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

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

Efficient preclinical treatment of cortical T cell acute lymphoblastic leukemia with T lymphocytes secreting anti-CD1a T cell engagers

BACKGROUND: The dismal clinical outcome of relapsed/refractory (R/R) T cell acute lymphoblastic leukemia (T-ALL) highlights the need for innovative targeted therapies. Although chimeric antigen receptor (CAR)-engineered T cells have revolutionized the treatment of B cell malignancies, their clinical implementation in T-ALL is in its infancy. CD1a represents a safe target for cortical T-ALL (coT-ALL) patients, and fratricide-resistant CD1a-directed CAR T cells have been preclinically validated as an immunotherapeutic strategy for R/R coT-ALL. Nonetheless, T-ALL relapses are commonly very aggressive and hyperleukocytic, posing a challenge to recover sufficient non-leukemic effector T cells from leukapheresis in R/R T-ALL patients. METHODS: We carried out a comprehensive study using robust in vitro and in vivo assays comparing the efficacy of engineered T cells either expressing a second-generation CD1a-CAR or secreting CD1a x CD3 T cell-engaging Antibodies (CD1a-STAb). RESULTS: We show that CD1a-T cell engagers bind to cell surface expressed CD1a and CD3 and induce specific T cell activation. Recruitment of bystander T cells endows CD1a-STAbs with an enhanced in vitro cytotoxicity than CD1a-CAR T cells at lower effector:target ratios. CD1a-STAb T cells are as effective as CD1a-CAR T cells in cutting-edge in vivo T-ALL patient-derived xenograft models. CONCLUSIONS: Our data suggest that CD1a-STAb T cells could be an alternative to CD1a-CAR T cells in coT-ALL patients with aggressive and hyperleukocytic relapses with limited numbers of non-leukemic effector T cellsResearch in LA-V laboratory is funded by the Spanish Ministry of Science and Innovation (PID2020-117323RB-100 and PDC2021-121711-100), and the Carlos III Health Institute (DTS20/00089), with European Regional Development Fund (FEDER) cofinancing; the Spanish Association Against Cancer (AECC PROYE19084ALVA) and the CRIS Cancer Foundation (FCRIS-2018-0042 and FCRIS2021-0090). Research in PM laboratory is supported by CERCA/Generalitat de Catalunya and Fundació Josep Carreras-Obra Social la Caixa for core support; 'la Caixa' Foundation under the agreement LCF/PR/HR19/52160011; the European Research Council grant (ERC-PoC-957466); the Spanish Ministry of Science and Innovation (PID2019-108160RB-I00); and the ISCIII-RICORS within the Next Generation EU program (plan de Recuperación, Transformación y Resilencia). MLT is supported by Spanish Ministry of Science and Innovation (PID2019-105623RB-I00) and the Spanish Association Against Cancer (CICPF18030TORI). PP is supported by Carlos III Health Institute (PI21-01834), with FEDER cofinancing and Fundación Ramón Areces. NT was supported by an FPU PhD fellowship from Spain's Ministerio de Universidades (FPU19/00039). OH was supported by an industrial PhD fellowship from the Comunidad de Madrid (IND2020/BMD-17668). LD-A was supported by a Rio Hortega fellowship from the Carlos III Health Institute (CM20/00004). VMD is supported by the Torres Quevedo subprogram of the State Research Agency of the Ministry of Science, Innovation and Universities (Ref. PTQ2020-011056). DSM is partially founded by a Sara Borrell fellowship from Carlos III Health Institute (CD19/00013

Clinical impact of aging on outcomes of cardioneuroablation for reflex syncope or functional bradycardia. Results from the cardionEuroabLation: patiEnt selection, imaGe integrAtioN and outComEs. The ELEGANCE multicenter study

Background: Cardioneuroablation (CNA) is a novel treatment for reflex syncope. The effect of aging on CNA efficacy is not fully understood. Objective: We assessed the impact of aging on candidacy and efficacy of CNA for treating vasovagal syncope (VVS), carotid sinus syndrome (CSS) and functional bradyarrhythmia. Methods: The ELEGANCE multicenter study assessed CNA in patients with reflex syncope or severe functional bradyarrhythmia. Patients underwent pre-CNA Holter ECG, head-up tilt testing (HUT) and electrophysiologic study. CNA candidacy and efficacy was assessed in 14 young (18-40 years), 26 middle-aged (41-60 years) and 20 older (&gt;60 years) patients. Results: Sixty patients (37 men; mean age: 51±16 years) underwent CNA. The majority (80%) had VVS, 8% CSS, and 12% functional bradycardia/AV block. Pre-CNA Holter ECG, HUT and EP findings did not differ across age groups. Acute CNA success was 93%, without differences between age groups (p=0.42). Post-CNA HUT response was negative in 53%, vasodepressor in 38%, cardioinhibitory in 7% and mixed in 2%, without differences across age groups (p=0.59). At follow-up (8 months, IQR:4-15), 53 (88%) patients were free of symptoms. Kaplan-Meier curves did not show differences in event-free survival between age groups (p=0.29). The negative predictive value of a negative HUT was 91.7%. Conclusions: CNA is a viable treatment for reflex syncope and functional bradyarrhythmia in all ages, and is highly effective in mixed VVS. HUT is a key-step of post-ablation clinical assessment

Automatic and interpretable prediction of the site of origin in outflow tract ventricular arrhythmias: machine learning integrating electrocardiograms and clinical data

The treatment of outflow tract ventricular arrhythmias (OTVA) through radiofrequency ablation requires the precise identification of the site of origin (SOO). Pinpointing the SOO enhances the likelihood of a successful procedure, reducing intervention times and recurrence rates. Current clinical methods to identify the SOO are based on qualitative analysis of pre-operative electrocardiograms (ECG), heavily relying on physician’s expertise. Although computational models and machine learning (ML) approaches have been proposed to assist OTVA procedures, they either consume substantial time, lack interpretability or do not use clinical information. Here, we propose an alternative strategy for automatically predicting the ventricular origin of OTVA patients using ML. Our objective was to classify ventricular (left/right) origin in the outflow tracts (LVOT and RVOT, respectively), integrating ECG and clinical data from each patient. Extending beyond differentiating ventricle origin, we explored specific SOO characterization. Utilizing four databases, we also trained supervised learning models on the QRS complexes of the ECGs, clinical data, and their combinations. The best model achieved an accuracy of 89%, highlighting the significance of precordial leads V1-V4, especially in the R/S transition and initiation of the QRS complex in V2. Unsupervised analysis revealed that some origins tended to group closer than others, e.g., right coronary cusp (RCC) with a less sparse group than the aortic cusp origins, suggesting identifiable patterns for specific SOOs

Ablation of tachycardia in arrhythmogenic right ventricular dysplasia

La displasia arritmogénica del ventrículo derecho es una cardiopatía de origen genético, su importancia radica en la capacidad de generar muerte súbita en pacientes en la tercera y cuarta década de la vida, después de grandes esfuerzos por aumentar la sensibilidad y mejorar la capacidad diagnóstica continúa siendo un importante problema de salud pública. Los desfibriladores implantables han demostrado aumentar la supervivencia de quienes presentan arritmias letales asociadas, sin embargo, debido al carácter progresivo de la enfermedad un interrogante de importancia es cómo tratar a los pacientes con terapias apropiadas y frecuentes de estos dispositivos, la ablación por radiofrecuencia es una respuesta terapéutica seria a este dilema. En la actualidad disponemos de técnicas de ablación que combinan los métodos de la imagen TC cardiaca, la resonancia cardiaca, los mapas electroanatómicos y algunas herramientas de la electrofisiología convencional que permiten realizar ablaciones sin la inducción de arritmias ventriculares de forma sostenida y durante el ritmo sinusal, de modo similar el mejor entendimiento de la patogenia introdujo el uso de técnicas híbridas endo y epicárdica, la suma de cada uno de estos avances ha aumentado la tolerancia durante el procedimiento, ha mejorado los resultados en las etapas agudas postablación y en los seguimientos a mediano plazo, hoy los márgenes de seguridad y eficacia para esta técnica se incrementan, siendo de primera línea en diferentes situaciones de relevancia en esta compleja enfermedad.Arrhythmogenic right ventricular dysplasia (ARVD) is a genetic disease associated with sudden cardiac death, affecting subjects in the 3 rd and 4 th decade of life. Despite great efforts made in order to improve its early diagnosis, ARVD remains as a major public health problem in Europe and America. Currently, risk stratification of sudden cardiac death in patients with ARVD remains challenging. Over the last decade implantable defibrillators have been shown to increase survival of patients with structural heart disease and risk factors for sudden cardiac death. However, there is no consensus about how to treat patients with recurrent appropriate implantable defibrillators therapies. Recent studies have shown that radiofrequency ablation is an effective treatment for patients with recurrent episodes of ventricular tachycardia. Specifically, substrate ablation techniques have been shown to be especially useful in the case of ARVD, as these techniques allow performing ablation during sinus rhythm. Additionally, emerging tools as electroanatomic navigation, CT or MRI have provided further knowledge of the pathogenesis of ARVD, allowing the development of novel therapeutic approaches. In this review epidemiologic, pathogenic, diagnostic and therapeutic features of ARVD are discussed, with special focus on the treatment of ventricular arrhythmias associated with ARVD

Cardioneuroablation for carotid sinus syndrome: a case series

Cardioinhibitory carotid sinus syndrome (CSS) is a neurally mediated (reflex) syncope, secondary to excessive vagal response to carotid sinus pressure. A growing body of studies have shown that catheter ablation of ganglionated plexi (GPs) or cardioneuroablation (CNA) is effective in treating patients with vasovagal syncope.1 To date, no studies systematically evaluated CNA in patients with CSS

Dyssynchronization reduces dynamic obstruction without affecting systolic function in patients with hypertrophic obstructive cardiomyopathy: a pilot study

status: publishe

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.This work has been funded by Generalitat Valenciana Grant AICO/2021/318 (Consolidables 2021) and Grant PID2020-114291RB-I00 funded by MCIN/10.13039/501100011033 and by “ERDF A way of making Europe”