Empagliflozin's role in reducing ventricular repolarization heterogeneity: insights into cardiovascular mortality decline from the EMPATHY-HEART trial.

BACKGROUND: The incidence of myocardial infarction (MI) and sudden cardiac death (SCD) is significantly higher in individuals with Type 2 Diabetes Mellitus (T2DM) than in the general population. Strategies for the prevention of fatal arrhythmias are often insufficient, highlighting the need for additional non-invasive diagnostic tools. The T-wave heterogeneity (TWH) index measures variations in ventricular repolarization and has emerged as a promising predictor for severe ventricular arrhythmias. Although the EMPA-REG trial reported reduced cardiovascular mortality with empagliflozin, the underlying mechanisms remain unclear. This study investigates the potential of empagliflozin in mitigating cardiac electrical instability in patients with T2DM and coronary heart disease (CHD) by examining changes in TWH. METHODS: Participants were adult outpatients with T2DM and CHD who exhibited TWH > 80 µV at baseline. They received a 25 mg daily dose of empagliflozin and were evaluated clinically including electrocardiogram (ECG) measurements at baseline and after 4 weeks. TWH was computed from leads V4, V5, and V6 using a validated technique. The primary study outcome was a significant (p < 0.05) change in TWH following empagliflozin administration. RESULTS: An initial review of 6,000 medical records pinpointed 800 patients for TWH evaluation. Of these, 412 exhibited TWH above 80 µV, with 97 completing clinical assessments and 90 meeting the criteria for high cardiovascular risk enrollment. Empagliflozin adherence exceeded 80%, resulting in notable reductions in blood pressure without affecting heart rate. Side effects were generally mild, with 13.3% experiencing Level 1 hypoglycemia, alongside infrequent urinary and genital infections. The treatment consistently reduced mean TWH from 116 to 103 µV (p = 0.01). CONCLUSIONS: The EMPATHY-HEART trial preliminarily suggests that empagliflozin decreases heterogeneity in ventricular repolarization among patients with T2DM and CHD. This reduction in TWH may provide insight into the mechanism behind the decreased cardiovascular mortality observed in previous trials, potentially offering a therapeutic pathway to mitigate the risk of severe arrhythmias in this population. TRIAL REGISTRATION: NCT: 04117763.

Repolarization indicates electrical instability in ventricular arrhythmia originating from papillary muscle.

AIMS: Cardiac arrhythmia originating from the papillary muscle (PM) can trigger ventricular fibrillation (VF) and cause sudden cardiac death even in the absence of structural heart disease. Most premature ventricular contractions, however, are benign and hitherto difficult to distinguish from a potentially fatal arrhythmia. Altered repolarization characteristics are associated with electrical instability, but electrophysiological changes which precede degeneration into VF are still not fully understood. METHODS AND RESULTS: Ventricular arrhythmia (VA) was induced by aconitine injection into PMs of healthy sheep. To investigate mechanisms of degeneration of stable VA into VF in structurally healthy hearts, endocardial high-density and epicardial mapping was performed during sinus rhythm (SR) and VA. The electrical restitution curve, modelling the relation of diastolic interval and activation recovery interval (a surrogate parameter for action potential duration), is steeper in VA than in non-arrhythmia (ventricular pacing and SR). Steeper restitution curves reflect electrical instability and propensity to degenerate into VF. Importantly, we find the parameter repolarization time in relation to cycle length (RT/CL) to differentiate self-limiting from degenerating arrhythmia with high specificity and sensitivity. CONCLUSION: RT/CL may serve as a simple index to aid differentiation between self-limiting and electrically instable arrhythmia with the propensity to degenerate to VF. RT/CL is independent of cycle length and could easily be measured to identify electrical instability in patients.

Risk stratification for sudden cardiac death: current status and challenges for the future.

Sudden cardiac death (SCD) remains a daunting problem. It is a major public health issue for several reasons: from its prevalence (20% of total mortality in the industrialized world) to the devastating psycho-social impact on society and on the families of victims often still in their prime, and it represents a challenge for medicine, and especially for cardiology. This text summarizes the discussions and opinions of a group of investigators with a long-standing interest in this field. We addressed the occurrence of SCD in individuals apparently healthy, in patients with heart disease and mild or severe cardiac dysfunction, and in those with genetically based arrhythmic diseases. Recognizing the need for more accurate registries of the global and regional distribution of SCD in these different categories, we focused on the assessment of risk for SCD in these four groups, looking at the significance of alterations in cardiac function, of signs of electrical instability identified by ECG abnormalities or by autonomic tests, and of the progressive impact of genetic screening. Special attention was given to the identification of areas of research more or less likely to provide useful information, and thereby more or less suitable for the investment of time and of research funds.

Effect of angiotensin receptor-neprilysin inhibitor on atrial electrical instability in atrial fibrillation.

Background and objective: Around 33.5 million patients suffered from atrial fibrillation (AF), causing complications and increasing mortality and disability rate. Upstream treatment for AF is getting more popular in clinical practice in recent years. The angiotensin receptor-neprilysin inhibitor (ARNI) is one of the potential treatment options. Our study aimed to investigate the effect of ARNI on atrial electrical instability and structural remodeling in AF. Methods: Our research consisted of two parts - a retrospective real-world clinical study and an animal experiment on calmness to verify the retrospective founding. In the retrospective study, we reviewed all patients (n = 110) who had undergone the first AF ablation from 1 August 2018 to 1 March 2022. Patients with ARNI (n = 36) or angiotensin II receptor antagonist (ARB) (n = 35) treatment were enrolled. Their clinical data, ultrasound cardiogram (UCG) and Holter parameters were collected before radiofrequency catheter ablation (RFCA) as baseline and at 24-week follow-up. Univariate and multivariate logistic regression analysis were performed. In the animal experiment, we established an AF model (n = 18) on canines by rapid atrial pacing. After the successful procedure of pacing, all the 15 alive beagles were equally and randomly assigned to three groups (n = 5 each): Control group, ARB group, and ARNI group. UCG was performed before the pacing as baseline. Physiological biopsy, UCG, and electrophysiological study (EPS) were performed at 8-week. Results: Clinical data showed that the atrial arrhythmia rate at 24-week was significantly lower in ARNI group compared to ARB group (P < 0.01), and ARNI was independently associated with a lower atrial arrhythmia rate (P < 0.05) at 24-week in multivariate regression logistic analysis. In the animal experiment, ARNI group had a higher atrial electrical stability score and a shorter AF duration in the EPS compared to Control and ARB group (P < 0.05). In the left atrium voltage mapping, ARNI group showed less low voltage and disordered zone compared to Control and ARB group. Compared to Control group, right atrium diameter (RAD), left ventricle end-diastolic volume index (LVEDVI), E/A, and E/E' were lower in ARNI group (P < 0.05) at the 8-weeks follow-up, while left atrium ejection fraction (LAEF) and left ventricle ejection fraction (LVEF) were higher (P < 0.01). Compared to ARB group, LVEF was higher in ARNI group at the 8-week follow-up (P < 0.05). ARB and ARNI group had a lower ratio of fibrotic lesions in the left atrium tissues compared to Control group (P < 0.01), but no difference was found between the ARB and the ARNI group. Conclusion: ARNI could reduce atrial electrical instability in AF in comparison with ARB in both retrospective study and animal experiment.

A Digital Electrocardiographic System for Assessing Myocardial Electrical Instability: Principles and Applications.

The aim of the study was to develop an ECG hardware and software system for monitoring electrical instability of the myocardium and to assess the diagnostic and prognostic capabilities of this setup in a cardiology clinic. MATERIALS AND METHODS: The Intecard 7.3 software and hardware system developed in this study makes it possible to measure fluctuations of the ECG amplitude-time parameters using the beat-to-beat mode. Intecard 7.3 evaluates a number of ECG markers that reflect electrical instability of the myocardium. Among them are the fragmented QRS complex, the spatial QRS-T angle, the T-wave alternans, the duration, and dispersion of the QT interval, the turbulence and acceleration/deceleration of the heart rhythm.Clinical trials of Intecard 7.3 were carried out with 734 patients with ischemic heart disease or cardiomyopathy and 112 healthy individuals. RESULTS: Intecard 7.3 reliably identifies fragmented QRS complexes by detecting short spikes of <25 ms in the ascending parts of the Q, R, and S waves. The QRS-T angle is determined from the reference amplitudes of the R and T waves in leads avF, V2, V5, and V6. Digital precision processing of the ECG signal improves its accuracy to microvolts and microseconds.The software was designed to measure the T-wave amplitude in each of 300-500 cardiobeats; T-wave alternans was estimated by the moving average method. In a typical cardiobeat, the QT dispersion was calculated based on 12 ECG leads. From the sequence of RR intervals, turbulence, and deceleration of the heart rhythm were determined.During the observation period of 5.0 [2.1; 5.9] years, 90 out of 734 patients (12.3%) experienced adverse cardiovascular events (ACVE). In this period, the myocardial electrical instability was recorded in patients with ACVE more frequently than in those without ACVE. Thus, the frequency of fragmented QRS was 72.2±4.7 vs 16.8±1.5% (p<0.01), the values of the QRS-T angle were 128 [55; 101] vs 80 [53; 121]° (p<0.001), the T-wave alternans - 36.9 [15.5; 62.1] vs 21.9 [10.2; 30.7] µV (p<0.005), the QT interval - 408 [383; 438] vs 376 [351; 400] ms (p<0.001), the QT dispersion - 76 [57; 96] vs 64 [50; 92] ms (p<0.005), respectively. In patients with ACVE, the threshold that triggers pathological rhythm turbulence was higher (>0%) than that in healthy controls (p<0.001); the deceleration of the heart rhythm was reduced from 19.2 [2.2; 38.0] to 8.8 [4.0; 16.8] ms (p<0.05).A personalized model for ACVE risk stratification has been developed. In this model, the area under the ROC curve was 0.856; sensitivity - 75%; specificity - 78%; predictive accuracy - 77%. CONCLUSION: Using the ECG markers of myocardial electrical instability, the Intecard 7.3 system allows one to predict life-threatening ventricular tachyarrhythmias and sudden cardiac death with an accuracy of 77%. The non-invasiveness, high productivity, and reasonable cost ensure the availability of this predictive technology in all levels of healthcare.

Prediction of Cardiac Mechanical Performance From Electrical Features During Ventricular Tachyarrhythmia Simulation Using Machine Learning Algorithms.

In ventricular tachyarrhythmia, electrical instability features including action potential duration, dominant frequency, phase singularity, and filaments are associated with mechanical contractility. However, there are insufficient studies on estimated mechanical contractility based on electrical features during ventricular tachyarrhythmia using a stochastic model. In this study, we predicted cardiac mechanical performance from features of electrical instability during ventricular tachyarrhythmia simulation using machine learning algorithms, including support vector regression (SVR) and artificial neural network (ANN) models. We performed an electromechanical tachyarrhythmia simulation and extracted 12 electrical instability features and two mechanical properties, including stroke volume and the amplitude of myocardial tension (ampTens). We compared predictive performance according to kernel types of the SVR model and the number of hidden layers of the ANN model. In the SVR model, the prediction accuracies of stroke volume and ampTens were the highest when using the polynomial kernel and linear kernel, respectively. The predictive performance of the ANN model was better than that of the SVR model. The prediction accuracies were the highest when the ANN model consisted of three hidden layers. Accordingly, we propose the ANN model with three hidden layers as an optimal model for predicting cardiac mechanical contractility in ventricular tachyarrhythmia. The results of this study are expected to be used to indirectly estimate the hemodynamic response from the electrical cardiac map measured by the optical mapping system during cardiac surgery, as well as cardiac contractility under normal sinus rhythm conditions.

Risk stratification personalised model for prediction of life-threatening ventricular tachyarrhythmias in patients with chronic heart failure.

BACKGROUND: The development of prognostic factors of life-threatening ventricular tachyarrhythmias (VTA) and sudden cardiac death (SCD) continues to maintain its priority and relevance in cardiology. The development of a method of personalised prognosis based on multifactorial analysis of the risk factors associated with life-threatening heart rhythm disturbances is considered a key research and clinical task. AIM: To design a prognostic and mathematical model to define personalised risk for life-threatening VTA in patients with chronic heart failure (CHF). METHODS: The study included 240 patients with CHF (mean-age of 50.5 ± 12.1 years; left ventricular ejection fraction 32.8 ± 10.9%; follow-up period 36.8 ± 5.7 months). The participants received basic therapy for heart failure. The elec-trocardiogram (ECG) markers of myocardial electrical instability were assessed including microvolt T-wave alternans, heart rate turbulence, heart rate deceleration, and QT dispersion. Additionally, echocardiography and Holter monitoring (HM) were performed. The cardiovascular events were considered as primary endpoints, including SCD, paroxysmal ventricular tachycardia/ventricular fibrillation (VT/VF) based on HM-ECG data, and data obtained from implantable device interrogation (CRT-D, ICD) as well as appropriated shocks. RESULTS: During the follow-up period, 66 (27.5%) subjects with CHF showed adverse arrhythmic events, including nine SCD events and 57 VTAs. Data from a stepwise discriminant analysis of cumulative ECG-markers of myocardial electrical instability were used to make a mathematical model of preliminary VTA risk stratification. Uni- and multivariate Cox logistic regression analysis were performed to define an individualised risk stratification model of SCD/VTA. A binary logistic regression model demonstrated a high prognostic significance of discriminant function with a classification sensitivity of 80.8% and specificity of 99.1% (F = 31.2; c2 = 143.2; p < 0.0001). CONCLUSIONS: The method of personalised risk stratification using Cox logistic regression allows correct classification of more than 93.9% of CHF cases. A robust body of evidence concerning logistic regression prognostic significance to define VTA risk allows inclusion of this method into the algorithm of subsequent control and selection of the optimal treatment modality to treat patients with CHF.

Antiarrhythmic Effect Of Antioxidants In Patients With Atrial Fibrillation.

Resume In accordance with modern concepts, one of the leading roles in the development of paroxysmal atrial fibrillation and flutter, belongs - the restructuring of the myocardium, in second place - sick sinus syndrome and in third place - the presence of accessory pathways and hormonal disorders. The development of atrial fibrillation and flutter in the structural pathology, primarily begins with of drugs if it does not work, we have to carry out ablation. Providing proper, effective and important combination therapy - is the main challenge in cardiology.

Prevention of ventricular arrhythmia complicating acute myocardial infarction by local cardiac denervation.

BACKGROUND: Augmentation of sympathetic nerve activity after acute myocardial infarction (AMI) contributes to fatal arrhythmia. In this study, we investigated whether local ablation of the coronary sinus (CS) and great cardiac vein (GCV) peripheral nerves could reduce ventricular arrhythmias (VA) in a canine AMI model. METHODS: Twenty-one anesthetized dogs were randomly assigned into the sham-operated, MI and MI-ablation groups, respectively. The incidence and duration of VA were monitored among different groups. The ventricular effective refractory period (ERP), the ERP dispersion and the ventricular fibrillation threshold (VFT) were measured during the experiments. Norepinephrine (NE) levels in CS blood and cardiac tissue were also detected in this study. RESULTS: The incidence and duration of VA in MI-ablation group were significantly reduced as compared to the MI dogs (p<0.05). Furthermore, local cardiac denervation drastically prolonged the ventricular ERP in the ischemia area, decreased the ERP dispersion, and reduced NE levels in CS blood (P<0.05). VFT also showed an increased trend in the AMI-ablation group. CONCLUSIONS: The results of this study indicate that, in the canine AMI model, local ablation of CS and GCV peripheral nerves reduces VA occurrence and improves ventricular electrical stability with no obvious effects on heart rate, mean arterial pressure and infarct size. This study suggests that local cardiac denervation may prevent ventricular arrhythmias complicating AMI.