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Background: Manually derived electrocardiographic (ECG) parameters were not associated with mortality in mechanically ventilated COVID‐19 patients in earlier studies, while increased high‐sensitivity cardiac troponin‐T (hs‐cTnT) and N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) were. To provide evidence for vectorcardiography (VCG) measures as potential cardiac monitoring tool, we investigated VCG trajectories during critical illness. Methods: All mechanically ventilated COVID‐19 patients were included in the Maastricht Intensive Care Covid Cohort between March 2020 and October 2021. Serum hs‐cTnT and NT‐proBNP concentrations were measured daily. Conversion of daily 12‐lead ECGs to VCGs by a MATLAB‐based script provided QRS area, T area, maximal QRS amplitude, and QRS duration. Linear mixed‐effect models investigated trajectories in serum and VCG markers over time between non‐survivors and survivors, adjusted for confounders. Results: In 322 patients, 5461 hs‐cTnT, 5435 NT‐proBNP concentrations and 3280 ECGs and VCGs were analyzed. Non‐survivors had higher hs‐cTnT concentrations at intubation and both hs‐cTnT and NT‐proBNP significantly increased compared with survivors. In non‐survivors, the following VCG parameters decreased more when compared to survivors: QRS area (−0.27 (95% CI) (−0.37 to −0.16, p <.01) μVs per day), T area (−0.39 (−0.62 to −0.16, p <.01) μVs per day), and maximal QRS amplitude (−0.01 (−0.01 to −0.01, p <.01) mV per day). QRS duration did not differ. Conclusion: VCG‐derived QRS area and T area decreased in non‐survivors compared with survivors, suggesting that an increase in myocardial damage and tissue loss play a role in the course of critical illness and may drive mortality. These VCG markers may be used to monitor critically ill patients. [ABSTRACT FROM AUTHOR]

Background: The prognosis of Duchenne muscular dystrophy (DMD) is poor once it develops to the stage of cardiac impairment. Recent studies have demonstrated that electrocardiogram (ECG), which consists of general ECG and vectorcardiogram (VCG), retains an extremely powerful role in the assessment of patients with reduced left ventricular (LV) systolic dysfunction. However, data regarding VCG recordings in DMD and its prognostic value for reduced left ventricular ejection fraction (LVEF) of DMD have never been reported. This study aims to describe the characteristics of VCG in children with DMD and to explore the predictive value of VCG for reduced LVEF in children with DMD. Methods: A total of 306 patients with a known diagnosis of DMD confirmed by the genetic test were retrospectively enrolled at our hospital between August 2018 and August 2022. This resulted in a total study group of 486 VCG recordings. Among them, 75 DMD patients who underwent cardiac magnetic resonance (CMR) later after one year follow-up were prospectively enrolled. The trend of VCG parameters of DMD patients across the different age span were compared with age-matched normal children. Concordance statistic analysis was further performed to assess the validity of VCG parameters in predicting the occurrence of reduced LVEF in patients with DMD. Results: DMD patients have a significantly higher heart rate, R waves in V1, QRS loop percentage in the right anterior quadrant in the horizontal plane (horizontal quadrant II) and QRS loop percentage in the anterior superior quadrant in the sagittal plane (sagittal quadrant IV) than normal children. Concordance statistic (C-statistic) showed an area under the curve of quadrant IV in the sagittal plane of baseline was 0.704. The receiver operating characteristic (ROC) curve shows that quadrant IV in the sagittal plane of 7.57% was the optimal cutoff with a sensitivity of 53.3% and a specificity of 88.3% for predicting reduced LVEF in DMD patients. Conclusions: Our study firstly showed that QRS loop percentage in the right anterior quadrant in the horizontal plane (horizontal quadrant II) and QRS loop percentage in the anterior superior quadrant in the sagittal plane (sagittal quadrant IV) could be abnormal in DMD boys as early as before 5 years old. Evaluation of the myocardium by VCG in the early age to predict possible cardiac systolic dysfunction may have important implications for the ongoing management of DMD boys. [ABSTRACT FROM AUTHOR]

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3DQRSarea is a strong marker for cardiac resynchronization therapy and can be obtained by taking the (i) summation or the (ii) difference of the areas subtended by positive and negative deflections in X, Y, Z vectorcardiographic electrocardiogram (ECG) leads. We correlated both methods with the instantaneous‐absolute‐3D‐voltage‐time‐integral (VTIQRS‐3D). 3DQRSarea consistently underestimated the VTIQRS‐3D, but the summation method was a closer and more reliable approximation. The dissimilarity was less apparent in left bundle branch block (r2 summation.996 vs. difference.972) and biventricular paced ECGs (r2.996 vs..957) but was more apparent in normal ECGs (r2.988 vs..653). [ABSTRACT FROM AUTHOR]

Introduction: Measurement of the spatial ventricular gradient (SVG), spatial QRST angles, and other vectorcardiographic measures of myocardial electrical heterogeneity have emerged as novel risk stratification methods for sudden cardiac death and other adverse cardiovascular events. Prior studies of normal limits of these measurements included primarily young, healthy, White volunteers, but normal limits in older patients are unknown. The influence of race and body mass index (BMI) on these measurements is also unclear. Methods: Normal 12‐lead electrocardiograms (ECGs) from a single center were identified. Patients with abnormal cardiovascular, pulmonary, or renal history (assessed by International Classification of Disease [ICD‐9/ICD‐10] codes) or abnormal cardiovascular imaging were excluded. The SVG and QRST angles were measured and stratified by age, sex, and race. Multivariable linear regression was used to assess the influence of age, BMI, and heart rate (HR) on these measurements. Results: Among 3292 patients, observed ranges of SVG and QRST angles (peak and mean) differed significantly based on sex, age, and race. Sex differences attenuated with increasing age. Men tended to have larger SVG magnitude (60.4 [46.1–77.8] vs. 52.5 [41.3–65.8] mv*ms, p <.0001) and elevation, and more anterior/negative SVG azimuth (−14.8 [−25.1 to −4.3] vs. 1.3 [−9.8 to 10.5] deg, p <.0001) compared to women. Men also had wider QRST angles. Observed ranges varied significantly with BMI and HR. SVG and QRST angle measurements were robust to different filtering bandwidths and moderate fiducial point annotation errors, but were heavily affected by changes in baseline correction. Conclusions: Age, sex, race, BMI, and HR significantly affect the range of SVG and QRST angles in patients with normal ECGs and no known cardiovascular disease, and should be accounted for in future studies. An online calculator for prediction of these "normal limits" given demographics is provided at https://bivectors.github.io/gehcalc/. [ABSTRACT FROM AUTHOR]

Providing reliable detection of QRS complexes is key in automated analyses of electrocardiograms (ECG). Accurate and timely R-peak detections provide a basis for ECG-based diagnoses and to synchronize radiologic, electrophysiologic, or other medical devices. Compared with classical algorithms, deep learning (DL) architectures have demonstrated superior accuracy and high generalization capacity. Furthermore, they can be embedded on edge devices for real-time inference. 3D vectorcardiograms (VCG) provide a unifying framework for detecting R-peaks regardless of the acquisition strategy or number of ECG leads. In this article, a DL architecture was demonstrated to provide enhanced precision when trained and applied on 3D VCG, with no pre-processing nor post-processing steps. Experiments were conducted on four different public databases. Using the proposed approach, high F1-scores of 99.80% and 99.64% were achieved in leave-one-out cross-validation and cross-database validation protocols, respectively. False detections, measured by a precision of 99.88% or more, were significantly reduced compared with recent state-of-the-art methods tested on the same databases, without penalty in the number of missed peaks, measured by a recall of 99.39% or more. This approach can provide new applications for devices where precision, or positive predictive value, is essential, for instance cardiac magnetic resonance imaging. [ABSTRACT FROM AUTHOR]

Coronary artery disease (CAD) is among the leading causes of death worldwide. Initial studies require an electrocardiogram stress test often followed by cardiac imaging procedures. However, conventional indices still show insufficient diagnostic performance. We propose quaternion methods to evaluate abnormal alterations during ventricular depolarization and repolarization. Assessment was conducted during a Bruce protocol treadmill stress test and after the end of the exercise. We developed an algorithm to automatically determine the beginning and end of exercise and then, computed the angular and linear velocities. Statistical analysis for feature selection and classification between ischaemic and non-ischaemic patients was used. The most significant markers were maximum linear velocity during ventricular depolarization (p < 5E-9) and maximum angular velocity during the second half of the repolarization loop (p < 5E-16). The latter reached sensitivity / specificity pair of 78 / 92 (AUC 0.89). A linear classifier showed a trend of reduction in cardiac vector velocity in at-risk patients after the end of exercise. The sensitivity / specificity pair reached was 86 / 100. Trajectory deviations of depolarization / repolarization loops that result from ischaemia effects, could be responsible for the observed reduction in dynamic changes during exercise. Further studies could provide non-invasive complementary tools to detect CAD risk. [ABSTRACT FROM AUTHOR]

Summary: The paper aims to develop a universally implementable efficient test for testing homogeneity of mean directions of several independent hyper‐spherical populations. Conventional tests are valid only under highly concentrated and/or large‐size groups. Focusing on the popular Langevin distribution on a d‐hyper‐sphere, the present work extends the very recent results for the circular case. The hurdle of the nuisance non‐location‐scale concentration parameter κ is overcome through a variant of the integrated likelihood ratio test (ILRT), yielding a simple and elegant test statistic. Analytically, second‐order accurate asymptotic chi‐squared distribution of ILRT is established. Extensive simulation study demonstrates that ILRT uniformly outperforms its peers, notably under highly dispersed groups, which is precisely the target parametric region, and is robust under a large class of alternate distributions. Five real‐life data analyses from diverse disciplines, including the emerging field of vectorcardiography and a novel application to compositional data analysis in the context of drug development, illustrate applications of the findings. [ABSTRACT FROM AUTHOR]

Myocardial infarction (MI) occurs due to the decrease in the blood flow into one part of the heart, and it further causes damage to the heart muscle. The 12-channel electrocardiogram (ECG) has been widely used to detect and localize MI pathology in clinical studies. The vectorcardiogram (VCG) is a 3-channel recording system used to measure the heart's electrical activity in sagittal, transverse, and frontal planes. The VCG signals have advantages over the 12-channel ECG to localize posterior MI pathology. Detection and localization of MI using VCG signals are vital in clinical practice. This paper proposes a multi-channel multi-scale two-stage deep-learning-based approach to detect and localize MI using VCG signals. In the first stage, the multivariate variational mode decomposition (MVMD) decomposes the three-channel-based VCG signal beat into five components along each channel. The multi-channel multi-scale VCG tensor is formulated using the modes of each channel of VCG data, and it is used as the input to the deep convolutional neural network (CNN) to classify MI and normal sinus rhythm (NSR) classes. In the second stage, the multi-class deep CNN is used for the categorization of anterior MI (AMI), anterior-lateral MI (ALMI), anterior-septal MI (ASMI), inferior MI (IMI), inferior-lateral MI (ILMI), inferior-posterior-lateral (IPLMI) classes using MI detected multi-channel multi-scale VCG instances from the first stage. The proposed approach is developed using the VCG data obtained from a public database. The results reveal that the approach has obtained the accuracy, sensitivity, and specificity values of 99.58%, 99.18%, and 99.87%, respectively, for MI detection. Moreover, for MI localization, we have obtained the overall accuracy value of 99.86% in the second stage for our proposed network. The proposed approach has demonstrated superior classification performance compared to the existing VCG signal-based MI detection and localization techniques. [ABSTRACT FROM AUTHOR]

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Aims: Ventricular activation patterns can aid clinical decision-making directly by providing spatial information on cardiac electrical activation or indirectly through derived clinical indices. The aim of this work was to derive an atlas of the major modes of variation of ventricular activation from model-predicted 3D bi-ventricular activation time distributions and to relate these modes to corresponding vectorcardiograms (VCGs). We investigated how the resulting dimensionality reduction can improve and accelerate the estimation of activation patterns from surface electrogram measurements.Methods and Results: Atlases of activation time (AT) and VCGs were derived using principal component analysis on a dataset of simulated electrophysiology simulations computed on eight patient-specific bi-ventricular geometries. The atlases provided significant dimensionality reduction, and the modes of variation in the two atlases described similar features. Utility of the atlases was assessed by resolving clinical waveforms against them and the VCG atlas was able to accurately reconstruct the patient VCGs with fewer than 10 modes. A sensitivity analysis between the two atlases was performed by calculating a compact Jacobian. Finally, VCGs generated by varying AT atlas modes were compared with clinical VCGs to estimate patient-specific activation maps, and the resulting errors between the clinical and atlas-based VCGs were less than those from more computationally expensive method.Conclusion: Atlases of activation and VCGs represent a new method of identifying and relating the features of these high-dimensional signals that capture the major sources of variation between patients and may aid in identifying novel clinical indices of arrhythmia risk or therapeutic outcome. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Heart diseases alter the rhythmic behaviors of cardiac electrical activity. Recent advances in sensing technology bring the ease to acquire space-time electrical activity of the heart such as vectorcardiogram (VCG) signals. Recurrence analysis of successive heartbeats is conducive to detect the disease-altered cardiac activities. However, conventional recurrence analysis is more concerned about homogeneous recurrences, and overlook heterogeneous types of recurrence variations in VCG signals (i.e., in terms of state properties and transition dynamics). This paper presents a new framework of heterogeneous recurrence analysis for the characterization and modeling of disease-altered spatiotemporal patterns in multi-channel cardiac signals. Experimental results show that the proposed approach yields an accuracy of 96.9%, a sensitivity of 95.0%, and a specificity of 98.7% for the identification of myocardial infarctions. The proposed method of heterogeneous recurrence analysis shows strong potential to be further extended for the analysis of other physiological signals such as electroencephalogram (EEG) and electromyography (EMG) signals towards medical decision making. [ABSTRACT FROM AUTHOR]

Background: In the prehospital triage of patients presenting with symptoms suggestive of acute myocardial ischemia, reliable myocardial ischemia detection in the electrocardiogram (ECG) is pivotal. Due to large interindividual variability and overlap between ischemic and nonischemic ECG-patterns, incorporation of a previous elective (reference) ECG may improve accuracy. The aim of the current study was to explore the potential value of serial ECG analysis using subtraction electrocardiography.Methods: SUBTRACT is a multicenter retrospective observational study, including patients who were prehospitally evaluated for acute myocardial ischemia. For each patient, an elective previously recorded reference ECG was subtracted from the ambulance ECG. Patients were classified as myocardial ischemia cases or controls, based on the in-hospital diagnosis. The diagnostic performance of subtraction electrocardiography was tested using logistic regression of 28 variables describing the differences between the reference and ambulance ECGs. The Uni-G ECG Analysis Program was used for state-of-the-art single-ECG interpretation of the ambulance ECG.Results: In 1,229 patients, the mean area-under-the-curve of subtraction electrocardiography was 0.80 (95%CI: 0.77-0.82). The performance of our new method was comparable to single-ECG analysis using the Uni-G algorithm: sensitivities were 66% versus 67% (p-value > .05), respectively; specificities were 80% versus 81% (p-value > .05), respectively.Conclusions: In our initial exploration, the diagnostic performance of subtraction electrocardiography for the detection of acute myocardial ischemia proved equal to that of state-of-the-art automated single-ECG analysis by the Uni-G algorithm. Possibly, refinement of both algorithms, or even integration of the two, could surpass current electrocardiographic myocardial ischemia detection. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Medicina Neotloznyh Sostoanij is the property of Zaslavsky O.Yu and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Implantable cardioverter-defibrillators (ICDs) improve survival of systolic heart failure (HF) patients who are at risk of sudden cardiac death (SCD). We recently showed that electrocardiographic (ECG) global electrical heterogeneity (GEH) is independently associated with SCD in the community-dwelling cohort and developed GEH SCD risk score. The Global Electrical Heterogeneity and Clinical Outcomes (GEHCO) study is a retrospective multicenter cohort designed with two goals: (1) validate an independent association of ECG GEH with sustained ventricular tachyarrhythmias and appropriate ICD therapies and (2) validate GEH ECG risk score for prediction of sustained ventricular tachyarrhythmias and appropriate ICD therapies in systolic HF patients with primary prevention ICD.Methods: All records of primary prevention ICD recipients with available data for analysis are eligible for inclusion. Records of ICD implantation in patients with inherited channelopathies and cardiomyopathies are excluded. Raw digital 12-lead pre-implant ECGs will be used to measure GEH (spatial QRST angle, spatial ventricular gradient magnitude, azimuth, and elevation, and sum absolute QRST integral). The primary endpoint is defined as a sustained ventricular tachyarrhythmia event with appropriate ICD therapy. All-cause death without preceding sustained ventricular tachyarrhythmia with appropriate ICD therapy will serve as a primary competing outcome. The study will draw data from the academic medical centers.Results: We describe the study protocol of the first multicenter retrospective cohort of primary prevention ICD patients with recorded at baseline digital 12-lead ECG.Conclusion: Findings from this study will inform future trials to identify patients who are most likely to benefit from primary prevention ICD.Trial Registration: URL: http://www.clinicaltrials.gov . Unique identifier: NCT03210883. [ABSTRACT FROM AUTHOR]

Advanced sensing and internet of things bring the big data, which provides an unprecedented opportunity for data-driven knowledge discovery. However, it is common that a large number of variables (or predictors, features) are involved in the big data. Complex interdependence structures among variables pose significant challenges on the traditional framework of predictive modeling. This paper presents a new methodology of self-organizing network to characterize the interrelationships among variables and cluster them into homogeneous subgroups for predictive modeling. Specifically, we develop a new approach, namely nonlinear coupling analysis to measure variable-to-variable interdependence structures. Further, each variable is represented as a node in the complex network. Nonlinear-coupling forces move these nodes to derive a self-organizing topology of the network. As such, variables are clustered into sub-network communities. Results of simulation experiments demonstrate that the proposed method not only outperforms traditional variable clustering algorithms such as hierarchical clustering and oblique principal component analysis, but also effectively identifies interdependent structures among variables and further improves the performance of predictive modeling. Additionally, real-world case study shows that the proposed method yields an average sensitivity of 96.80% and an average specificity of 92.62% in the identification of myocardial infarctions using sparse parameters of vectorcardiogram representation models. The proposed new idea of self-organizing network is generally applicable for predictive modeling in many disciplines that involve a large number of highly-redundant variables. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Myocardial infarction is a coronary artery ailment, and it is characterized by the changes in the morphological features such as the shape of T-wave, Q-wave and ST-segment of ECG signal. In clinical standard, it is a challenging problem to diagnose MI pathology using 12-lead ECG and vectorcardiogram (VCG). VCG has the advantage to record the heart electrical activities in three orthogonal planes (frontal, sagittal and transverse). This paper proposes a new method for automated detection or grading of MI pathology from vectorcardiogram (VCG) signals. The method uses relevance vector machine (RVM) classifier and the multiscale features of VCG signal for MI detection. The multiscale analysis of VCG signal is performed using dual-tree complex wavelet transform. The diagnostic features such as the complex wavelet sub-band (CWS) $$L_{1}$$ -Norm (CWS $$L_{1}$$ -norm) and the complex wavelet entropy (CWE) are evaluated from the sub-band complex wavelet coefficients of each orthogonal lead of VCG. The RVM classifier is considered to evaluate the performance of the combination of the CWS $$L_{1}$$ -norm and the CWE features of VCG. Three different kernel functions such as Gaussian, bubble and Cauchy are used for RVM. The results show that the RVM classifier with Gaussian kernel function has an average accuracy, an average sensitivity and an average specificity values of 99.80, 99.67 and 99.90%, respectively. The performance of RVM classifier is compared with the existing methods for detection of MI from VCG and 12-lead ECG signals. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Practical Electrocardiology is the property of Journal of Practical Electrocardiology Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Progress in Modern Biomedicine is the property of Publishing House of Progress in Modern Biomedicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Progress in Modern Biomedicine is the property of Publishing House of Progress in Modern Biomedicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Medicina Neotloznyh Sostoanij is the property of Zaslavsky O.Yu and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aims: Left ventricular activation delay due to left bundle branch block (LBBB) is an important determinant of the severity of dyssynchronous heart failure (DHF). We investigated whether patient-specific computational models constructed from non-invasive measurements can provide measures of baseline dyssynchrony and its reduction after CRT that may explain the degree of long-term reverse ventricular remodelling.Methods and Results: LV end-systolic volume reduction (ΔESVLV) measured by 2D trans-thoracic echocardiography in eight patients following 6 months of CRT was significantly (P < 0.05) greater in responders (26 ± 20%, n = 4) than non-responders (11 ± 16%, n = 4). LV reverse remodelling did not correlate with baseline QRS duration or its change after biventricular pacing, but did correlate with baseline LV endocardial activation measured by electroanatomic mapping (R2 = 0.71, P < 0.01). Patient-specific models of LBBB ventricular activation with parameters obtained by matching model-computed vectorcardiograms (VCG) to those derived from standard patient ECGs yielded LV endocardial activation times that correlated well with those measured from endocardial maps (R2 = 0.90). Model-computed 3D LV activation times correlated strongly with the reduction in LVESV (R2 = 0.93, P < 0.001). Computed decreases due to simulated CRT in the time delay between LV septal and lateral activation correlated strongly with ΔESVLV (R2 = 0.92, P < 0.001). Models also suggested that optimizing VV delays may improve resynchronization by this measure of activation delay.Conclusions: Patient-specific computational models constructed from non-invasive measurements can compute estimates of LV dyssynchrony and their changes after CRT that may be as good as or better than electroanatomic mapping for predicting long-term reverse remodelling. [ABSTRACT FROM AUTHOR]

The electrocardiogram is an important tool for the initial diagnostic suspicion of hypertrophic cardiomyopathy in any of its forms, both in symptomatic and in asymptomatic patients because it is altered in more than 90 percent of the cases. Electrocardiographic anomalies are more common in patients carriers of manifest hypertrophic cardiomyopathy and the electrocardiogram alterations are earlier and more sensitive than the increase in left ventricular wall thickness detected by the echocardiogram. Nevertheless, despite being the leading cause of sudden death among young competitive athletes there is no consensus over the need to include the method in the pre-participation screening. In apical hypertrophic cardiomyopathy the electrocardiographic hallmarks are the giant negative T waves in anterior precordial leads. In the vectorcardiogram, the QRS loop is located predominantly in the left anterior quadrant and T loop in the opposite right posterior quadrant, which justifies the deeply negative T waves recorded. The method allows estimating the left ventricular mass because it relates to the maximal spatial vector voltage of the left ventricle in the QRS loop. The recording on electrocardiogram or Holter monitoring of nonsustained monomorphic ventricular tachycardia in patients with syncope, recurrent syncope in young patient, hypotension induced by strain, bradyarrhythmia, or concealed conduction are markers of poor prognosis. The presence of rare sustained ventricular tachycardia is observed in mid-septal obstructive HCM with apical aneurysm. The presence of complete right bundle branch block pattern is frequent after the percutaneous treatment and complete left bundle branch block is the rule after myectomy. [ABSTRACT FROM AUTHOR]

Measurements of the Q-T interval are less reliable in children than in adults. Identification of superior diagnostic tools is warranted. This study aimed to investigate whether a vectorcardiogram (VCG) recorded from three orthogonal leads (X, Y, Z) according to Frank is superior to a 12-lead electrocardiogram (ECG) in providing a correct long Q-T syndrome (LQTS) diagnosis in children. This LQTS group consisted of 35 genetically confirmed carriers of mutations in the KCNQ1 ( n = 29) and KCNH2 ( n = 6) genes. The control group consisted of 35 age- and gender-matched healthy children. The mean age was 7 years in the LQTS group and 6.7 years in the control group (range, 0.5-16 years). The corrected Q-T interval (QT) was measured manually (QT) by one author (A.W.). The 12-lead ECG automatic measurements (QT) and interpretation (QT) of QT were performed with the Mac5000 (GE Medical System), and the VCG automatic measurements (QT) were performed with the Mida1000, CoroNet (Ortivus AB, Sweden). By either method, a QT longer than 440 ms was considered prolonged and indicative of LQTS. Of the 35 children with genetically confirmed LQTS, 30 (86 %) received a correct diagnosis using QT, 29 (82 %) using QT, 24 (69 %) using QT, and 17 (49 %) using QT. Specificity was 0.80 for QT, 0.83 for QT, 0.77 for QT, and 0.83 for QT. The VCG automatic measurement of QT seems to be a better predictor of LQTS than automatic measurement and interpretation of 12-lead ECG. [ABSTRACT FROM AUTHOR]

Aims Previous studies have reported right bundle branch block in Brugada syndrome. Subsequent analysis of electrocardiograms (ECGs) found one-third of cases classified as right bundle branch block did not meet criteria of a wide final S wave in the left leads. We aimed to study the role of the vectorcardiogram to characterize Brugada type 1 ECG pattern. Methods and results Compare Frank-method vectorcardiogram in 11 patients with Brugada type 1 ECG pattern (BrS group) with vectorcardiogram of 20 healthy individuals with ECGs depicting incomplete right bundle branch block (IRBBB group) and 12 patients with complete right bundle branch block (CRBBB group). Initial 10–20 ms vector of the QRS loop in the horizontal plane (HP): BrS and IRBBB groups: Vector heading anterior and leftward. CRBBB group: Vector directed anterior and rightward. Conclusions Vectorcardiograms in patients with Brugada type 1 ECG pattern have distinctive characteristics compared with healthy individuals with incomplete and CRBBB. These differences relate to the spatial location of the end conduction delay (right superior and posterior quadrant in the BrS group) and the morphology, size, and velocity of inscription of afferent and efferent limbs of the T loop (circular, small, of symmetrical limbs) and with a 1:1 length/width ratio. [ABSTRACT FROM PUBLISHER]

The electrocardiogram (ECG) is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks, may contain useful information about the nature of disease afflicting the heart. However, these subtle details cannot be directly monitored by the human observer. Besides, these signals are highly subjective, and the symptoms may appear at random in the time scale. It is very taxing and time-consuming to decipher cardiac abnormalities based on these ECG signals. The Vectorcardiogram (VCG) is the vector loop in the 2-D frontal plane, indicating the magnitude and direction of the instantaneous heart electrical activity vector (HAV), which represents the sum of the dipole vectors located along the instantaneous depolarization wavefront. The HAV is constructed from the monitored 3-lead ECG signals, placed at the three vertices of the modified Einthoven triangle formed by the 3-lead system in the frontal plane of the torso. The VCG examines the electrical activities within the heart, using the ECG signals along the three sides of the modified Einthoven triangle, and displays electrical events in the 2-dimensional frontal plane. This study demonstrates the development of the heart-depolarisation vector-locus cardiogram (using modified Einthoven’s triangle), as a diagnostic measure of the left ventricular depolarisation strength. Our work involves the reconstruction of the “equivalent heart vector” for the QRS complex from limb lead voltages of a sample ECG, and plotting the progression of the cardiac vector during the QRS complex. We have demonstrated the construction of the frontal plane heart-depolarization vector cardiogram (HDVC), as the path of the locus of the tip of the heart electrical activity vector, with initial and terminal points at the origin. In this work, we have shown characteristic patterns of HDVC for cardiac states namely, normal, bundle branch block, ventricular hypertrophy and myocardial infarction. We have demonstrated how HDVC can be diagnostically employed to characterize cardiac disorders, such as ventricular hypertrophy bundle branch block and inferior myocardial infarction. [ABSTRACT FROM AUTHOR]

Introduction: Spatial characteristics of atrial fibrillatory waves have been extracted by using a vectorcardiogram (VCG) during atrial fibrillation (AF). However, the VCG is usually not recorded in clinical practice and atrial loops are derived from the 12-lead electrocardiogram (ECG). We evaluated the suitability of the reconstruction of orthogonal leads from the 12-lead ECG for fibrillatory waves in AF. Methods: We used the Physikalisch-Technische Bundesanstalt diagnostic ECG database, which contains 15 simultaneously recorded signals (12-lead ECG and three Frank orthogonal leads) of 13 patients during AF. Frank leads were derived from the 12-lead ECG by using Dower's inverse transform. Derived leads were then compared to true Frank leads in terms of the relative error achieved. We calculated the orientation of AF loops of both recorded orthogonal leads and derived leads and measured the difference in estimated orientation. Also, we investigated the relationship of errors in derivation with fibrillatory wave amplitude, frequency, wave residuum, and fit to a plane of the AF loops. Results: Errors in derivation of AF loops were 68 ± 31% and errors in the estimation of orientation were 35.85 ± 20.43°. We did not find any correlation among these errors and amplitude, frequency, or other parameters. Conclusions: In conclusion, Dower's inverse transform should not be used for the derivation of orthogonal leads from the 12-lead ECG for the analysis of fibrillatory wave loops in AF. Spatial parameters obtained after this derivation may differ from those obtained from recorded orthogonal leads. [ABSTRACT FROM AUTHOR]

Aims The aim of this study was to assess the prognostic importance of the spatial QRS-T angle for fatal and non-fatal cardiac events.Methods and results Electrocardiograms (ECGs) were recorded in 6134 men and women aged 55 years and over from the prospective population-based Rotterdam Study. Spatial QRS-T angles were categorized as normal, borderline or abnormal. Using Cox's proportional hazards model, abnormal angles showed increased hazard ratios of cardiac death (age-and sex-adjusted hazard ratio 5.2 (95% CI 4.0–6.8)), non-fatal cardiac events (2.2 (1.5–3.1)), sudden death (5.6 (3.7–8.5)) and total mortality (2.3 (2.0–2.7)). None of the classical cardiovascular and ECG predictors provided larger hazard ratios. After adjustment for these predictors, the association of abnormal spatial QRS-T angles with all fatal study endpoints remained strong, but the association with non-fatal cardiac events disappeared. Computation of Akaike's information criterion showed that the angle contributed significantly to the prediction of all fatal endpoints by classical cardiovascular and ECG predictors.Conclusion The spatial QRS-T angle is a strong and independent predictor of cardiac mortality in the elderly. It is stronger than any of the classical cardiovascular risk factors and ECG risk indicators and provides additional value to them in predicting fatal cardiac events. [ABSTRACT FROM PUBLISHER]

Some studies provide a link between the width of QRS complexes and late potentials occurring at the end of the QRS complex in signal-averaged recordings. The purpose of this study was to compare three methods of QRS duration measurement: the conventional 12 lead ECG. the Frank vectorcardiogram (VCG) and the signal-averaged electrocardiogram. The recordings were made at a similar time in 121 consecutive patients with the Cardionics PC-based system (ECG and VCG) and the ardionics high resolution ECG, based on methods described by Simson. Patients with bundle branch block were excluded. All patients had presented a myocardial infarction and were studied either for spontaneous ventricular arrhythmias or systematically 3 to 6 weeks after an acute myocardial infarction. The signal-averaged ECG and VCG QRS durations were similar in 41 patients without inducible ventricular arrhythmias and with normal signal-averaged ECG but were longer (<0·001) than the conventional ECG QRS duration. In 36 patients with spontaneous and inducible ventricular tachyarrhythmias, the QRS duration was significantly longer on signal-averaged ECG than on VCG (<0·05) and longer on VCG than on conventional ECG (<0·05). The QRS duration was also significantly (<0·001) longer with the three techniques in patients with spontaneous ventricular tachycardia (VT) than in patients without spontaneous and inducible VT. A QRS duration on VCG ≥ 110 ms and on conventional ECG ≥ 100 ms had a sensitivity of 93% and 77% and a specificity of 83% and 85% respectively for predicting an abnormal signal-averaged ECG. In conclusion, the measurement of QRS duration with the conventional ECG, VCG or the signal-averaged ECG could be a simple method to detect the patients with myocardial infarction prone to VT. [ABSTRACT FROM PUBLISHER]

Twelve patients with double-chambered right ventricles were investigated to determine the significance of the electrocardiogram and vectorcardiogram in the evaluation of this condition. Two subgroups of individuals having various forms of obstruction to right ventricular outflow with and without intracardiac shunting were utilized as controls. The electrocardiogram of patients with double-chambered right ventricle had a characteristic appearance identifiable as a right ventricular hypertrophy pattern seen best in the extreme right precordial leads VR–VR with tendency to normalization of pattern in V, which contrasted with the pattern in both control subgroups. The vectorcardiogram in all 8 cases of double-chambered right ventricle in which this study was performed exhibited homogeneity of loop appearance and direction best identifiable in the horizontal plane by a prominent terminal orientation of the loop rightward and posteriorly. Both control subgroups exhibited heterogeneity of loop conformation, significantly more initial right-anterior force and less rightposterior force than the double-chambered right ventricle group. The electro-vectorcardiographic findings with double-chambered right ventricle were predictable for this abnormality and appear to have significant diagnostic importance. [ABSTRACT FROM PUBLISHER]

Copyright of Klinische Wochenschrift is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Klinische Wochenschrift is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Patients with Brugada syndrome (BrS) can show a leftward deviation of the frontal QRS-axis upon provocation with sodium channel blockers. The cause of this axis change is unclear. In this study, we aimed to determine (1) the prevalence of this left axis deviation and (2) to evaluate its cause, using the insights that could be derived from vectorcardiograms. Hence, from a large cohort of patients who underwent ajmaline provocation testing (n = 1430), we selected patients in whom a type-1 BrS-ECG was evoked (n = 345). Depolarization and repolarization parameters were analyzed for reconstructed vectorcardiograms and were compared between patients with and without a >30° leftward axis shift. We found (1) that the prevalence of a left axis deviation during provocation testing was 18% and (2) that this left axis deviation was not explained by terminal conduction slowing in the right ventricular outflow tract (4th QRS-loop quartile: +17 ± 14 ms versus +13 ± 15 ms, nonsignificant) but was associated with a more proximal conduction slowing (1st QRS-loop quartile: +12[8;18] ms versus +8[4;12] ms, p < 0.001 and 3rd QRS-loop quartile: +12 ± 10 ms versus +5 ± 7 ms, p < 0.001). There was no important heterogeneity of the action potential morphology (no difference in the ventricular gradient), but a left axis deviation did result in a discordant repolarization (spatial QRS-T angle: 122[59;147]° versus 44[25;91]°, p < 0.001). Thus, although the development of the type-1 BrS-ECG is characterized by a terminal conduction delay in the right ventricle, BrS-patients with a left axis deviation upon sodium channel blocker provocation have an additional proximal conduction slowing, which is associated with a subsequent discordant repolarization. Whether this has implications for risk stratification is still undetermined. [ABSTRACT FROM AUTHOR]

Background: Global electrical heterogeneity (GEH) is associated with sudden cardiac death (SCD) in adults of 45 years and above. However, GEH has not been previously measured in young athletes. The goal of this study was to establish a reference for vectorcardiograpic (VCG) metrics in male and female athletes.Methods: Skiers (n = 140; mean age 19.2 ± 3.5 years; 66% male, 94% white; 53% professional athletes) were enrolled in a prospective cohort. Resting 12-lead ECGs were interpreted per the International ECG criteria. Associations of age, sex, and athletic performance with GEH were studied.Results: In age and training level-adjusted analyses, male sex was associated with a larger T vector [T peak magnitude +186 (95% CI 106-266) µV] and a wider spatial QRS-T angle [+28.2 (17.3-39.2)°] as compared to women. Spatial QRS-T angle in the ECG left ventricular hypertrophy (LVH) voltage group (n = 21; 15%) and normal ECG group did not differ (67.7 ± 25.0 vs. 66.8 ± 28.2; p = 0.914), suggesting that ECG LVH voltage in athletes reflects physiological remodeling. In contrast, skiers with right ventricular hypertrophy (RVH) voltage (n = 26, 18.6%) had wider QRS-T angle (92.7 ± 29.6 vs. 66.8 ± 28.2°; p = 0.001), larger SAI QRST (194.9 ± 30.2 vs. 157.8 ± 42.6 mV × ms; p < 0.0001), but similar peak SVG vector magnitude (1976 ± 548 vs. 1939 ± 395 µV; p = 0.775) as compared to the normal ECG group. Better athletic performance was associated with the narrower QRS-T angle. Each 10% worsening in an athlete's Federation Internationale de' Ski downhill ranking percentile was associated with an increase in spatial QRS-T angle by 2.1 (95% CI 0.3-3.9) degrees (p = 0.013).Conclusion: Vectorcardiograpic adds nuances to ECG phenomena in athletes. [ABSTRACT FROM AUTHOR]

Ebstein's anomaly is a congenital heart disease where the most important anatomic feature is the inferior displacement of the tricuspid valve leaflets. Vectorcardiographic features are mainly forgotten and electrocardiographic features may be unrecognized by cardiologists handling adult patients. [ABSTRACT FROM AUTHOR]