Localization of Ventricular Arrhythmias for Catheter Ablation: The Role of Surface Electrocardiogram

Comprehensive review of pulmonary vein stenosis post-atrial fibrillation ablation: diagnosis, management, and prognosis

Pulmonary vein stenosis (PVS) can occasionally occur in the follow-up after pulmonary vein isolation (PVI) for atrial fibrillation (AF). During PVI, ablation is performed at the PV ostium or distal part, leading to tissue damage. This damage can result in fibrosis of the necrotic myocardium, proliferation, and thickening of the vascular intima, as well as thrombus formation, further advancing PVS. Mild-to-moderate PVS often remains asymptomatic, but severe PVS can cause symptoms, such as dyspnea, cough, fatigue, decreased exercise tolerance, chest pain, and hemoptysis. These symptoms are due to pulmonary hypertension and pulmonary infarction. Imaging evaluations such as contrast-enhanced computed tomography are essential for diagnosing PVS. Early suspicion and detection are necessary, as underdiagnosis can lead to inappropriate treatment, disease progression, and poor outcomes. The long-term prognosis of PVS remains unclear, particularly regarding the impact of mild-to-moderate PVS over time. PVS treatment focuses on symptom management, with no established definitive solutions. For severe PVS, transcatheter PV angioplasty is performed, though the risk of restenosis remains high. Restenosis and reintervention rates have improved with stent implantation compared with balloon angioplasty. The role of subsequent antiplatelet therapy remains uncertain. Dedicated evaluation is essential for accurate diagnosis and appropriate management to avoid significant long-term impacts on patient outcomes.

Clinical utility of ambulatory ECG monitoring and 2D-ventricular strain for evaluation of post-COVID-19 ventricular arrhythmia

BACKGROUND

A relatively common complication of COVID -19 infection is arrhythmia. There is limited information about myocardial deformation and heart rate variability (HRV) in symptomatic post COVID patients presented by ventricular arrhythmia.

AIM OF THE STUDY

Our goal was to assess 2D-ventricular strain and heart rate variability indices (evaluated by ambulatory ECG monitoring) in post-COVID-19 patients suffering from ventricular arrhythmia.

METHODS

The current observational case-control study performed on 60 patients one month after they had recovered from the COVID-19 infection. Thirty healthy volunteers served as the control group. Each participant had a full medical history review, blood tests, a 12-lead surface electrocardiogram (ECG), 24-h ambulatory ECG monitoring, and an echo-Doppler examination to evaluate the left ventricular (LV) dimensions, tissue Doppler velocities, and 2D-speckle tracking echocardiography (2D-STE) for both the LV and right ventricular (RV) strain.

RESULTS

Symptomatic post-COVID patients with monomorphic premature ventricular contractions (PVCs) showed a substantial impairment of LV/RV systolic and diastolic functions, LV/RV myocardial performance (MPI) with reduced indices of HRV. Patients with higher versus lower ventricular burden had poorer functional status, higher levels of inflammatory biomarkers and reduced parameters of HRV (New York Heart Association (NYHA) class: 2.1 ± 0.9 vs. 1.5 ± 0.6, p < 0.001, C-reactive protein (CRP): 13.3 ± 4.1 vs. 8.3 ± 5.9 mg/L, p < 0.0001, low frequency/high frequency (LF/HF): 3.6 ± 2.4 vs. 2.2 ± 1.2, p < 0.002, the root mean square of the difference between successive normal intervals (rMSSD): 21.8 ± 4.7 vs. 29.3 ± 14.9 ms, p < 0.039 and the standard deviation of the RR interval (SDNN): 69.8 ± 19.1 vs.108.8 ± 37.4 ms, p < 0.0001). The ventricular burden positively correlated with neutrophil/lymphocyte ratio (NLR) (r = 0.33, p < 0.001), CRP (r = 0.60, p < 0.0001), while it negatively correlated with LV-global longitudinal strain (GLS) (r = -0.38, p < 0.0001), and RV-GLS (r = -0.37, p < 0.0001).

CONCLUSIONS

Patients with post-COVID symptoms presented by ventricular arrhythmia had poor functional status. Patients with post-COVID symptoms and ventricular arrhythmia had subclinical myocardial damage, evidenced by speckle tracking echocardiography while having apparently preserved LV systolic function. The burden of ventricular arrhythmia in post-COVID patients significantly correlated with increased inflammatory biomarkers and reduced biventricular strain.

Flecainide in Ventricular Arrhythmias: From Old Myths to New Perspectives

Flecainide is an IC antiarrhythmic drug (AAD) that received in 1984 Food and Drug Administration approval for the treatment of sustained ventricular tachycardia (VT) and subsequently for rhythm control of atrial fibrillation (AF). Currently, flecainide is mainly employed for sinus rhythm maintenance in AF and the treatment of idiopathic ventricular arrhythmias (IVA) in absence of ischaemic and structural heart disease on the basis of CAST data. Recent studies enrolling patients with different structural heart diseases demonstrated good effectiveness and safety profile of flecainide. The purpose of this review is to assess current evidence for appropriate and safe use of flecainide, 30 years after CAST data, in the light of new diagnostic and therapeutic tools in the field of ischaemic and non-ischaemic heart disease.

Catheter Ablation of Life-Threatening Ventricular Arrhythmias in Athletes

A recent surveillance analysis indicates that cardiac arrest/death occurs in ≈1:50,000 professional or semi-professional athletes, and the most common cause is attributable to life-threatening ventricular arrhythmias (VAs). It is critically important to diagnose any inherited/acquired cardiac disease, including coronary artery disease, since it frequently represents the arrhythmogenic substrate in a substantial part of the athletes presenting with major VAs. New insights indicate that athletes develop a specific electro-anatomical remodeling, with peculiar anatomic distribution and VAs patterns. However, because of the scarcity of clinical data concerning the natural history of VAs in sports performers, there are no dedicated recommendations for VA ablation. The treatment remains at the mercy of several individual factors, including the type of VA, the athlete's age, and the operator's expertise. With the present review, we aimed to illustrate the prevalence, electrocardiographic (ECG) features, and imaging correlations of the most common VAs in athletes, focusing on etiology, outcomes, and sports eligibility after catheter ablation.

Localization of origins of premature ventricular contraction in the whole ventricle based on machine learning and automatic beat recognition from 12-lead ECG

OBJECTIVE

The localization of origins of premature ventricular contraction (PVC) is the key factor for the success of ablation of ventricular arrhythmias. Existing methods rely heavily on manual extraction of PVC beats, which limits their application to the automatic PVC recognition from long-term data recorded by ECG monitors before and during operation. In addition, research identifying PVC sources in the whole ventricle have not been reported. The purpose of this study was to validate the feasibility of localization of origins of PVC in the whole ventricle and to explore an automatic algorithm for recognition of PVC beats based on long-term 12-lead ECG.

APPROACH

This study included 249 patients with spontaneous PVCs or pacing-induced PVCs. A novel algorithm was used to automatically extract PVC beats from a massive amount of original ECG data, which was collected by different acquisition devices. After clustering and labelling, 374 sample groups, each containing dozens to hundreds of PVC beats, formed the entire dataset of 11 categories corresponding to 11 regions of PVC origins in the whole ventricle. To choose the best classification model for the current task, four machine learning methods, support vector machine (SVM), random forest (RF), gradient-boosting decision tree (GBDT) and Gaussian naïve Bayes (GNB), were compared by randomly selecting 70% of the entire dataset (sample groups = 257) for training and the remaining 30% (sample groups = 117) for testing. The average performance of each model was estimated by the bootstrap method using 1000 resampling trials.

MAIN RESULTS

For PVC beat recognition, the achieved testing accuracy, sensitivity and specificity is 97.6%, 98.3% and 96.7%, respectively. For localization purpose, the achieved testing accuracy varies slightly from 70.7% to 74.1% among four classifiers, and when neighboring regions were combined, the testing rank accuracy is improved to a range of 91.5% to 93.2%.

SIGNIFICANCE

The proposed algorithm can automatically recognize PVC beats and map them to one of the 11 regions in the whole ventricle. Owing to the high accuracy of PVC beat recognition and the capability to target the potential PVC origins in multi regions, it is expected to be a predominant technique being used in clinical settings to automatically analyze huge ECG data before and during operation so as to replace the tedious manual identification.