Biventricular / Left Ventricular Pacing in Hypertrophic Obstructive Cardiomyopathy: An Overview

Hypertrophic cardiomyopathy (HCM) is an autosomal dominant inherited genetic disease characterized by compensatory pathological left ventricle (LV) hypertrophy due to sarcomere dysfunction. In an important proportion of patients with HCM, the site and extent of cardiac hypertrophy results in severe obstruction to LV outflow tract (LVOT), contributing to disabling symptoms and increasing the risk of sudden cardiac death (SCD). In patients with progressive and/or refractory symptoms despite optimal pharmacological treatment, invasive therapies that diminish or abolish LVOT obstruction relieve heart failure-related symptoms, improve quality of life and could be associated with long-term survival similar to that observed in the general population. The gold standard in this respect is surgical septal myectomy, which might be supplementary associated with a reduction in SCD. Percutaneous techniques, particularly alcohol septal ablation (ASA) and more recently radiofrequency (RF) septal ablation, can achieve LVOT gradient reduction and symptomatic benefit in a large proportion of HOCM patients at the cost of a supposedly limited septal myocardial necrosis and a 10-20% risk of chronic atrioventricular block. After an initial period of enthusiasm, standard DDD pacing failed to show in randomized trials significant LVOT gradient reductions and objective improvement in exercise capacity. However, case reports and recent small pilot studies suggested that atrial synchronous LV or biventricular (biV) pacing significantly reduce LVOT obstruction and improve symptoms (acutely as well as long-term) in a large proportion of severely symptomatic HOCM patients not suitable to other gradient reduction therapies. Moreover, biV/LV pacing in HOCM seems to be associated with significant LV reverse remodelling

Use of therapeutic hypothermia and extracorporeal life support after an unusual response to the ajmaline challenge in a patient with Brugada syndrome

AbstractBackgroundBrugada syndrome is a cardiac disorder associated with a high risk of sudden cardiac death, especially in young subjects. The incidence and prevalence are likely underestimated. The diagnosis is based on a characteristic electrocardiography (ECG) pattern. The most commonly performed confirmatory test in cases of equivocal ECG is the intravenous ajmaline challenge. Although relatively safe, it carries the risk of ventricular arrhythmias that could potentially degenerate into a refractory electrical storm.Case reportA 27-year-old man developed sustained ventricular fibrillation after ajmaline challenge. He was rescued on extracorporeal life support after 108min of cardiopulmonary resuscitation. Extracorporeal life support allowed recovery of spontaneous circulation and resulted in a positive neurological outcome.<Learning objective: This case is an example of how extracorporeal life support was instituted after prolonged and unsuccessful cardiopulmonary resuscitation resulting in a positive central neurological outcome.

Computed tomography-based identification of ganglionated plexi to guide cardioneuroablation for vasovagal syncope

This study shows that CT-based EFP-guided CNA for CI-VVS is feasible, can assist RF delivery with high precision, and has the potential to overcome the interpatient variability that affects CNA when performed solely by anatomic landmarks. Further larger studies with longer follow-up are required to improve CT-based identification of GPs and our understanding of GP pathophysiology

Nonsurgical transthoracic epicardial radiofrequency ablation An alternative in incessant ventricular tachycardia

AbstractObjectivesThe purpose of this study was to analyze the feasibility, efficacy, and safety of epicardial radiofrequency (RF) ablation in patients with incessant ventricular tachycardia (VT).BackgroundManagement of patients with incessant VT is a difficult clinical problem. Drugs and RF catheter ablation are not always effective. A nonsurgical transthoracic epicardial RF ablation can be an alternative in patients refractory to conventional therapy.MethodsEpicardial RF ablation was performed in 10 patients who presented with incessant VT despite the use of two or more intravenous antiarrhythmic drugs.ResultsIn eight patients, endocardial ablation (EdA) failed to control the tachycardia. In the remaining two patients, epicardial ablation (EpA) was first attempted because of left ventricular thrombus and severe artery disease, respectively. Eight patients had a diagnosis of coronary artery disease with healed myocardial infarction. One patient had dilated cardiomyopathy, and one patient had idiopathic, incessant VT. In patients with structural heart disease, the mean ejection fraction was 0.28 ± 0.10%. Four patients previously received an implantable defibrillator. The EpA effectively terminated the incessant tachycardia in eight patients, which represents a success rate of 80%. In them, after a follow-up of 18 ± 18 months, a single episode of a different VT was documented in one patient. No significant complications occurred related to the procedure.ConclusionsIn patients with incessant VT despite the use of drugs or standard EdA, the epicardial approach was very effective and should be considered as an alternative in this life-threatening situation

Cardioneuroablation for vasovagal syncope: insights on patients' selection, centre settings, procedural workflow and endpoints-results from an European Heart Rhythm Association survey.

AIMS Cardioneuroablation (CNA) is a catheter-based intervention for recurrent vasovagal syncope (VVS) that consists in the modulation of the parasympathetic cardiac autonomic nervous system. This survey aims to provide a comprehensive overview of current CNA utilization in Europe. METHODS AND RESULTS A total of 202 participants from 40 different countries replied to the survey. Half of the respondents have performed a CNA during the last 12 months, reflecting that it is considered a treatment option of a subset of patients. Seventy-one per cent of respondents adopt an approach targeting ganglionated plexuses (GPs) systematically in both the right atrium (RA) and left atrium (LA). The second most common strategy (16%) involves LA GP ablation only after no response following RA ablation. The procedural endpoint is frequently an increase in heart rate. Ganglionated plexus localization predominantly relies on an anatomical approach (90%) and electrogram analysis (59%). Less utilized methods include pre-procedural imaging (20%), high-frequency stimulation (17%), and spectral analysis (10%). Post-CNA, anticoagulation or antiplatelet therapy is prescribed, with only 11% of the respondents discharging patients without such medication. Cardioneuroablation is perceived as effective (80% of respondents) and safe (71% estimated <1% rate of procedure-related complications). Half view CNA emerging as a first-line therapy in the near future. CONCLUSION This survey offers a snapshot of the current implementation of CNA in Europe. The results show high expectations for the future of CNA, but important heterogeneity exists regarding indications, procedural workflow, and endpoints of CNA. Ongoing efforts are essential to standardize procedural protocols and peri-procedural patient management

Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation

The left atrium (LA) can change in size and shape due to atrial fibrillation (AF)-induced remodeling. These alterations can be linked to poorer outcomes of AF ablation. In this study, we propose a novel comprehensive computational analysis of LA anatomy to identify what features of LA shape can optimally predict post-ablation AF recurrence. To this end, we construct smooth 3D geometrical models from the segmentation of the LA blood pool captured in pre-procedural MR images. We first apply this methodology to characterize the LA anatomy of 144 AF patients and build a statistical shape model that includes the most salient variations in shape across this cohort. We then perform a discriminant analysis to optimally distinguish between recurrent and non-recurrent patients. From this analysis, we propose a new shape metric called vertical asymmetry, which measures the imbalance of size along the anterior to posterior direction between the superior and inferior left atrial hemispheres. Vertical asymmetry was found, in combination with LA sphericity, to be the best predictor of post-ablation recurrence at both 12 and 24 months (area under the ROC curve: 0.71 and 0.68, respectively) outperforming other shape markers and any of their combinations. We also found that model-derived shape metrics, such as the anterior-posterior radius, were better predictors than equivalent metrics taken directly from MRI or echocardiography, suggesting that the proposed approach leads to a reduction of the impact of data artifacts and noise. This novel methodology contributes to an improved characterization of LA organ remodeling and the reported findings have the potential to improve patient selection and risk stratification for catheter ablations in AF

Training machine learning models with synthetic data improves the prediction of ventricular origin in outflow tract ventricular arrhythmias

In order to determine the site of origin (SOO) in outflow tract ventricular arrhythmias (OTVAs) before an ablation procedure, several algorithms based on manual identification of electrocardiogram (ECG) features, have been developed. However, the reported accuracy decreases when tested with different datasets. Machine learning algorithms can automatize the process and improve generalization, but their performance is hampered by the lack of large enough OTVA databases. We propose the use of detailed electrophysiological simulations of OTVAs to train a machine learning classification model to predict the ventricular origin of the SOO of ectopic beats. We generated a synthetic database of 12-lead ECGs (2,496 signals) by running multiple simulations from the most typical OTVA SOO in 16 patient-specific geometries. Two types of input data were considered in the classification, raw and feature ECG signals. From the simulated raw 12-lead ECG, we analyzed the contribution of each lead in the predictions, keeping the best ones for the training process. For feature-based analysis, we used entropy-based methods to rank the obtained features. A cross-validation process was included to evaluate the machine learning model. Following, two clinical OTVA databases from different hospitals, including ECGs from 365 patients, were used as test-sets to assess the generalization of the proposed approach. The results show that V2 was the best lead for classification. Prediction of the SOO in OTVA, using both raw signals or features for classification, presented high accuracy values (>0.96). Generalization of the network trained on simulated data was good for both patient datasets (accuracy of 0.86 and 0.84, respectively) and presented better values than using exclusively real ECGs for classification (accuracy of 0.84 and 0.76 for each dataset). The use of simulated ECG data for training machine learning-based classification algorithms is critical to obtain good SOO predictions in OTVA compared to real data alone. The fast implementation and generalization of the proposed methodology may contribute towards its application to a clinical routine