Type Of Arrhythmia Research Articles

PO-04-123 TACHYARRHYTHMIA OUTCOMES IN CONGENITALLY CORRECTED TRANSPOSITION OF THE GREAT ARTERIES: DOES TREATMENT PATHWAY MATTER?

Patients with congenitally corrected transposition of the greater arteries (cc-TGA) are at risk for developing both atrial and ventricular tachyarrhythmia. However, data on the impact of treatment pathway (non-surgical management, anatomic repair, or physiologic repair) is limited. To describe arrhythmia types and freedom from early (≤30 days post-op) and late (>30 days post-op) sustained tachyarrhythmia requiring intervention (medication, cardioversion, or ablation) in patients with cc-TGA based on treatment pathway. We conducted a retrospective cohort study including all patients with cc-TGA who were followed at our institution between January 1995 and December 2021. Patients were stratified according to treatment pathway as follows: non-surgical, anatomic repair, and physiologic repair. Tachyarrhythmia types analyzed included sustained atrial fibrillation (AF), atrial flutter (AFL), atrial tachycardia and ventricular tachycardia. A total of 170 patients were included in the study, of whom 82 underwent anatomic repair (median age 1.5 yrs, median follow-up 11.5 yrs), 46 physiologic repair (median age 25.2 yrs, median follow-up 12.6 yrs), and 42 non-surgical (median age 35.7 yrs, median follow-up 11 yrs). Overall 50 patients (29%) had tachyarrhythmia: 12/82 (15%) anatomic repair, 15/46 (33%) physiologic repair, and 23/42 (55%) non-surgical. Prevalence of AFL was highest after anatomic repair compared to physiologic repair or non-surgical (32% vs. 22% vs 0%, p=0.024). Prevalence of AF was higher in physiologic repair and non-surgical compared to anatomic repair (52% vs. 65% vs. 0%, p<0.0001). Patients with physiologic repair had more late tachyarrhythmia versus anatomic repair (83% vs. 33%, p=0.002). Freedom from tachyarrhythmia was lowest in anatomic repair vs. physiologic repair and non-surgical (p=0.013), Figure 1A. Estimated freedom from tachyarrhythmia at 20 years in the anatomic, physiologic, and non-surgical groups were 80%, 88%, and 95%, respectively. Freedom from postsurgical tachyarrhythmia trended towards increase prevalence after physiologic repair compared to anatomic repair (p=0.065), Figure 1B. Arrhythmia type differed based on treatment pathway, with AFL more prevalent after anatomic repair and AF more prevalent in physiologic repair and non-surgical management. Freedom from tachyarrhythmia was lowest in the anatomic repair group. Continued follow-up after anatomic repair is needed to determine their long-term risk beyond the 2nd decade.

Atrial cardiomyocytes orchestrate the development of profibrotic inflammatory profile associated with atrial fibrillation vulnerability

Atrial fibrillation (AF) is the most common type of arrhythmia encountered clinically. AF risk factors include hypertension, respiratory diseases, obesity, or heart failure. Right heart disease (RHD) has also been described among AF risk factors associated with an atrial inflammatory profile leading to AF. Studies focusing on the cardiomyocytes (CM) orchestration of the tri-factorial relation between RHD, inflammation, and AF are rare. This project aims to characterize the proarrhythmogenic remodeling affecting atrial cardiomyocyte in a rat model of RHD induced by permanent pulmonary trunk constriction. Characterize RHD induced electrophysiological and morphological CM remodeling leading to atrial inflammation and fibrosis, responsible for increased AF susceptibility. Pulmonary artery banding (PAB) was performed on Wistar rats weighing 225–275 g to induce right-sided cardiac hypertrophy and dilation. Sham animals did not receive the PAB surgery. Cardiac echography and electrophysiological studies were performed in vivo on all animals before sacrifice, 21 days post-surgery. Optical mapping was performed ex-vivo on Langendorff-perfused hearts. Freshly isolated right ventricular (RV), as well as right and left atrial (RA and LA) CM, underwent contractility recording in vitro. Histological analyses were performed to assess myocardial fibrosis and Connexin-43 levels. Genes and protein levels were obtained by qPCR and Western-blot analyses respectively. PAB animals developed severe ventricular and atrial myocardial hypertrophy and dilation compared to Sham, as assessed by echocardiography. PAB animals were significantly more susceptible to AF compared to Sham. Freshly isolated CM revealed that overall CM size was increased in PAB animals, and contractile activity of CM was increased compared to the Sham rats. Analyses of targeted protein and gene expression levels by immunohistochemistry and qPCR analyses showed enhanced expression of fibrosis and inflammation-related compounds in whole-RA and RA CM from PAB, compared to Sham. RHD induces electro-physiological remodeling influencing the RA CM contractile machinery which in turn, leads to the development of pro-arrhythmogenic substrate including atrial inflammation, fibrosis, and enhanced AF inducibility.

PO-03-221 BURDEN OF ARRHYTHMIAS AND CLINICAL OUTCOMES IN PATIENTS WITH DILATED CARDIOMYOPATHY ACCORDING TO LARGE DATASET

Dilated cardiomyopathy (DCM) is characterized by dilation & impaired systolic function of one or both ventricles. Although heart rhythm disorders are associated with DCM, description of their prevalence & clinical outcomes is limited in the literature. Aim of this study was to investigate the burden, basic characteristics, & clinical outcomes of arrhythmias in DCM. We queried the National Inpatient Sample between 2017-2020 for adult patients who were hospitalized with DCM. The primary outcome was inpatient mortality. The secondary outcomes were cardiogenic shock, cardiac arrest, invasive mechanical ventilation, length of stay (LOS) & total hospital cost. Multivariable logistic, linear & Poisson regression analyses were used to estimate clinical outcomes. p-value < 0.05 was significant. There were 875,625 hospitalizations with DCM, of which 402,947 (46.1%) had arrhythmia of any type. Mean age was 64.2 yrs, 57.7% were Caucasian, 66.2% were male. The most prevalent arrhythmia was ventricular tachycardia (VT) 105,810 (12.08%), followed by paroxysmal atrial fibrillation (AFib) 104,330 (11.9%), permanent AFib 77824 (8.8%), persistent AFib 30,810 (3.5%), different degree of atrioventricular block (AVB) 26,644 (3.04%) with complete AVB being the most frequent (1.5%), & sick sinus syndrome 20220 (2.3%). Subgroup with arrhythmia vs without arrhythmia had HTN 6.3% vs 8.2%; PH 19.8% vs 15.5%; HF 89.0% vs 85.9%; HLD 53.3% vs 47.2%; CKD 45.5% vs 39.7%; COPD 28.3% vs 26.9%, respectively. During hospitalization, these subgroups had following complication rates: ACS 12.5% vs 14.1%; AKI 37.6% vs 31.8%; stroke 2.8% vs 3.1%, respectively. Subgroup with arrhythmia was associated with higher ICD (6.1% vs 2.0%), PPM (2.4% vs 0.2%), and LVAD (1.4% vs 0.6%) insertion rate. Subgroup with VT showed worse primary and secondary outcomes, while populations with AFib and AVB showed significant secondary outcomes (Table 1). Significant proportion of DCM patients is affected by arrhythmia (46%), where VT, AFib, AVB, & sick sinus syndrome being the most prevalent. Subgroup with arrhythmia is associated with HF, PH, HLD, CKD, COPD & with increased insertion rates of PPM, ICD, LVAD devices. Moreover, DCM population with different types of arrhythmias showed worse clinical outcomes & had higher resource utilization. This signifies the importance of early detection & treatment of rhythm disorders in DCM population. More research aimed at pathogenesis & long-term outcomes is needed.

Frequency and Clinical Profile of Cardiac Arrhythmias and its Immediate Outcome in Children at Tertiary Care Hospital

Objective: To determine the frequency and clinical profile of arrhythmia and its immediate outcome in children presenting to a tertiary care center. Study Design: A cross-sectional study. Duration and place of study: July 2021 to June 2022, the National Institute of Cardiovascular Diseases, Karachi. Methodology: A total of 100 children of both gender , ranging in age from 1 day to 18 years, who presented with the symptoms of syncope, decreased or increased heart rate, chest discomfort, breathlessness were included in this study. Children who presented with cardiac arrhythmias had varying proportions of several criteria of relevance, such as clinical characteristics, age and gender distribution. In patients with unexplained arrhythmias or syncope, a thorough history, general physical exam, and cardiac examinations—including 12-lead electrocardiograms, 2-D echocardiograms, and Holter studies—were conducted. Results: A total of 100 children were included in this study among them 70 children presented with tachyarrhythmia and 30 children presented with bradycardia. The average age was 8.13± 4.45 years. Among the tachyarrythmias group the most frequent initial symptoms recorded in 45 (64.28%) and 15 (21.42%) youngsters, respectively, were palpitation and chest pain. A total of 19 (27.14%) children were discovered to have acyanotic CHDs. SVT was found to be the most common type of arrhythmia in 25 (30.1%) children, followed by ventricular tachycardia and atrial fibrillation in 15 (21.42%) and 10 (14.28%) of the same age groups. A total of 3 (4.28%) of the hospitalized children died. Among the bradycardia group 80% of children were found with complete heart block, 53.3% syncope, 26.7% were asymptomatic, and 20% were with multiple findings of irritability, poor feeding, breathlessness, and syncope. 20% of them developed LV dysfunction. Conclusion: The most frequent presenting symptoms were palpitations and chest discomfort. The other most common types of arrhythmia were supraventricular tachycardia, atrial fibrillation, ventricular tachycardia and bradycardia. Children's hospital stays were generally short and the therapy for arrhythmias had favorable overall results, however, 4.28% of children in the tachyarrhythmia’s group died of heart failure, while there was no expiry in the bradycardia group. Keywords: Arrhythmias, palpitations, supraventricular and ventricular tachycardia, bradycardia and heart Block

PERBANDINGAN EFEKTIVITAS RIVAROXABAN DAN WARFARIN DALAM MENGATASI KEJADIAN EMBOLI PADA PASIEN DENGAN ATRIAL FIBRILASI

Atrial Fibrillation (AF) is one of the most common types of cardiac arrhythmias caused by abnormal electrical activity in the heart's atria. A study conducted in Indonesia on the urban population in Jakarta obtained an AF incidence rate of 0.2% with a male to female ratio of 3:2. Oral anticoagulant therapy is the standard therapy for AF to prevent stroke and systemic embolism. The most widely used oral anticoagulants are Vitamin K Antagonist (VKA) such as Warfarin and Direct Oral Anticoagulants such as Rivaroxaban. This literature author conducted to compare the effectiveness. Warfarin and Rivaroxaban in dealing with embolic events in AF patients to find out which type of anticoagulant should be used. The literature sources used were Pubmed, Google Scholar, Medline, Ebsco, Hindawi, Science Direct and Cochrane. Anticoagulants have been used to prevent embolic disease in AF patients and the drug classes used are DOAC and VKA. Based on a literature search it was found that Rivaroxaban can reduce the risk of stroke and systemic embolism as well as major bleeding events compared to Warfarin. Rivaroxaban has been shown to have superior effectiveness compared to warfarin and can be used as an alternative drug in treating embolic events in AF patients.

A "two-step classification" machine learning method for non-invasive localization of premature ventricular contraction origins based on 12-lead ECG.

Premature ventricular contraction (PVC) is a type of cardiac arrhythmia that originates from ectopic pacemaker in the ventricles. The localization of the origin of PVC is essential for successful catheter ablation. However, most studies on non-invasive PVC localization focus on elaborate localization in specific regions of the ventricle. This study aims to propose a machine learning algorithm based on 12-lead electrocardiogram (ECG) data that can improve the accuracy of PVC localization in the whole ventricle. We collected 12-lead ECG data from 249 patients with spontaneous or pacing-induced PVCs. The ventricle was divided into 11 segments. In this paper, we propose a machine learning method consisting of two consecutive classification steps. In the first classification step, each PVC beat was labeled to one of the 11 ventricular segments using six features, including a newly proposed morphological feature called "Peak_index." Four machine learning methods were tested for comparative multi-classification performance and the best classifier result was kept to the next step. In the second classification step, a binary classifier was trained using a smaller combination of features to further differentiate segments that are easily confused. The Peak_index as a proposed new classification feature combined with other features is suitable for whole ventricle classification by machine learning methods. The test accuracy of the first classification reached 75.87%. It is shown that a second classification for confusable categories can improve the classification results. After the second classification, the test accuracy reached 76.84%, and when a sample classified into adjacent segments was considered correct, the test "rank accuracy" was improved to 93.49%. The binary classification corrected 10% of the confused samples. This paper proposes a "two-step classification" method to localize the origin of PVC beats into the 11 regions of the ventricle using non-invasive 12-lead ECG. It is expected to be a promising technique to be used in clinical settings to help guide ablation procedures.

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

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

Genome and atrial fibrillation.

Atrial fibrillation (AF), the most common type of arrhythmia, can cause several adverse effects, such as stroke, heart failure, and cognitive dysfunction, also in addition to reducing quality of life and increasing mortality. Evidence suggests that AF is caused by a combination of genetic and clinical predispositions. In line with this, genetic studies on AF have progressed significantly through linkage studies, genome-wide association studies, use of polygenic risk scores, and studies on rare coding variations, gradually elucidating the relationship between genes and the pathogenesis and prognosis of AF. This article will review current trends in genetic analysis concerning AF.

Correlation of Cardiopulmonary Bypasses and Cardiac Troponin I in Predicting Post-Op Arrhythmia

Aim: The correlation of cardiopulmonary bypasses (CPB) and cardiac troponin I (cTnI) in predicting arrhythmia remain unclear. Aim of this study to investigate the correlation of cardiopulmonary bypasses duration and cardiac troponin I with the type of arrhythmias. Methods: This is a retrospective observational study took place in our hospital between May 2020-December 2021.The study included a total of thirty-three patients who underwent open-heart surgery. Patients between the age of 2 months and 14 years of both genders with the diagnosis of ventricular septal defect (VSD), atrioventricular defect (AVSD) and tetralogy of Fallot (TOF) were included in this study. Patients with preoperative a history of major intraoperative events and high-level of cardiac troponin I were excluded from the study. The accuracy was calculated using sensitivity and specificity. The area under the ROC curve (95% CI) and p-value were also calculated. Results: Out of thirty-three patients undergoing open-heart surgery, 58.1% were male and were one year of age or more (71%). A statistically significant correlation among arrhythmia, cardiac troponin I and cardiopulmonary bypasses was observed (p &lt; 0.05). Cardiac troponin I predicted high-level sensitivity for arrhythmias, hospital stay, and intensive care unit stay, while low specificity was reported for cardiac troponin I compared to cardiopulmonary bypasses. Conclusion: The higher level of cardiac troponin I was correlated with the underlying burden of arrhythmias. A novel high- sensitivity cardiac troponin I assay can protectively recognize patients at low risk of arrhythmias. Keywords: Arrhythmia, Cardiac troponin I, Cardiopulmonary bypass, Sensitivity, Specificity

Arrhythmias in Williams Syndrome

Williams syndrome (WS) is a congenital, multisystem disorder in which 80% of patients have cardiovascular abnormalities. Sudden cardiac death occurs 25 to 100 times more often in WS than in the general population, and cardiac repolarization is abnormal in WS. We sought to determine the prevalence of primary arrhythmias in patients with WS and whether QTc prolongation impacts arrhythmia risk. We retrospectively reviewed all patients with WS with ambulatory electrocardiogram (ECG) monitoring at our institution between October 2017 and January 2022. The primary outcome was the presence of arrhythmia. Predictors pre-determined for analysis included premature ventricular and atrial complex burden (%), degree of QTc change with varying heart rates, intervals and rhythm on 12-lead ECG, age, gender, symptomatology, and clinical and surgical history. A total of 74 patients (55% female, median age 8years (3, 13) underwent 108 ambulatory monitors. Arrhythmias were present in 9 patients (12%). Within this group of 9 patients, 18/24 serial monitors were abnormal, and 3/9 patients (33%) had >1 arrhythmia type. Older age (p=0.002) and symptoms (syncope, p=0.005) were associated with arrhythmias. Arrhythmia was not associated with the degree of structural heart disease. Atrial tachycardia was the most identified arrhythmia (n=6; 67% of patients with arrhythmias and 8% of the total cohort). The QTc abnormally increased with higher heart rates in all groups. There was a higher number of premature ventricular and atrial complexes per hour in patients with arrhythmias. In conclusion, atrial arrhythmias were the most common arrhythmia in patients with WS and routine ambulatory ECG and intermittent rhythm monitoring are indicated in WS, particularly given the high risk of sudden cardiac death in WS.

Label correlation embedding guided network for multi-label ECG arrhythmia diagnosis

In clinical practice, one patient may suffer from more than one arrhythmia simultaneously, that is, one ECG record may be associated with multiple types of arrhythmias. In fact, there are inherent dependencies between arrhythmias. However, previous studies have mainly focused on multi-class (single-label) ECG classification, which addresses each type of arrhythmia independently and ignores the multi-label correlation between different ECG abnormalities. To address the lack of ECG multi-label classification methods, we proposed a label correlation embedding guided network (LCEGNet) model to effectively recognize multi-label ECG arrhythmias and explore the correlation between ECG abnormalities. First, label correlation embedding was obtained based on the correlation matrix between different arrhythmias to guide feature extraction. Subsequently, the category-specific attention coefficient was obtained by calculating the cosine similarity coefficient between the label embedding and feature spaces. Experiments on public and self-collected ECG datasets were conducted. The LCEGNet achieved F1 scores of 0.777 and 0.872 and subset accuracy of 0.750 and 0.828 on the two datasets, respectively. A classification speed of 7.796ms was achieved. The experimental results demonstrate that the proposed LCEGNet achieved approximately a 11% and 9.1% improvement in the F1 score and subset accuracy, respectively, compared with traditional ResNet architecture and a 4.3% and 5.54% improvement in the F1 score and subset accuracy, respectively, compared with the state-of-the-art approaches.

Association between circulating leukocytes and arrhythmias: Mendelian randomization analysis in immuno-cardiac electrophysiology.

Cardiac arrhythmia is a common disease associated with high mortality and morbidity. Circulating leukocyte counts, which serve as a biomarker for assessing systemic immune status, have been linked to arrhythmias in observational studies. However, observational studies are plagued by confounding factors and reverse causality, whether alterations in circulating leukocyte components are causally associated with arrhythmias remains uncertain. The present study explored this question based on genetic evidence. We performed Mendelian randomization (MR) analysis to evaluate whether alterations in leukocyte counts affect aggregated risk of all types of arrhythmia or risk of five specific types of arrhythmia. Single-nucleotide polymorphisms serving as proxies for leukocyte differential counts were retrieved from the Blood Cell Consortium, and statistical data on arrhythmias were obtained from the UK Biobank), FinnGenand a meta-analysis of genome-wide association studies for atrial fibrillation. We applied inverse variance-weighted method as the primary analysis, complemented by a series of sensitivity analyses. Bidirectional analyses were conducted to assess reverse causality. Finally, multivariable MR was performed to study the joint effects of multiple risk factors. We found that genetically predicted differential leukocyte counts were not significantly associated with aggregated occurrence of all types of arrhythmia. In contrast, each 1-standard deviation increase in lymphocyte count was associated with 46% higher risk of atrioventricular block (OR 1.46, 95% CI 1.11-1.93, p=0.0065). A similar effect size was observed across all MR sensitivity analyses, with no evidence of horizontal pleiotropy. Reverse MR analysis suggested that atrioventricular block was unlikely to cause changes in lymphocyte count. Primary MR analysis based on the inverse-variance weighted method suggested that changes in neutrophil count alter risk of right bundle branch block, and changes in basophil count alter risk of atrial fibrillation. However, these causal relationships were not robust in sensitivity analyses. We found no compelling evidence that neutrophil or lymphocyte counts cause atrial fibrillation. Our data support higher lymphocyte count as a causal risk factor for atrioventricular block. These results highlight the importance of immune cells in the pathogenesis of specific cardiac conduction disorders.

Behavior of Retrograde Conduction Time at Supraventricular Tachycardia Induction and its Role in Differential Diagnosis

Background: Differential diagnosis between orthodromic reentrant tachycardia (ORT) and atypical nodal reentrant tachycardia (ANRT) can be challenging. Our hypothesis was that ANRT presents more variability in retrograde conduction time at tachycardia onset than ORT. Objectives: The objectives of this study were to assess retrograde conduction time variability at the start of tachycardia in ANRT and ORT, and postulate a new diagnostic tool to differentiate these two types of arrhythmias. Methods: The ventriculoatrial (VA) interval of the first beats after tachycardia induction was measured until stabilization. The difference between the maximum and minimum VA interval was defined as delta VA (ΔVA), and the number of beats needed for VA interval stabilization was also assessed. Atrial tachycardias were excluded. Results: In a total of 101 patients included in the study, ORT was diagnosed in 64 patients and ANRT in 37. ΔVA interval was 0 (interquartile range [IQR] 0-5) milliseconds (ms) in ORT vs. 40 (21-55) ms in ANRT (p &lt;0.001). The VA interval significantly stabilized earlier in ORT (1.5 [1-3] beats) than in ANRT (5 [4-7] beats) (p&lt;0.001). A ΔVA &lt;10 ms diagnosed ORT with 100% sensitivity, specificity, and positive and negative predictive values. Ventriculoatrial interval stabilization in less than 3 beats predicted ORT with good diagnostic accuracy. The results were similar considering only accessory septal pathways. Typical NRTs presented an intermediate variation. Conclusion: Presence of ΔVA &lt;10 ms is a simple criterion that accurately differentiates ORT from ANRT, independently of the accessory pathway localization.

42. Atrial Fibrillation and Hypertension in Prolanis Community in Bandung City: A Quantitative-Descriptive Study

Background: Atrial fibrillation (AF) is the most common type of cardiac arrhythmia which often is asymptomatic and undiagnosed. One of the risk factors for atrial fibrillation include high blood pressure. Hypertension itself, based on International Society of Hypertension 2020 is defined when systolic blood pressure $140mmHg and/or diastolic blood pressure $90mmHg. In Indonesia, we have PROLANIS (Program Pengelolaan Penyakit Kronis), a program which is held by Ministry of Health in Indonesia to manage chronic disease such as hypertension. Objective: This descriptive study is aimed to identify the prevalence of atrial fibrillation in hypertensive patient among PROLANIS community in Bandung City. Method: We performed prospective screening using a six-leads FDA approved ECG mobile in twenty-one primary care among PROLANIS community during March-October 2022. Result: We collected 692 data from PROLANIS community in twenty-one primary care in Bandung City. AF in normotensive patient was 2.7% (n = 10), AF in stage 1 hypertension was 4.37% (n = 10) and AF in stage 2 hypertension was 4.5% (n = 4). Conclusion: Hypertension and AF often coexist. Patient with hypertension have 1.7-fold higher risk of developing AF than normotensive individual. Hypertension may induce early and progressive changes in left atrium anatomy and function, which may promote AF through a variety of electrophysiological mechanism. We found studies which conducted by the same method (using mobile electrocardiogram), AF was found 8.1% in hypertensive patient. The diagnosis of atrial fibrillation from the tools warrants further cardiological evaluation but it could be helpful in patients at cardiovascular risk for better prevention.

Novel Deep Convolutional Neural Network based Classification of Arrhythmia

&#x0D; Holter monitors are used to record Electrocardiogram (ECG) data which is extremely hard to analyze manually. Convolutional Neural Network (CNN) are known to be efficient for classification of image data. Hence, in this study, we are using Deep Convolutional Neural Network to classify the ECG data into various types of Arrhythmias. Denoising, segmentation and data augmentation techniques are used for pre-processing of the data. The proposed model uses the MIT-BIH Arrhythmia Dataset for training and evaluation purpose this dataset has much imbalance which has been removed using data augmentation techniques. The proposed approach shows an overall accuracy 99.67% along with 99.68% precision and 99.66% recall. Further, we have also compared the state-of-the-art models like 2D CNN, genetic ensemble of classifiers, Long Short-Term Memory (LSTM) Networks, etc results with proposed model. And the introduced approach is outperforming when compared to these models.&#x0D;

НАРУШЕНИЯ СЕРДЕЧНОГО РИТМА И ПРОВОДИМОСТИ У МУЖЧИН МОЛОЖЕ 50 ЛЕТ С КАРДИОГЕННЫМ ШОКОМ ПРИ ИНФАРКТЕ МИОКАРДА

Relevance. Cardiogenic shock remains one of the most common causes of death in myocardial infarction. Aim. To evaluate the features of cardiac rhythm and conduction disturbances in myocardial infarction complicated by cardiogenic shock, as well as their significance for the development of this complication in males under 50 years old to improve prevention and outcomes. Material and methods. The study included males aged 19-49 years old with type I myocardial infarction. The patients were divided into age- comparable groups. The study group consisted of seven patients with cardiogenic shock, the control group - without cardiogenic shock - 223 patients. A comparative analysis of arrhythmias among the variants of the clinical course, complications, as well as their structure in selected groups were performed. The influence of the studied parameters on the risk of cardiogenic shock development in the examined patients was assessed by the method of risk analysis using the Pearson Chi-square test. Results. In the study group, a higher incidence of arrhythmias in the structure of MI complications (85.7%) was revealed than in the control group (24.2%; p=0.003). They were observed in combination with complications of the group of contractile myocardial insufficiency and its mechanical failure (57.1% and 6.3%, respectively; р˂0.0001) and only contractile insufficiency (28.6% and 11.2%; р˂0,0001). In the structure of arrhythmias in the study group, the frequency of observation of atrial fibrillation and flutter (66.7%) prevailed over the control group (4.9%; р˂0.0001), ventricular fibrillation (50.0 and 2.4%, respectively; р˂ 0.0001), supraventricular tachycardias (33.3% and 1.5%; р˂0.0001), supraventricular (33.3% and 8.3%; р=0.03) and polytopic extrasystoles (33.3% and 3 .9%; p=0.0003), ventricular tachycardias (16.7% and 2.0%; p=0.02), complete atrioventricular blockades (16.7% and 2.0%; p=0.02) and asystole (16.7% and 1.5%; p=0.007). The risk of cardiogenic shock development increased with these arrhythmias. Conclusions. The listed types of arrhythmias should be used in the formation of high-risk groups for the cardiogenic shock development in myocardial infarction for monitoring and timely implementation of the necessary treatment. It is also expedient to take them in the prognostic modeling of this complication.

The incidence of spontaneous arrhythmias in telemetered beagle dogs, Göttingen Minipigs and Cynomolgus non-human primates: A HESI consortium retrospective analysis

IntroductionCharacterization of the incidence of spontaneous arrhythmias to identify possible drug-related effects is often an important part of the analysis in safety pharmacology studies using telemetry. MethodsA retrospective analysis in non-clinical species with and without telemetry transmitters was conducted. Electrocardiograms (24 h) from male and female beagle dogs (n = 131), Göttingen minipigs (n = 108) and cynomolgus non-human primates (NHP; n = 78) were analyzed. ResultsVentricular tachycardia (VT) was observed in 3% of the dogs but was absent in minipigs and NHPs. Ventricular fibrillation (VF) was not observed in the 3 species. Ventricular premature beats (VPBs) were more frequent during daytime and atrioventricular blocks (AVBs) were more frequent at night in all species. A limited number of animals exhibited a high arrhythmia frequency and there was no correlation between animals with higher frequency of an arrhythmia type and the frequency of other arrythmias in the same animals. Clinical chemistry or hematology parameters were not different with or without telemetry devices. NHP with a transmural left ventricular pressure (LVP) catheter exhibited a greater incidence of VPBs and PJCs compared to telemetry animals without LVP. DiscussionAll species were similar with regards to the frequency of ventricular ectopic beats (26–46%) while the dog seemed to have more frequent junctional complexes and AVB compared to NHP and minipigs. Arrhythmia screening may be considered during pre-study evaluations, to exclude animals with abnormally high arrhythmia incidence.

REAL CLINICAL PRACTICE OF TREATMENT OF CARDIAC ARRHYTHMIAS IN LOCOMOTIVE CREW WORKERS

Cardiac arrhythmias create prerequisites for the occurrence of sudden cardiac death in the workplace, which poses a threat to the safety of train traffic. A targeted examination of locomotive crew workers (LCW) includes the diagnosis of cardiac arrhythmias for effective and safe pharmacotherapy. A retrospective analysis of 100 medical histories of machinists and assistant machinists hospitalized in the cardiology department of the Private healthcare institution "Clinical Hospital "Russian Railways-medicine" Voronezh", who have the following types of cardiac arrhythmias: supraventricular extrasystole (single 94%, paired 20%), single ventricular extrasystole 51%, paroxysmal form of atrial fibrillation 2%, conduction disorder 6%. According to the results of the examination, a group of LCW with prognostically unfavorable cardiac arrhythmias (32%) was identified, who underwent pharmacotherapy, including beta-blockers, antiarrhythmic drugs of class IC and class III. The choice of medications for pharmacotherapy in outpatient settings took into account the impact on professionally important functions according to the established List of "Medicines and traffic safety" (ed. from 2016). At discharge, 25% of patients were recommended nebivolol, which LCW could take in conditions of professional activity. Pharmacotherapy of drivers on an outpatient basis was continued with etacizine (3%), allapinine (2%), amiodarone (1%) with suspension from work for the period of taking the drug.

Pharmacological Potentials of Omega 3 Fatty Acid in Reduction of Atrial Fibrillation

Atrial fibrillation (AF) is the most common type of arrhythmia in the general population with a prevalence that reaches one third of patients with arterial hypertension, diabetic and other risk factors. In atrial fibrillation, the regular impulses produced by the sinus node for a normal heart beat are overwhelmed by rapid electrical discharges produced in the atria and adjacent parts of the pulmonary veins. Omega-3 polyunsaturated fatty acids (PUFAs), namely eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are permanent subjects of interest in relation to the protection of cardiovascular health and the prevention of the incidence of both ventricular and atrial arrhythmias. It has been proposed that Omega-3 polyunsaturated fatty acid possess anti-inflammatory properties that can inhibit arrhythmogenic mechanisms. Potential Targets of Omega-3 PUFAs Relevant to Arrhythmias Prevention are direct inhibition of sarcolemmal ion channels &amp; restoring cardiac connexion channels. Intake of omega-3 fatty acids significantly prevents the occurrence of AF. The purpose of this review is to focus on the novel cellular and molecular effects of omega-3 PUFAs, in the context of the mechanisms and factors involved in the development of atrial fibrillation.&#x0D; Keywords: Eicosapentaenoic acid, Docosahexaenoic acid, Atrial Fibrillation, Polyunsaturated fatty acids, Arrhythmias.

Exploring interpretability in deep learning prediction of successful ablation therapy for atrial fibrillation.

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, deep learning (DL) has increasingly been applied to improve RFCA treatment for AF. However, for a clinician to trust the prediction of a DL model, its decision process needs to be interpretable and have biomedical relevance. Aim: This study explores interpretability in DL prediction of successful RFCA therapy for AF and evaluates if pro-arrhythmogenic regions in the left atrium (LA) were used in its decision process. Methods: AF and its termination by RFCA have been simulated in MRI-derived 2D LA tissue models with segmented fibrotic regions (n = 187). Three ablation strategies were applied for each LA model: pulmonary vein isolation (PVI), fibrosis-based ablation (FIBRO) and a rotor-based ablation (ROTOR). The DL model was trained to predict the success of each RFCA strategy for each LA model. Three feature attribution (FA) map methods were then used to investigate interpretability of the DL model: GradCAM, Occlusions and LIME. Results: The developed DL model had an AUC (area under the receiver operating characteristic curve) of 0.78 ± 0.04 for predicting the success of the PVI strategy, 0.92 ± 0.02 for FIBRO and 0.77 ± 0.02 for ROTOR. GradCAM had the highest percentage of informative regions in the FA maps (62% for FIBRO and 71% for ROTOR) that coincided with the successful RFCA lesions known from the 2D LA simulations, but unseen by the DL model. Moreover, GradCAM had the smallest coincidence of informative regions of the FA maps with non-arrhythmogenic regions (25% for FIBRO and 27% for ROTOR). Conclusion: The most informative regions of the FA maps coincided with pro-arrhythmogenic regions, suggesting that the DL model leveraged structural features of MRI images to identify such regions and make its prediction. In the future, this technique could provide a clinician with a trustworthy decision support tool.