Background The use of intra-cardiac electrograms to guide atrial fibrillation (AF) ablation has yielded conflicting results. We evaluated an electrogram marker of AF drivers: the clustering of electrograms exhibiting spatio-temporal dispersion — regardless of whether such electrograms were fractionated or not. Objective To evaluate the usefulness of spatio-temporal dispersion, a visually recognizable electric footprint of AF drivers, for the ablation of all forms of AF. Methods We prospectively enrolled 105 patients admitted for AF ablation. AF was sequentially mapped in both atria with a 20-pole PentaRay catheter. We tagged and ablated only regions displaying electrogram dispersion during AF. Results were compared to a validation set in which a conventional ablation approach was used (pulmonary vein isolation/stepwise approach). To establish the mechanism underlying spatio-temporal dispersion of AF electrograms, we conducted realistic numerical simulations of AF drivers in a 2-dimensional model and optical mapping of ovine atrial scar-related AF. Results Ablation at dispersion areas terminated AF in 95%. After ablation of 17±10% of the left atrial surface and 18 months of follow-up, the atrial arrhythmia recurrence rate was 15% after 1.4±0.5 procedure/patient vs 41% in the validation set after 1.5±0.5 procedure/patient (arrhythmia free-survival rates: 85% vs 59%, log rank P<0.001). In comparison with the validation set, radiofrequency times (49 ± 21 minutes vs 85 ± 34.5 minutes, p=0.001) and procedure times (168 ± 42 minutes vs. 230 ± 67 minutes, p<.0001) were shorter. In simulations and optical mapping experiments, virtual PentaRay recordings demonstrated that electrogram dispersion is mostly recorded in the vicinity of a driver. Conclusions The clustering of intra-cardiac electrograms exhibiting spatio-temporal dispersion is indicative of AF drivers. Their ablation allows for a non-extensive and patient-tailored approach to AF ablation. Clinical trial.gov number: NCT02093949
Self-taught axillary vein puncture for pacemaker implantation seems immediately safe and faster than cephalic vein access, when performed by electrophysiologists trained to pacemaker implantation but not to axillary vein puncture.
Association between Hydroxychloroquine (HCQ) and Azithromycin (AZT) is under evaluation for patients with lower respiratory tract infection (LRTI) caused by the Severe Acute Respiratory Syndrome (SARS-CoV-2). Both drugs have a known torsadogenic potential, but sparse data are available concerning QT prolongation induced by this association. Our objective was to assess for COVID-19 LRTI variations of QT interval under HCQ/AZT in patients hospitalized, and to compare manual versus automated QT measurements. Before therapy initiation, a baseline 12 lead-ECG was electronically sent to our cardiology department for automated and manual QT analysis (Bazett and Fridericia's correction), repeated 2 days after initiation. According to our institutional protocol (Pasteur University Hospital), HCQ/ AZT was initiated only if baseline QTc ≤ 480ms and potassium level> 4.0 mmol/L. From March 24 th to April 20 th 2020, 73 patients were included (mean age 62 ± 14 years, male 67%). Two patients out of 73 (2.7%) were not eligible for drug initiation (QTc ≥ 500 ms). Baseline average automated QTc was 415 ± 29 ms and lengthened to 438 ± 40 ms after 48 hours of combined therapy. The treatment had to be stopped because of significant QTc prolongation in two out of 71 patients (2.8%). No drug-induced life-threatening arrhythmia, nor death was observed. Automated QTc measurements revealed accurate in comparison with manual QTc measurements. In this specific population of inpatients with COVID-19 LRTI, HCQ/AZT could not be initiated or had to be interrupted in less than 6% of the cases.
Introduction Multiple groups have reported on the usefulness of ablating in atrial regions exhibiting abnormal electrograms during atrial fibrillation (AF). Still, previous studies have suggested that ablation outcomes are highly operator‐ and center‐dependent. This study sought to evaluate a novel machine learning software algorithm named VX1 (Volta Medical), trained to adjudicate multipolar electrogram dispersion. Methods This study was a prospective, multicentric, nonrandomized study conducted to assess the feasibility of generating VX1 dispersion maps. In 85 patients, 8 centers, and 17 operators, we compared the acute and long‐term outcomes after ablation in regions exhibiting dispersion between primary and satellite centers. We also compared outcomes to a control group in which dispersion‐guided ablation was performed visually by trained operators. Results The study population included 29% of long‐standing persistent AF. AF termination occurred in 92% and 83% of the patients in primary and satellite centers, respectively, p = 0.31. The average rate of freedom from documented AF, with or without antiarrhythmic drugs (AADs), was 86% after a single procedure, and 89% after an average of 1.3 procedures per patient (p = 0.4). The rate of freedom from any documented atrial arrhythmia, with or without AADs, was 54% and 73% after a single or an average of 1.3 procedures per patient, respectively (p < 0.001). No statistically significant differences between outcomes of the primary versus satellite centers were observed for one (p = 0.8) or multiple procedures (p = 0.4), or between outcomes of the entire study population versus the control group (p > 0.2). Interestingly, intraprocedural AF termination and type of recurrent arrhythmia (i.e., AF vs. AT) appear to be predictors of the subsequent clinical course. Conclusion VX1, an expertise‐based artificial intelligence software solution, allowed for robust center‐to‐center standardization of acute and long‐term ablation outcomes after electrogram‐based ablation.
Background: Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease, and sudden cardiac death represents an important mode of death in these patients. Data evaluating the implantable cardioverter defibrillator (ICD) in this patient population remain scarce. Methods: Nationwide French Registry including all TOF patients with an ICD initiated in 2010 by the French Institute of Health and Medical Research. The primary time to event endpoint was the time from ICD implantation to first appropriate ICD therapy. Secondary outcomes included ICD-related complications, heart transplantation, and death. Clinical events were centrally adjudicated by a blinded committee. Results: A total of 165 patients (mean age 42.2±13.3 years, 70.1% males) were included from 40 centers, including 104 (63.0%) in secondary prevention. During a median (IQR) follow-up of 6.8 (2.5-11.4) years, 78 (47.3%) patients received at least one appropriate ICD therapy. The annual incidence of the primary outcome was 10.5% (7.1% and 12.5% in primary and secondary prevention, respectively, p=0.03). Overall, 71 (43.0%) patients presented with at least one ICD complication, including inappropriate shocks in 42 (25.5%) patients and lead dysfunction in 36 (21.8%) patients. Among 61 (37.0%) primary prevention patients, the annual rate of appropriate ICD therapies was 4.1%, 5.3%, 9.5%, and 13.3% in patients with respectively no, one, two, or ≥ three guideline-recommended risk factors. QRS fragmentation was the only independent predictor of appropriate ICD therapies (HR 3.47, 95% CI 1.19-10.11), and its integration in a model with current criteria increased the 5-year time-dependent area under the curve from 0.68 to 0.81 (p=0.006). Patients with congestive heart failure and/or reduced LVEF had a higher risk of non-arrhythmic death or heart transplantation (HR=11.01, 95% CI: 2.96-40.95). Conclusions: Patients with TOF and an ICD experience high rates of appropriate therapies, including those implanted in primary prevention. The considerable long-term burden of ICD-related complications, however, underlines the need for careful candidate selection. A combination of easy-to-use criteria including QRS fragmentation might improve risk stratification. Clinical Trial Registration: URL: https://clinicaltrials.gov Unique Identifier: NCT03837574
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