Citations 2
Stroke and systemic embolism following atrial fibrillation ablation: the EMBOL-AF Global Registry
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European Heart Journal | March 31, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Background and Aims Stroke and systemic embolism are recognized but poorly characterized complications of atrial fibrillation (AF) and left atrial flutter (AFL) catheter ablation. Their incidence, outcomes, and procedural associations remain insufficiently defined. Methods Retrospective global registry was initiated by the European Heart Rhythm Association Scientific Committee. A secure database captured data from ablation centres worldwide on general AF and left AFL ablation activity, as well as detailed information on patients with symptomatic embolic events between 2017 and 2024. Results Overall, 204 centres reported 335 743 ablation procedures and 550 embolic events (incidence 0.16%). Centre-level rate ranged from 0% to 3.1%. Most events were cerebral (94%), followed by peripheral (5%), and combined (1%). Coronary air embolism accounted for 62% of all peripheral events. Intraprocedural events occurred in 93 patients (17%), within 72 h in 357 (78%) and beyond 72 h in 100 (22%); 128 cases (23%) were diagnosed after hospital discharge. Nonparoxysmal AF (0.23% vs 0.15%; P < .001), centre experience, and ablation energy source (radiofrequency, 0.16%; cryoballoon, 0.16%; pulsed field ablation, 0.25%; laserballoon, 0.88%; P < .001) were associated with embolic risk. Median NIHSS score after stroke was 4 (interquartile range, 2–9). Three-month follow-up was available for 518 patients with embolism (95%): 181 (35%) had sequelae and 16 (3%) died. Conclusions Symptomatic embolic events are infrequent but associated with significant morbidity and mortality. Most events occur early, though a substantial proportion arise later. Higher event rates were observed with laser and possibly with pulsed field ablation. A greater centre experience was associated with a lower embolism incidence.
The hope and the hype of artificial intelligence for syncope management
Johnston, Samuel L. , Barsotti, Ercole John , Fedorowski, Artur , Ricci, Fabrizio , Heller, Eric G, Sheldon, Robert S. , Sutton, Richard , Shen, Win‐Kuang , Thiruganasambandamoorthy, Venkatesh , Adhaduk, Mehul , Parker, William H. , Aburizik, Arwa , Haselton, Corey R, Cuskey, Alex J, Johansson, Madeleine , Dominic, Paari , Rao, B. Hygriv , Mudireddy, Avinash , Statz, Giselle M., Benditt, David G. , Gatti, Mauro , Menè, Roberto , Shiffer, Dana , Vassilikos, Vassilios , Bakogiannis, Constantinos , Fedorowski, Artur , Ricci, Fabrizio , Sheldon, Robert , Sutton, Richard , Shen, Win-Kuang , Thiruganasambandamoorthy, Venkatesh , Adhaduk, Mehul , Parker, William H , Aburizik, Arwa , Lee, Sangil , Johansson, Madeleine , Macfarlane, Donald , Dominic, Paari , Abe, Haruhiko , Rao, B Hygriv , Mudireddy, Avinash , Sonka, Milan , Sandhu, Roopinder K , Kenny, Rose Anne , Gopinathannair, Rakesh , Benditt, David , Dipaola, Franca , Gatti, Mauro , Giaj Levra, Alessandro , Furlan, Raffaello , Ruwald, Martin H , Vassilikos, Vassilios , Gebska, Milena A , Olshansky, Brian , Cuskey, Alex, Lee, Sangil , Kenny, Rose Anne , Gopinathannair, Rakesh , Dipaola, Franca , Costantino, Giorgio , Furlan, Raffaello , Olshansky, Brian
European Heart Journal - Digital Health | June 25, 2025 | Volume: 6 | Issue: 5 | Pages: 1046-1054
Abstract Aims Syncope remains a diagnostic challenge despite advancements in testing and treatment. Cardiac syncope is an independent predictor of mortality and can be difficult to distinguish from other causes of transient loss of consciousness (TLOC). This paper explores whether artificial intelligence (AI) can improve the evaluation and management of patients with syncope. Methods and results We conducted a literature review and incorporated the opinions of experts in the fields of syncope and AI. The cause of TLOC is often unclear, hospitalization criteria are ambiguous, diagnostic tests are frequently non-informative, and assessments are costly. Patients are left with unanswered questions and limited guidance. Artificial intelligence (AI) has the potential to optimize syncope evaluation by processing large data sets, detecting imperceptible patterns, and assisting clinicians. However, AI has limitations, including errors, lack of human empathy, and uncertain clinical utility. Liability issues further complicate its integration. We present three viewpoints: (i) AI is crucial for advancing syncope management; (ii) AI can enhance the patient experience; and (iii) AI in syncope care is inevitable. Conclusion Artificial intelligence may improve syncope diagnosis and management, particularly through machine learning–based test interpretation and wearable device data. However, it has yet to surpass human clinical judgment in complex decision-making. Current challenges include gaps in understanding syncope mechanisms, AI interpretability, generalizability, and clinical integration. Standardized diagnostic approaches, real-world validation, and curated data sets are essential for progress. Artificial intelligence may enhance efficiency and communication but raises concerns regarding confidentiality, bias, inequities, and legal implications.