Europace最新文献

Aims: We report our single-centre experience of mid-term to long-term retrieval and reimplantation of a tine-based leadless pacemaker [Micra transcatheter pacing system (TPS)]. The TPS is a clinically effective alternative to transvenous single-chamber ventricular pacemakers. Whereas it is currently recommended to abandon the TPS at the end of device life, catheter-based retrieval may be favourable in specific scenarios.

Methods and results: We report on nine consecutive patients with the implanted TPS who subsequently underwent transcatheter retrieval attempts. The retrieval system consists of the original TPS delivery catheter and an off-the-shelf single-loop 7 mm snare. The procedure was guided by fluoroscopy and intracardiac echocardiography. After an implantation duration of 3.1 ± 2.8 years (range 0.4-9.0), the overall retrieval success rate was 88.9% (8 of 9 patients). The mean procedure time was 89 ± 16 min, and the fluoroscopy time was 18.0 ± 6.6 min. No procedure-related adverse device events occurred. In the one unsuccessful retrieval, intracardiac echocardiography revealed that the TPS was partially embedded in the ventricular tissue surrounding the leadless pacemaker body in the right ventricle. After retrieval, three patients were reimplanted with a new TPS device. All implantations were successful without complications.

Conclusion: A series of transvenous late retrievals of implanted TPS devices demonstrated safety and feasibility, followed by elective replacement with a new leadless pacing device or conventional transvenous pacing system. This provides a viable end-of-life management alternative to simple abandonment of this leadless pacemaker.

Aims: The effective refractory period (ERP) is one of the main electrophysiological properties governing arrhythmia, yet ERP personalization is rarely performed when creating patient-specific computer models of the atria to inform clinical decision-making. This study evaluates the impact of integrating clinical ERP measurements into personalized in silico models on arrhythmia vulnerability.

Methods and results: Clinical ERP measurements were obtained in seven patients from multiple locations in the atria. Atrial geometries from the electroanatomical mapping system were used to generate personalized anatomical atrial models. The Courtemanche M. et al. cellular model was adjusted to reproduce patient-specific ERP. Four modeling approaches were compared: homogeneous (A), heterogeneous (B), regional (C), and continuous (D) ERP distributions. Non-personalized approaches (A and B) were based on literature data, while personalized approaches (C and D) were based on patient measurements. Modeling effects were assessed on arrhythmia vulnerability and tachycardia cycle length, with sensitivity analysis on ERP measurement uncertainty. Mean vulnerability was 3.4 ± 4.0%, 7.7 ± 3.4%, 9.0 ± 5.1%, and 7.0 ± 3.6% for scenarios A-D, respectively. Mean tachycardia cycle length was 167.1 ± 12.6 ms, 158.4 ± 27.5 ms, 265.2 ± 39.9 ms, and 285.9 ± 77.3 ms for scenarios A-D, respectively. Incorporating perturbations to the measured ERP in the range of 2, 5, 10, 20, and 50 ms changed the vulnerability of the model to 5.8 ± 2.7%, 6.1 ± 3.5%, 6.9 ± 3.7%, 5.2 ± 3.5%, and 9.7 ± 10.0%, respectively.

Conclusion: Increased ERP dispersion had a greater effect on re-entry dynamics than on vulnerability. Inducibility was higher in personalized scenarios compared with scenarios with uniformly reduced ERP; however, this effect was reversed when incorporating fibrosis informed by low-voltage areas. Effective refractory period measurement uncertainty up to 20 ms slightly influenced vulnerability. Electrophysiological personalization of atrial in silico models appears essential and requires confirmation in larger cohorts.

Aims: Sports-related physical activity is associated with an increased risk of ventricular dysfunction and arrhythmias in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC). However, there are currently no standardized strategies for activity assessment. Thresholds for harmful levels of physical activity suggested by previous studies vary substantially and neither lifetime activity burden nor continuous modelling approaches were considered.

Methods and results: For this single-centre retrospective study, ARVC patients were interviewed to assess sports-related and non-sports-related physical activity between the age of 10 years and the last follow-up. Activity data were aggregated to the median metabolic equivalent of task-hours (METh) per week for each year. The association between cumulative physical activity burden and clinical study endpoints was investigated using Cox regression models. A total of 124 patients (median age: 39.5 years, 48% male) were included in the analysis, of whom 93 had been diagnosed with definite ARVC. Study participants reported a median overall activity of 202.3 METh/week, with 38.7 METh/week attributed to sports-related activity. In the continuous model, cumulative overall activity burden was associated with the occurrence of symptomatic heart failure [hazard ratio (HR) per 100 METh/week: 1.017, 95% CI (1.003, 1.032), P = 0.015], sustained ventricular tachycardia [HR: 1.021, 95% CI (1.006, 1.037), P = 0.007], and implantable cardioverter defibrillator interventions [HR: 1.017, 95%CI (1.000, 1.034), P = 0.048]. This finding was consistent when considering sports-related activity separately as a predictor variable, whereas the resulting hazard ratios did not show a significant association for non-sports-related physical activity.

Conclusion: This study demonstrates for the first time that cumulative physical activity as a continuous predictor variable is associated with symptomatic heart failure and arrhythmic risk in ARVC patients. Collaborative research is required in larger cohorts to investigate the influence of potential confounders on event occurrence and to develop threshold recommendations for clinical practice.

Aims: Achieving acute and durable mitral isthmus (MI) block remains challenging using radiofrequency (RF) catheter ablation alone. Vein of Marshall (VoM) ethanolization results in chemical damage along the MI resulting in the creation of a durable transmural lesion with a very high rate of procedural block. However, no studies have systematically assessed the efficacy of MI ablation alone when no anatomical VoM is present.

Methods and results: Thirty seven patients without VoM evidenced after careful angiographic examination were included. Ablation parameters and result were compared with a matched control group in whom the posterior MI line was performed without assessing the presence of the VoM. Mitral isthmus block was achieved in 36 out of 37 patients without VoM (97%), with endocardial ablation only in 5/37 (14%) and combined endocardial and coronary sinus ablation in 32/37 patients (86%). There was a significant difference in the occurrence of block between patients without a VoM and the control group (97.3% vs. 65% respectively, P < 0.01), with a trend towards less needed RF {26 [interquartile range (IQR) 20-38] vs. 29 [IQR 19-40] tags [P = 0.8], 611 [IQR 443-805] vs. 746 [IQR 484-1193] seconds [P = 0.08]}.

Conclusion: The absence of a VoM is associated with a very high rate of procedural block during posterior MI ablation. The higher rate of MI block in this specific population would also suggest the crucial role of the VoM (when present) in resistant MI block.

Aims: Reduction of atrial fibrillation (AF) burden is the preferred outcome measure over categorical AF rhythm recurrence after AF ablation. In this sub-analysis of the TeleCheck-AF project, we tested the feasibility of smartphone app-based approximation of time spent with AF and/or symptoms.

Methods and results: Patients scheduled for at least one teleconsultation during the 12-month follow-up after AF ablation were instructed to use a smartphone photoplethysmography-based application for simultaneous symptom and rhythm monitoring three times daily for 1 week. Proxies of time spent with AF and/or symptoms (% recordings, load, and % days), temporal aggregation of AF and/or symptoms (density), and symptom-rhythm correlation (SRC) were assessed. In total, 484 patients (60% male, 62 ± 9.9 years) were included. Adherence, motivation, and patient satisfaction were high. %AF recordings, AF load, and %AF days (rs = 0.88-0.95) and %symptom recordings, symptom load, and %symptom days (rs = 0.95-0.98) showed positive correlations. The SRC correlated negatively with time spent with symptoms (rs = -0.65-0.90) and with time spent with AF (rs = -0.31-0.34). In patients with paroxysmal AF before ablation and AF during the monitoring period, 87% (n = 39/44) had a low-density score <50% ('paroxysmal AF pattern') while 5% (n = 2/44) had a high-density score >90% ('persistent AF pattern'). Corresponding numbers for patients with persistent AF before ablation were 48% (n = 11/23) and 43% (n = 10/23), respectively.

Conclusion: On-demand, app-based simultaneous rhythm and symptom assessment provides objective proxies of time spent with AF and/or symptoms and SRC, which may assist in assessing AF and symptom outcomes after AF ablation.

Aims: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been linked to cardiovascular complications, notably cardiac arrhythmias. The open reading frame (ORF) 3a of the coronavirus genome encodes for a transmembrane protein that can function as an ion channel. The aim of this study was to investigate the role of the SARS-CoV-2 ORF 3a protein in COVID-19-associated arrhythmias and its potential as a pharmacological target.

Methods and results: Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) and cultured human fibroblasts were infected with SARS-CoV-2. Subsequent immunoblotting assays revealed the expression of ORF 3a protein in hiPSC-CM but not in fibroblasts. After intracytoplasmic injection of RNA encoding ORF 3a proteins into Xenopus laevis oocytes, macroscopic outward currents could be measured. While class I, II, and IV antiarrhythmic drugs showed minor effects on ORF 3a-mediated currents, a robust inhibition was detected after application of class III antiarrhythmics. The strongest effects were observed with dofetilide and amiodarone. Finally, molecular docking simulations and mutagenesis studies identified key amino acid residues involved in drug binding.

Conclusion: Class III antiarrhythmic drugs are potential inhibitors of ORF 3a-mediated currents, offering new options for the treatment of COVID-19-related cardiac complications.

Aims: Pathophysiology of atrial fibrillation (AF) remains unclear. Interactions between scar and conduction velocity (CV) and their impact on wavefront propagation in sinus rhythm (SR) and rotational activity burden in AF were evaluated.

Methods and results: Local activation times (LATs) and voltage data were obtained from patients undergoing ablation for persistent AF. Omnipolar voltage (OV) and bipolar voltage (BV) data were obtained during AF and SR at pacing intervals of 600 and 250 ms. Local activation times were used to determine CV dynamics and their relationship to the underlying voltage and pivot points in SR. Computational modelling studies were performed to evaluate the impact of CVs and fibrosis on rotational activity burden in AF. Data from 60 patients with a total of 2 768 400 LAT and voltage points were analysed (46 140 ± 5689 points/patient). Voltage determined CV dynamics. Enhanced CV heterogeneity sites were predominantly mapped to low-voltage zones (LVZs) (0.2-0.49 mV) (128/168, 76.2%) rather than LVZs (<0.2 mV) and frequently co-located to pivot points (151/168, 89.9%). Atrial fibrillation OV maps correlated better with SR BV 250 ms than 600 ms maps, thereby representing fixed and functional remodelling. Sinus rhythm maps at 250 ms compared with 600 ms harboured a greater number of pivot points. Increased CV slowing and functional remodelling on computational models resulted in a greater rotational activity burden.

Conclusion: Conduction velocity dynamics are impacted by the degree of scar. Conduction velocity heterogeneity and functional remodelling impacts wavefront propagation in SR and rotational activity burden in AF. This study provides insight into the pathophysiology of AF and identifies potential novel ablation targets.

Aims: Physical activity has shown association with ventricular arrhythmia, however, the role of specific behavioral patterns over a 24 h cycle remains unknown. Therefore, we aimed to explore associations between physical behavior and appropriate implantable cardioverter defibrillator (ICD) therapy.

Methods and results: We included patients with an ICD at two European sites, who wore wrist-based accelerometers capturing 24 h movement and sleep behaviours for 28 days. Behavioural measures included activity volume, duration and intensity, sleep duration, and efficiency. Participants were followed for 12 months for the outcome of appropriate ICD therapy. Cox proportional hazard models with restricted cubic splines were used for the analysis. Lastly, the predictive capacity was tested. A total of 253 ICD patients were included (mean age 63.5 (±10.2), 48 (19.0%) female). During follow-up, 40 participants (15.8%) received appropriate ICD therapy; 32 anti-tachycardia pacing (ATP) only (12.6%), 5 shock only (2.0%), and 3 combined ATP and shock (1.2%). In the adjusted model, high inactive duration (HR 1.40 (95% 1.10-1.78)), peak walking cadence (HR 1.07 (95% 1.03-1.12)), and total sleep duration (HR 1.50 (1.02-2.22)) were associated with the outcome. The dose-response relationship was U-shaped for inactive duration with a cut-off at 16 h, and linear for peak cadence and sleep. The prediction model reached an area under the receiver operating characteristic curve of 0.70 ± 0.03, with highest accuracy in the first months.

Conclusion: Wearable-derived 24 h movement and sleep behaviours collected over 28 days were associated with later appropriate ICD therapy risk. Testing of the predictive value of digital biomarkers for enhanced risk stratification of ventricular arrhythmia warrants larger prospective studies.

Clinical trial registration: National Trial Registration (NL9218, http://onderzoekmetmensen.nl/).