Focus on atrial fibrillation: role of atrioventricular node ablation, prediction by deep learning, and anticoagulation in device-detected arrhythmia

For the podcast associated with this article, please visit https://academic.oup.com/eurheartj/pages/Podcasts. This Focus Issue on arrhythmias contains the State of the Art Review entitled ‘Atrioventricular node ablation for atrial fibrillation in the era of conduction system pacing’ by Jacqueline Joza from McGill University Health Center in Montreal, Quebec, Canada, and colleagues.1 The authors note that despite key advances in catheter-based treatments, the management of persistent atrial fibrillation (AF) remains a therapeutic challenge in a significant subset of patients. While success rates have improved with repeat AF ablation procedures and the concurrent use of antiarrhythmic drugs, the likelihood of maintaining sinus rhythm during long-term follow-up is still limited. Atrioventricular node ablation (AVNA) has returned as a valuable treatment option given the recent developments in cardiac pacing. With the advent of conduction system pacing, AVNA has seen a revival where pacing-induced cardiomyopathy after AVNA is felt to be overcome. This review discusses the role of permanent pacemaker implantation and AVNA for AF management in this new era of conduction system pacing. Specifically, this review discusses the haemodynamic consequences of AF and the mechanisms through which ‘pace-and-ablate therapy’ enhances outcomes, analyses historical and more recent literature across various pacing methods, and works to identify patient groups that may benefit from earlier implementation of this approach. Patients with overt AF and high stroke risk benefit from oral anticoagulants.2–7 In contrast, the optimal antithrombotic therapy in patients with device-detected AF (DDAF) is uncertain. In a Fast Track Congress article entitled ‘Anticoagulation in device-detected atrial fibrillation with or without vascular disease: a combined analysis of the NOAH-AFNET 6 and ARTESiA trials’, Renate Schnabel from the University Heart and Vascular Center Hamburg in Germany, and colleagues indicate that concomitant vascular disease can modify the benefits and risks of anticoagulation.8 These pre-specified analyses of the NOAH-AFNET 6 (n = 2534 patients) and ARTESiA (n = 4012 patients) trials compared anticoagulation with no anticoagulation in patients with DDAF with or without vascular disease, defined as prior stroke/transient ischaemic attack, and coronary or peripheral artery disease. Efficacy outcome was the primary outcomes of both trials, a composite of stroke, systemic arterial embolism, myocardial infarction, pulmonary embolism, or cardiovascular death. Safety outcomes were major bleeding or major bleeding and death. In patients with vascular disease (NOAH-AFNET 6, 56%; ARTESiA, 46%), the primary outcome occurred at 3.9%/patient-year with and 5.0%/patient-year without anticoagulation (NOAH-AFNET 6), and 3.2%/patient-year with and 4.4%/patient-year without anticoagulation (ARTESiA). Without vascular disease, outcomes were equal with and without anticoagulation (NOAH-AFNET 6, 2.7%/patient-year; ARTESiA, 2.3%/patient-year in both randomized groups). Meta-analysis found consistent results across both trials (I2heterogeneity = 6%) with a trend for interaction with randomized therapy (Pinteraction = .08). Anticoagulation equally increased major bleeding in vascular disease patients (edoxaban, 2.1%/patient-year; no anticoagulation, 1.3%/patient-year; apixaban, 1.7%/patient-year; no anticoagulation, 1.1%/patient-year; incidence rate ratio 1.55) and without vascular disease (edoxaban, 2.2%/patient-year; no anticoagulation, 0.6%/patient-year; apixaban, 1.4%/patient-year; no anticoagulation, 1.1%/patient-year; incidence rate ratio 1.93) (Figure 1). Summary of findings in the NOAH-AFNET 6 and ARTESiA subanalysis and meta-analysis in patients with and without vascular disease. Orange and blue curves are NOAH-AFNET 6 data with (orange) and without (blue) anticoagulation; red and black curves are ARTESiA data with (black) and without (red) anticoagulation. CV, cardiovascular; DDAF, device-detected atrial fibrillation; DOAC, direct oral anticoagulant; MI, myocardial infarction; OAC, oral anticoagulation; PE, pulmonary embolism; SE, systemic arterial embolism; TIA, transient ischaemic attack.8 The authors conclude that patients with DDAF and vascular disease are at higher risk of stroke and cardiovascular events, and may derive a greater benefit from anticoagulation than patients with DDAF without vascular disease. The contribution is accompanied by an Editorial by Dominik Linz and Sevasti-Maria Chaldoupi from Maastricht University in the Netherlands.9 The authors note that in general, stroke risk in patients with DDAF and low AF burden is very low. However, in patients with DDAF and vascular disease, stroke prevalence is higher. Conceptually, AF-related and non-AF-related stroke mechanisms should be considered as a continuum, which can help to approximate the patient's stroke risk and steer prevention and treatment strategies of the patient's unique risk factors to prevent strokes and progression of DDAF to clinical ECG-documented AF. Schnabel et al. showed, that the absence of vascular disease may help to identify patients with DDAF at low stroke risk who may not benefit from DOACs. Besides this, more and more emerging evidence on DDAF and the introduction of novel innovative biomarker- and digital health-based strategies may soon help to assess the full continuum of AF-related and non-AF-related stroke mechanisms to provide solid information on the benefit of anticoagulation in a substantial intermediate group. Until then, mainly shared decision-making and patient preferences will further inform our treatment decisions. Deep learning is generating growing interest.10–13 Deep learning applied to ECGs (ECG-AI) is an emerging approach for predicting AF or atrial flutter. In a Fast Track Congress article entitled ‘Prediction of incident atrial fibrillation using deep learning, clinical models, and polygenic scores’, Gilbert Jabbour from the Université de Montréal in Canada, and colleagues in this study introduce an ECG-AI model developed and tested at a tertiary cardiac centre, comparing its performance with clinical models and AF polygenic score (PGS).14 ECGs in sinus rhythm from the Montreal Heart Institute were analysed, excluding those from patients with pre-existing AF. The primary outcome was incident AF at 5 years. An ECG-AI model was developed by splitting patients into non-overlapping datasets: 70% for training, 10% for validation, and 20% for testing. The performance of ECG-AI, clinical models, and PGS was assessed in the test dataset. The ECG-AI model was externally validated in the Medical Information Mart for Intensive Care-IV hospital dataset. A total of ∼700 000 ECGs from about 145 000 patients were included. Mean age was 61 years, and 58% were male. The primary outcome was observed in 15% of patients, and the ECG-AI model showed an area under the receiver operating characteristic curve (AUC-ROC) of 0.78. In a subgroup analysis of 2301 patients, ECG-AI outperformed CHARGE-AF (AUC-ROC = 0.62) and PGS (AUC-ROC = 0.59). Adding PGS and CHARGE-AF to ECG-AI improved goodness of fit (likelihood ratio test P < .001), with minimal changes to the AUC-ROC (0.76–0.77). In the external validation cohort, ECG-AI model performance remained consistent (AUC-ROC = 0.77). Jabbour et al. conclude that ECG-AI provides an accurate tool to predict new-onset AF in a tertiary cardiac centre, surpassing clinical models and PGS. The contribution is accompanied by an Editorial by Shinwan Kany from the University Heart and Vascular Center Hamburg-Eppendorf in Germany, together with Patrick Ellinor and Shaan Khurshid from the Broad Institute of Harvard and the Massachusetts Institute of Technology in Cambridge, MA, USA.15 The authors highlight that overall, this important study by Jabbour et al. sets the stage to address several key questions in the field of AF risk estimation. First, we need more robust external validation to evaluate the performance of AF risk models in more diverse populations, including exploration of potential extensions to single-lead ECGs obtained using wearable devices. Second, we ought to define the additional value of incorporating even more data sources including contemporary biomarkers, imaging, and protein-based signatures. The increasing availability and accessibility of datasets including a wider breadth of data types will be critical to facilitate development of such models, as will emerging AI-based methods capable of combining disparate data types and modelling high-level interactions end to end. Third, and most importantly, we must perform prospective studies and clinical trials to define populations for whom AF screening and related preventive interventions, perhaps guided by multimodality AF risk stratification, improve outcomes. Ultimately, Jabbour and colleagues have added an important piece to the puzzle of AF risk, a puzzle which we must solve one piece at a time. Acute excessive alcohol intake may cause the holiday heart syndrome, characterized by cardiac arrhythmias including atrial fibrillation. In a Clinical Research article entitled ‘Acute alcohol consumption and arrhythmias in young adults: the MunichBREW II study’, Stefan Brunner from LMU Munich in Germany, and colleagues indicate that since underlying data are scarce, the study aimed to prospectively investigate the temporal course of occurring cardiac arrhythmias following binge drinking in young adults.16 A total of 202 volunteers planning acute alcohol consumption with expected peak breath alcohol concentrations (BACs) of ≥1.2 g/kg were enrolled. The study comprised 48 h ECG monitoring covering baseline (Hour 0), ‘drinking period’ (Hours 1–5), ‘recovery period’ (Hours 6–19), and two control periods corresponding to 24 h after the ‘drinking’ and ‘recovery periods’, respectively. Acute alcohol intake was monitored by BAC measurements during the ‘drinking period’. ECGs were analysed for mean heart rate, atrial tachycardia, premature atrial complexes, premature ventricular complexes (PVCs), and heart rate variability measures. Data revealed an increase in heart rate and an excess of atrial tachycardias with increasing alcohol intake. Heart rate variability analysis indicated an autonomic modulation with sympathetic activation during alcohol consumption and the subsequent ‘recovery period’, followed by parasympathetic predominance thereafter. Premature atrial complexes occurred significantly more frequently in the ‘control periods’, whereas PVCs were more frequent in the ‘drinking period’. Ten participants experienced notable arrhythmic episodes, including atrial fibrillation and ventricular tachycardias, primarily during the ‘recovery period’ (Figure 2). Acute alcohol consumption results in an increase of heart rate and an excess of atrial tachycardias during the ‘drinking period’. It modulates autonomic tone with sympathetic activation during alcohol consumption and the subsequent ‘recovery period’, followed by parasympathetic predominance thereafter. Clinically relevant cardiac arrhythmias occur primarily during the ‘recovery period’. AV, atrioventricular; BAC, breath alcohol concentration; ECG, electrocardiogram.16 Brunner et al. conclude that the study demonstrates the impact of binge drinking on heart rate alterations and increased atrial tachycardias during the ‘drinking period’, and the occurrence of clinically relevant arrhythmias during the ‘recovery period’, emphasizing the holiday heart syndrome as a health concern. This manuscript is accompanied by an Editorial by Nicole Evans and Aleksandr Voskoboinik from the Alfred Hospital in Melbourne, Australia.17 The authors note that great challenges exist in curbing excessive alcohol intake, which remains ubiquitous in Western societies. In fact, in a randomized trial demonstrating the benefits of alcohol abstinence on AF, 39% of (motivated) AF patients in the abstinence arm continued to drink and the study needed to be shortened from 12 to 6 months in order to achieve compliance. Binge drinking and alcohol excess remain a major public health concern around the world, and studies such as that by Brunner et al. are important in drawing awareness to the deleterious effects of acute alcohol excess. The optimal management of heart failure with preserved ejection fraction (HFpEF) remains challenging.18–22 Accelerated atrial pacing offers potential benefits for patients with HFpEF and AF, compared with standard lower rate pacing. In a Translational Research article entitled ‘Accelerated atrial pacing reduces left-heart filling pressure: a combined clinical–computational study’, Tim van Loon from Maastricht University in the Netherlands, and colleagues investigate the relationship between atrial pacing rate and left-heart filling pressure.23 Seventy-five consecutive patients undergoing catheter ablation for AF underwent assessment of mean left atrial pressure (mLAP) and atrioventricular (AV) conduction delay (PR interval) in sinus rhythm and accelerated atrial pacing with 10 bpm increments up to Wenckebach block. Computer simulations of a virtual HFpEF cohort complemented clinical observations and hypothesized on the modulating effects of AV coupling and atrial (dys)function. In the study cohort, 65% of patients had a high HFpEF likelihood, and 37% had an elevated mLAP at sinus rhythm. A median pacing rate of 100 significantly reduced mLAP from 12.8 mmHg to 10.4 mmHg (P < .001). Conversely, a higher median pacing rate of 130 bpm significantly increased mLAP to 14.7 mmHg (P < .05). The PR interval and, hence, AV conduction delay was prolonged incrementally with increasing pacing rates. Simulations corroborated these clinical findings, showing mLAP reduction at a moderately increased pacing rate and a subsequent increase at higher rates. Moreover, simulations suggested that mLAP reduction is optimized when AV conduction delay shortens with increasing rate. The authors conclude that accelerated pacing acutely reduces left-heart filling pressure in patients undergoing AF catheter ablation and in computer simulations with HFpEF features, suggesting it as a potential therapeutic strategy to alleviate congestion symptoms. Virtual HFpEF patient cohorts suggest that AV sequential pacing may further optimize this therapy's beneficial effects. The contribution is accompanied by an Editorial by Markus Meyer from the University of Minnesota in Minneapolis, MN, USA.24 Meyer confirms that small clinical studies are underway to confirm the efficacy of personalized accelerated physiological AV pacing, i.e. PACE HFpEF (NCT04546555) and FIRE HFpEF (NCT05839730), and larger randomized controlled trials are in preparation. It will be crucial to ascertain that accelerated pacing is safe and that the benefits are clear and sustained in order to justify the implantation of advanced pacemaker systems into patients with ‘normal’ heart rates. It is important not to extrapolate these benefits to legacy pacemaker systems, as it is well established that excessive ventricular pacing from standard lead locations can harm patients. Although the early results appear promising, more research, such as the study by van Loon et al., is needed to fill remaining knowledge gaps to help maximize the safety and efficacy of this emerging treatment modality. In a Rapid Communication article entitled ‘Overdrive pacing for ventricular fibrillation storm after myocardial infarction’, Jan Charton from the Hôpital Cardiologique Haut Lévêque in Pessac, France, and colleagues note that polymorphic ventricular arrhythmias (ventricular fibrillation and polymorphic ventricular tachycardia) are serious complications following myocardial infarction (MI).25 These arrhythmias should be recognized as a distinct arrhythmic entity with a specific pathophysiology, time course, and evolution, different from organized scar-related ventricular tachycardias. The authors retrospectively included patients from five French medical centres who presented post-MI arrhythmic storms between 2012 and 2023. Inclusion required an arrhythmic storm post-MI (<30 days) with attempted overdrive pacing. All patients experienced ventricular fibrillation or polymorphic ventricular tachycardia storms, triggered by short-coupled PVCs. No additional ECG parameters were required. Overdrive pacing was performed using a temporary transvenous pacing lead, a temporary external pacemaker with an active lead, or by reprogramming a previously implanted device. Fifty-one patients met inclusion criteria. Arrhythmic storms began 8 days (median) after MI diagnosis. Pacing was initiated after the failure of 2.8 ± 1.5 treatment regimens. Median electrical storm duration was 2.0 days. Mean overdrive pacing rate was 94.5 bpm and was maintained for 5.0 days (median). Eighteen patients were stimulated in AAI mode, 23 in VVI, and 10 in DDD. Overdrive pacing effectively suppressed recurrent arrhythmias, with no on-treatment recurrence in 47 patients (92%). After a median follow-up of 393 days, which included remote monitoring of 30 patients (59%), only one patient had ventricular arrhythmia recurrence, more than a year after the initial event. The authors conclude that overdrive pacing enables physicians to achieve acute control over arrhythmia recurrence and effectively ‘wait out the storm’ until recovery. This strategy limits the need for other invasive therapies, such as circulatory assistance or challenging emergency catheter ablation procedures. The issue is also complemented by two Discussion Forum contributions. In a commentary entitled ‘Utility of mineralocorticoid receptor antagonists in reducing burden of atrial fibrillation’, Thalys Sampaio Rodrigues and Han S. Lim from the University of Melbourne and Prashanthan Sanders from the University of Adelaide in Australia comment on the recent publication ‘Mineralocorticoid receptor antagonists for atrial fibrillation prevention: effective solution or empty promise?’ by Alireza Oraii from the McMaster University in Canada.26,27 Oraii et al. respond in a separate comment.28 The editors hope that this issue of the European Heart Journal will be of interest to its readers. Dr. Crea reports speaker fees from Abbott, Amgen, Astra Zeneca, BMS, Chiesi, Daiichi Sankyo, Menarini outside the submitted work. With thanks to Amelia Meier-Batschelet, Johanna Huggler, and Martin Meyer for help with compilation of this article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.