Irum Kotadia

Aims: The heterogeneity in response to catheter ablation amongst atrial fibrillation (AF) patients classified according to arrhythmia duration highlights the need for improved phenotyping. Multimodal assessment may better characterize the spectrum of pathophysiology present amongst patients classified as having paroxysmal or persistent AF. This study aimed to perform comprehensive multimodal pre-ablation phenotyping in patients undergoing AF ablation and evaluate associations with post-ablation arrhythmia recurrence, symptom burden, and bi-atrial substrate remodelling. Methods and results: In this multicentre prospective cohort study, 86 patients referred for first-time AF ablation (42% persistent AF) underwent pre-ablation phenotyping beyond usual care, incorporating patch-based ambulatory rhythm monitoring, atrial structural and functional MRI assessment, and formal symptom evaluation. Unsupervised K-means clustering was used to derive phenotypes. The primary outcome was 12-month arrhythmia recurrence; secondary analyses assessed symptom trajectories and bi-atrial substrate characteristics. Four AF phenotypes were identified. Arrhythmia recurrence occurred in 56.0%, 42.9%, 22.2%, and 19.0% of patients in Phenotypes 1–4, respectively (log-rank P = 0.032). Symptom trajectories differed across phenotypes, with the greatest improvements observed in Phenotypes 3 and 4. Exploratory electroanatomic mapping analyses demonstrated significant between-phenotype differences in bi-atrial bipolar voltage aligned with clinical trajectories. Importantly, phenotypes were not fully explained by conventional classification: Phenotype 2 experienced relatively high recurrence despite comprising predominantly paroxysmal AF patients whilst Phenotype 3 demonstrated favourable outcomes despite a high prevalence of persistent AF. Conclusion: Multimodal phenotyping identified distinct AF subgroups associated with differences in post-ablation recurrence, symptom trajectories, and electrophysiological substrate. This approach could improve pre-ablation risk stratification and shared decision-making. Registration: ClinicalTrials.gov Identifier: NCT05057507

Background: Embolic stroke of unknown source (ESUS) accounts for 1 in 6 ischemic strokes. Current guidelines do not recommend routine cardiac magnetic resonance (CMR) imaging in ESUS, and beyond the identification of cardioembolic sources, there are no data assessing new clinical findings from CMR in ESUS. This study aimed to assess the prevalence of new cardiac and noncardiac findings and to determine their impact on clinical care in patients with ESUS. Methods and Results: In this prospective, multicenter, observational study, CMR imaging was performed within 3 months of ESUS. All scans were reported according to standard clinical practice. A new clinical finding was defined as one not previously identified through prior clinical evaluation. A clinically significant finding was defined as one resulting in further investigation, follow‐up, or treatment. A change in patient care was defined as initiation of medical, interventional, surgical, or palliative care. From 102 patients recruited, 96 underwent CMR imaging. One or more new clinical findings were observed in 59 patients (61%). New findings were clinically significant in 48 (81%) of these patients. Of 40 patients with a new clinically significant cardiac finding, 21 (53%) experienced a change in care (medical therapy, n=15; interventional/surgical procedure, n=6). In 12 patients with a new clinically significant extracardiac finding, 6 (50%) experienced a change in care (medical therapy, n=4; palliative care, n=2). Conclusions: CMR imaging identifies new clinically significant cardiac and noncardiac findings in half of patients with recent ESUS. Advanced cardiovascular screening should be considered in patients with ESUS. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT04555538.

There is increasing evidence to suggest that atrial fibrillation is associated with a heightened risk of dementia. The mechanism of interaction is unclear. Atrial fibrillation-induced cerebral infarcts, hypoperfusion, systemic inflammation, and anticoagulant therapy-induced cerebral microbleeds, have been proposed to explain the link between these conditions. An understanding of the pathogenesis of atrial fibrillation-associated cognitive decline may enable the development of treatment strategies targeted towards the prevention of dementia in atrial fibrillation patients. The aim of this review is to explore the impact that existing atrial fibrillation treatment strategies may have on cognition and the putative mechanisms linking the two conditions. This review examines how components of the ‘Atrial Fibrillation Better Care pathway’ (stroke risk reduction, rhythm control, rate control, and risk factor management) may influence the trajectory of atrial fibrillation-associated cognitive decline. The requirements for further prospective studies to understand the mechanistic link between atrial fibrillation and dementia and to develop treatment strategies targeted towards the prevention of atrial fibrillation-associated cognitive decline, are highlighted.

Radiofrequency ablation (RFA) is a treatment used in the management of various arrhythmias including atrial fibrillation. Enhanced training for electrophysiologists through the use of physical simulators has a significant role in improving patient outcomes. The requirements for a high-fidelity simulator for cardiac RFA are challenging and not fully met by any research or commercial simulator at present. In this study, we have produced and evaluated a 3D-printed, bi-atrial model contained in a custom-made enclosure for RFA simulation using a new soft tissue-mimicking polymer, Layfomm-40, combined with thermochromic pigment and barium sulphate in an acrylic paint carrier. We evaluated the conductive properties of Layfomm-40, its sensitivity to RFA, and its visibility in X-ray imaging, and carried a full simulation of RFA in the cardiac catheterization laboratory by an electrophysiologist. We demonstrated that a patient-specific 3D-printed Layfomm-40 bi-atrial model coated with a custom thermochromic/barium sulphate paint was compatible with the CARTO3 electroanatomic mapping system and could be effectively imaged using X-ray fluoroscopy. We demonstrated the effective delivery and visualization of radiofrequency ablation lesions in this model. The simulator meets nearly all the requirements for high-fidelity physical simulation of RFA. The use of such simulators is likely to have impact on the training of electrophysiologists and the evaluation of novel RFA devices.

Background: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while patient-specific models in small cohorts primarily explain acute response to ablation. We aimed to predict long-term atrial fibrillation recurrence after ablation in large cohorts, by using machine learning to complement biophysical simulations by encoding more interindividual variability. Methods: Patient-specific models were constructed for 100 atrial fibrillation patients (43 paroxysmal, 41 persistent, and 16 long-standing persistent), undergoing first ablation. Patients were followed for 1 year using ambulatory ECG monitoring. Each patient-specific biophysical model combined differing fibrosis patterns, fiber orientation maps, electrical properties, and ablation patterns to capture uncertainty in atrial properties and to test the ability of the tissue to sustain fibrillation. These simulation stress tests of different model variants were postprocessed to calculate atrial fibrillation simulation metrics. Machine learning classifiers were trained to predict atrial fibrillation recurrence using features from the patient history, imaging, and atrial fibrillation simulation metrics. Results: We performed 1100 atrial fibrillation ablation simulations across 100 patient-specific models. Models based on simulation stress tests alone showed a maximum accuracy of 0.63 for predicting long-term fibrillation recurrence. Classifiers trained to history, imaging, and simulation stress tests (average 10-fold cross-validation area under the curve, 0.85±0.09; recall, 0.80±0.13; precision, 0.74±0.13) outperformed those trained to history and imaging (area under the curve, 0.66±0.17) or history alone (area under the curve, 0.61±0.14). Conclusion: A novel computational pipeline accurately predicted long-term atrial fibrillation recurrence in individual patients by combining outcome data with patient-specific acute simulation response. This technique could help to personalize selection for atrial fibrillation ablation.

Approximately one‐third of ischemic strokes are classified as cryptogenic strokes. The risk of stroke recurrence in these patients is significantly elevated with up to one‐third of patients with cryptogenic stroke experiencing a further stroke within 10 years. While anticoagulation is the mainstay of treatment for secondary stroke prevention in the context of documented atrial fibrillation (AF), it is estimated that up to 25% of patients with cryptogenic stroke have undiagnosed AF. Furthermore, the historical acceptance of a causal relationship between AF and stroke has recently come under scrutiny, with evidence to suggest that embolic stroke risk may be elevated even in the absence of documented atrial fibrillation attributable to the presence of electrical and structural changes constituting an atrial cardiomyopathy. More recently, the term embolic stroke of unknown source has garnered increasing interest as a subset of patients with cryptogenic stroke in whom a minimum set of diagnostic investigations has been performed, and a nonlacunar infarct highly suspicious of embolic etiology is suspected but in the absence of an identifiable secondary cause of stroke. The ongoing ARCADIA (Atrial Cardiopathy and Antithrombotic Drugs in Prevention After Cryptogenic Stroke) randomized trial and ATTICUS (Apixiban for Treatment of Embolic Stroke of Undetermined Source) study seek to further define this novel term. This review summarizes the relationship between AF, embolic stroke, and atrial cardiomyopathy and provides an overview of the clinical relevance of cardiac imaging, electrocardiographic, and serum biomarkers in the assessment of AF and secondary stroke risk. The implications of these findings on therapeutic considerations is considered and gaps in the literature identified as areas for future study in risk stratifying this cohort of patients.