages will certainly support the medical expert in timely diagnosis and treatment, which can save many lives. Many types of research have been carried out in this regard, but due to the problem of data imbalance in the medical and health care sector, it may not provide the desired results in all aspects. To overcome this problem, a sequential ensemble technique has been proposed that detects 6 types of cardiac arrhythmias on large ECG imbalanced datasets, and the data imbalanced issue of the ECG dataset has been addressed by using a hybrid data resampling technique called “Synthetically Minority Oversampling Technique and Tomek Link (SMOTE + Tomek)". The sequential ensemble technique employs two distinct deep learning models: Convolutional Neural Network (CNN) and a hybrid model, CNN with Long Short-Term Memory Network (CNN-LSTM). The two standard datasets “MIT-BIH arrhythmias database” (MITDB) and “PTB diagnostic database” (PTBDB) are combined and extracted 23, 998 ECG beats for the model validation. In this work, the three models CNN, CNN-LSTM, and ensemble approach were tested on four kinds of ECG datasets: the original data (imbalanced), the data sampled using a random oversampled technique, data sampled using SMOTE, and the dataset resampled using SMOTE + Tomek algorithm. The overall highest accuracy was obtained of 99.02% on the SMOTE + Tomek sampled dataset by ensemble technique and the minority class accuracy result (Recall) is improved by 20% as compared to the imbalanced data.

Arrhythmia classification algorithm based on multi-head self-attention mechanism

Cardiovascular disease is a major illness that causes human death, especially in the elderly. Timely and accurate diagnosis of arrhythmia types is the key to early prevention and diagnosis of cardiovascular diseases. This paper proposed an arrhythmia classification algorithm based on multi-head self-attention mechanism (ACA-MA). First, an ECG signal preprocessing algorithm based on wavelet transform is put forward and implemented using db6 wavelet transform to focus on improving the data quality of ECG signals and reduce the noise of ECG signals. Second, a linear projection layer for acquiring semantic features of ECG signals is designed using the matching relationship between ECG tag and segmented ECG signals. Third, a position encoding-based spatiotemporal characterization method of ECG signal sequences is designed to integrate time series information into a matrix operation. Fourth, a multi-head self-attentive mechanism capable of capturing global contextual information is proposed to extract relationships and semantic features between ECG segments and achieve semantic association and information stitching of nonadjacent ECG signals. Finally, experimental results on the arrhythmia dataset MIT/BIH show that ACA-MA outperforms other state-of-the-art methods with an overall classification accuracy of 99.4%, a specific rate of 99.41%, and a sensitivity of 97.36%.

Disturbed Cardiac Metabolism Triggers Atrial Arrhythmogenesis in Diabetes Mellitus: Energy Substrate Alternate as a Potential Therapeutic Intervention.

Atrial fibrillation (AF) is the most common type of sustained arrhythmia in diabetes mellitus (DM). Its morbidity and mortality rates are high, and its prevalence will increase as the population ages. Despite expanding knowledge on the pathophysiological mechanisms of AF, current pharmacological interventions remain unsatisfactory; therefore, novel findings on the underlying mechanism are required. A growing body of evidence suggests that an altered energy metabolism is closely related to atrial arrhythmogenesis, and this finding engenders novel insights into the pathogenesis of the pathophysiology of AF. In this review, we provide comprehensive information on the mechanistic insights into the cardiac energy metabolic changes, altered substrate oxidation rates, and mitochondrial dysfunctions involved in atrial arrhythmogenesis, and suggest a promising advanced new therapeutic approach to treat patients with AF.

Artificial intelligence software standardizes electrogram-based ablation outcome for persistent atrial fibrillation.

Multiple groups have reported on the usefulness of ablating in atrial regions exhibiting abnormal electrograms during atrial fibrillation (AF). Still, previous studies have suggested that ablation outcomes are highly operator- and center-dependent. This study sought to evaluate a novel machine learning software algorithm namedVX1 (Volta Medical), trained to adjudicate multipolar electrogram dispersion. This study was a prospective, multicentric, nonrandomized study conducted to assess the feasibility of generating VX1 dispersion maps. In 85 patients, 8 centers, and 17 operators, we compared the acute and long-term outcomes after ablation in regions exhibiting dispersion between primary and satellite centers. We also compared outcomes to a control group in which dispersion-guided ablation was performed visually by trained operators. The study population included 29% of long-standing persistent AF. AF termination occurred in 92% and 83% of the patients in primary and satellite centers, respectively, p = 0.31. The average rate of freedom from documented AF, with or without antiarrhythmic drugs (AADs), was 86% after a single procedure, and 89% after an average of 1.3 procedures per patient (p = 0.4). The rate of freedom from any documented atrial arrhythmia, with or without AADs, was 54% and 73% after a single or an average of 1.3 procedures per patient, respectively (p < 0.001). No statistically significant differences between outcomes of the primary versus satellite centers were observed for one (p = 0.8) or multiple procedures (p = 0.4), or between outcomes of the entire study population versus the control group (p > 0.2). Interestingly, intraprocedural AF termination and type of recurrent arrhythmia (i.e., AF vs. AT) appear to be predictors of the subsequent clinical course. VX1, an expertise-based artificial intelligence software solution, allowed for robust center-to-center standardization of acute and long-term ablation outcomes after electrogram-based ablation.

Angiographic Characteristics of the Vein of Marshall in Patients with and without Atrial Fibrillation.

Background: Ethanol infusion into the vein of Marshall (Et-VOM) is a novel therapeutic treatment for atrial fibrillation (AF). However, few studies have focused on the difference between AF and non-AF patients (presented other types of arrhythmias) regarding the characteristics of the vein of Marshall (VOM). Objective: This study sought to investigate the incidence, morphology, and angiographic characteristics of the VOM. Methods: Coronary sinus (CS) angiography was performed in all patients. The baseline, angiographic characteristics and measurements of VOM dimensions were compared between the AF and non-AF group. Results: CS angiography was performed in 290 patients. The VOM detection rate was higher in the AF group than in the non-AF group (91.8% vs. 84.1%, p = 0.044). In the right anterior oblique (RAO) projection, AF patients had significant larger VOM ostium, CS ostium, and CS diameter at VOM ostium than non-AF patients (1.9 ± 0.9 vs. 1.7 ± 0.7 mm, p = 0.015; 12.8 ± 4.1 vs. 11.4 ± 3.7 mm, p = 0.016; 9.1 ± 3.1 vs. 8.2 ± 2.9 mm, p = 0.028, respectively). There was a slight linear correlation between the VOM ostium and the CS ostium diameter as well as left atrial volume (LAV). Conclusion: AF patients seem to have a higher incidence of the VOM, larger VOM ostium, CS ostium, and CS lumen in RAO view. Meanwhile, the VOM ostium may correlate with the CS ostium and LAV.

Arterial hypertension and atrial fi brillation: general pathogenesis and mutual eff ects on the course of diseases

The article presents reviews of modern domestic and foreign scientific publications on the pathogenesis of atrial fibrillation (AF) in patients with arterial hypertension (AH), as well as the issues of blood pressure control in AF. Arterial hypertension (AH) is often accompanied by comorbidity, and, in addition, is the most frequent factor in the development of atrial fibrillation (AF). AF is the most common type of arrhythmia, which increases the risk of thromboembolic complications, heart failure, and leads to an increase in the overall mortality rate. The aim of the work was to study the pathological mechanisms of the formation of AF in hypertension, as well as their mutual impact on the course of diseases, and, in addition, to analyze and compare methods for measuring blood pressure (BP) in AF, used in modern clinical work, to identify the most objective method. A general scientific method was applied: analysis of modern scientifi c domestic and foreign literature on research problems, generalization, comparison, systematization of theoretical data on the experience of application. All reviews were indexed in PubMed, Medline, eLibrary, CyberLeninka, Google Scholar databases. The presented study allow us to conclude that hypertension is both a risk factor for atrial fi brillation and a complication of the course of the disease in patients with atrial fibrillation; the most objective method of measuring blood pressure in AF is oscillometric. The tasks and prospects of future research are identified.