Friedman, Paul A

BACKGROUND: Pulsed field ablation is now widely used for atrial fibrillation (AF) ablation, but atrial tachyarrhythmia recurrence remains common and postablation risk tools are limited. We assessed whether a validated sinus‑rhythm artificial intelligence— enabled ECG AF probability score, and its early postablation change, predicts recurrence after pulsed field ablation. METHODS: We studied consecutive patients undergoing index pulsed field ablation across 3 Mayo Clinic sites (February 2024–March 2025) with ≥1 sinus‑rhythm ECG within 180 days preprocedure. Baseline artificial intelligence—enabled ECG AF score (range 0–1) was the mean across baseline ECGs. Recovery indices (RI30/60/90), defined as mean postprocedure artificial intelligence—enabled ECG score within days 1–30/60/90 minus baseline, predicted post‑blanking recurrence using corresponding 30‑, 60‑, and 90‑day blanking windows. The primary outcome was time to first documented AF/atrial flutter/atrial tachycardia episode >30 seconds, ascertained via clinic ECGs, ambulatory monitoring, and device interrogations. Cox regression adjusted for prespecified clinical and echocardiographic covariates assessed associations; Harrell C‑statistic quantified discrimination. RESULTS: Among 1052 patients (67±10 years; 33% women), median baseline score was 0.35; 320 (30%) recurred over 188 days. Higher baseline score independently predicted recurrence (hazard ratio per 0.1 increase, 1.08 [95% CI, 1.03–1.14]). Scores rose on day 0 after ablation, then declined over subsequent weeks, with persistently higher, less‑improving trajectories among patients who recurred (time×recurrence interaction P <0.001). Day 0 score was not independently associated with recurrence after adjustment. Attenuated early recovery (higher recovery index) was independently associated with recurrence, most robustly for RI-90 (hazard ratio per 0.1 increase, 1.15 [95% CI, 1.07–1.24]), and improved discrimination beyond baseline and covariates (C‑statistic, 0.63–0.67; ΔC=0.04). Findings were consistent in a historical thermal ablation cohort. CONCLUSIONS: Baseline and early postablation dynamics of a sinus‑rhythm artificial intelligence—enabled ECG AF probability score are associated with pulsed field ablation recurrence and may aid multivariable risk stratification; prospective validation is warranted.

Abstract Aims Heart failure is prevalent; however, there is no cost-effective screening option. Against formal echocardiography, we assessed the diagnostic performance of focused cardiac ultrasound (FoCUS), performed by novice users guided and interpreted by artificial intelligence (AI) for the assessment of left ventricular ejection fraction (LVEF). Methods and results We prospectively enrolled 496 adults referred for diagnostic echocardiography. Novice operators (without clinical or imaging experience) underwent a 4-h imaging workshop, then performed FoCUS using a point-of-care device (Philips Lumify) utilizing real-time AI-image guidance (UltraSight). Images were assessed by AI-image interpretation software (Mayo Clinic), and two expert blinded echocardiologists. Median age was 67, 39% female, and body mass index range 17–56 kg/m2. Forty-one subjects (8.3%) exhibited moderate or greater LV dilatation and 28 (5.6%) had LVEF &lt;40%. The median scan time was 4 min (IQR 3–5). Adequate views were achieved in 95.0% and 97.4% of subjects for AI interpretation and expert analysis, respectively. A two-step diagnostic screening process for low EF in which only abnormal AI reads or uninterpretable scans were reviewed by experts (15.1%) had a sensitivity 96.2%, specificity 95.4%, PPV 54.3%, and NPV 99.8%. A subsequent prospective validation study of 344 subjects demonstrated similar results (sensitivity 100%, specificity 99.4%). Conclusion In this early feasibility investigation, AI-guidance technology embedded on a handheld device, enabled novice users without clinical or imaging experience to acquire sufficient quality images to accurately assess LVEF with minimal training. The technology evaluated in this study may hold promise for AI-guidance and interpretation to facilitate low-cost screening for cardiac dysfunction.

BACKGROUND: Radiofrequency (RF) ablation of premature ventricular complexes (PVCs) originating from the left ventricular summit may be unsuccessful, highlighting the need for alternative approaches. We aimed to assess the efficacy and safety of a novel dual-modality focal catheter in treating left ventricular summit PVCs in patients who had failed previous RF ablation. METHODS: Patients were prospectively enrolled and underwent a redo ablation procedure using an irrigated, contact-force sensing, dual-modality focal catheter (TactiFlex Duo, Abbott) under compassionate use indication. The ablation strategy, including the choice of energy modality (monopolar pulsed field [PF], RF, or both), was left to the operator’s discretion. Safety assessments included serial biomarkers, renal function, and CMR within 36 hours. Efficacy was defined as ≥80% reduction in PVC burden with symptom resolution at 3-month follow-up. RESULTS: Six consecutive patients (4 men; mean age, 53.8±15 years) with symptomatic left ventricular summit PVCs and a prior failed RF ablation (range, 1–2) were prospectively enrolled. All PVCs had an inferior axis, with a left bundle V1 morphology observed in 4 of 6 cases (mean burden, 30.1±5.3%). Acute suppression of PVCs was achieved in all cases. Acute suppression with a single PF application in the great cardiac vein-anterior interventricular vein occurred in 2 patients, while 3 patients required additional RF, PF, or combined RF+PF applications at adjacent sites. One patient with an inaccessible great cardiac vein-anterior interventricular vein was successfully treated in the left ventricular outflow tract with RF+PF application. Transient, reversible left anterior descending vasospasm was observed during PF delivery in 2 of 5 cases that underwent PF application adjacent to a coronary artery, despite pretreatment with intracoronary nitroglycerin without ECG or hemodynamic sequelae. All patients had durable suppression of PVCs at follow-up. CONCLUSIONS: In its first human application, dual-modality ablation was feasible and effective for refractory left ventricular summit PVCs. Transient coronary vasospasm occurred, though it was reversible and without acute clinical consequences.

Abstract Aims Coronary angiography might contain clinically relevant information, beyond its traditional role in delineating coronary artery disease. We sought to explore the role of deep learning (DL) in detecting right ventricular dysfunction from routinely acquired cine images during coronary angiography. Methods and results 3D-convolutional neural networks (CNN) were trained to identify right ventricle (RV) dysfunction from diagnostic angiography of the right coronary artery (RCA). The model’s input was two cine angiograms from LAO and RAO projections. The model’s output was normal vs. abnormal RV function. Ground truth on RV function was obtained from the nearest transthoracic echocardiogram to the coronary angiogram. Two analyses were performed to identify (i) any RV dysfunction (≥mild) and (ii) significant RV dysfunction (≥mild–moderate). A total of 10 336 coronary angiograms from 9849 patients (mean age 66, 36% women) were included. The cohort was split into training (70%), validation (15%), and testing (15%) sets. In the testing sets, the models attained an area under the ROC curve (AUC), sensitivity, and specificity of 0.82 (95% CI: 0.80–0.84), 0.75, and 0.74, for detecting any RV dysfunction, and 0.83 (95% CI: 0.80–0.86), 0.82, and 0.70 for detecting significant (≥mild–moderate) RV dysfunction. Combining an ECG-driven AI model with the angio-driven model improved the AUC values to 0.83 and 0.87 for detecting any or advanced RV dysfunction, respectively. Conclusion A novel deep learning algorithm yielded acceptable classification accuracy in detecting RV dysfunction from routine cine angiography of the RCA. The model’s performance improved further by adding ECG to its inputs.

BACKGROUND: MODULAR antitachycardia pacing (ATP), a multicenter, international trial, assesses a modular cardiac rhythm management system: a subcutaneous implantable cardioverter defibrillator in wireless communication with a leadless pacemaker (LP) capable of pace-terminating ventricular tachycardia. METHODS: Enrolees had one or more clinical risk factors for ventricular tachycardia and did not require chronic pacing. Complications included prespecified major LP system- and procedure-related complications, and any complication related to the LP, subcutaneous implantable cardioverter defibrillator, implantation, or study protocol. Survival analysis was performed to identify complication-free rates, therapy delivery, and all-cause mortality. RESULTS: The 297 patients enrolled had an ejection fraction of 35±13%, 43% secondary prevention indications, and 59% with prior ventricular arrhythmias. Of 286 patients undergoing LP implantation (100% success), 251 patients completed 12-month follow-up. Mortality rate was 6%, with none related to the implant procedure. Median follow-up duration was 23.4 months (interquartile range, 17.9–28.1). The LP major complication-free rate was 97.2%, exceeding the performance goal. The overall LP+ subcutaneous implantable cardioverter defibrillator system-related complication-free rate was 88.5%. Appropriate tachyarrhythmia-therapy (ATP+shock) rates were 14.4%, and appropriate shock rates were 8.5%. Inappropriate total tachyarrhythmia therapy was 9.5% of which 8.5% were shocks. ATP was 67.3% successful in terminating ventricular arrhythmia episodes and accelerated ventricular arrhythmias in 10.1% of episodes. Overall therapy burden (ATP+shock) was 96/100 patient-years, of which 44/100 patient-years was for shock delivery. CONCLUSIONS: One-year outcomes of the first modular pacing-defibrillator system reveal low system and LP complication rates and good ATP efficacy rates, suggesting that the modular cardiac rhythm management is a viable alternative to single-chamber implantable cardioverter defibrillators using low-energy pacing capability without the need for transvenous leads. CLINICAL TRIAL REGISTRATION: URL: https://clinicaltrials.gov/ ; Unique identifier: NCT04798768.

Background Postoperative atrial fibrillation occurs in ~40% after cardiac surgery. Mineralocorticoid receptor antagonists (MRA) are known to reduce chronic atrial fibrillation (AF) development and burden. We evaluated the association of preoperative MRA use with postoperative atrial fibrillation and investigated atrial cell types modulated by MRAs during cold preservation. Methods We studied 19 042 cardiac surgery patients at Mayo Clinic. Propensity 1:3 matching identified 298 MRA users and 894 non‐users. A subgroup analysis of patients on any preoperative diuretic was performed to isolate cardiac‐specific effects of MRAs, matching 298 MRA users to 894 non‐MRA diuretic users. AF recurrence was assessed for up to 6‐years. Single‐nucleus RNA sequencing (snRNA‐seq) was performed on human donor atria exposed to canrenone (a water‐soluble MRA) during cold preservation with ex‐vivo reperfusion, and expression profiles were compared with atria from patients with AF. Results After matching, preoperative MRA use was associated with a lower incidence of postoperative atrial fibrillation (19.8% versus 31.8%, P <0.001). In the diuretic‐only subgroup, MRA users also had lower postoperative atrial fibrillation (19.8% versus 33.2%, P <0.001). MRA use was associated with a reduced incidence of paroxysmal and chronic AF at 6‐years. snRNA‐seq identified a cardiomyocyte subpopulation, CM2, with high mineralocorticoid receptor expression where canrenone suppressed cold preservation‐induced mineralocorticoid receptor target gene expression, which was conversely elevated in chronic AF. Canrenone also attenuated stress‐response in atrial macrophages and pericytes. Conclusions Preoperative MRAs were associated with reduced postoperative and long‐term AF after cardiac surgery. Mechanistically, our ex‐vivo human atrial model revealed that MRAs suppress mineralocorticoid receptor ‐driven atrial stress responses, particularly in conduction‐relevant cardiomyocytes.

ABSTRACT Background Transvenous lead removal (TLR) is a Class I indication for patients with cardiac implantable electronic device (CIED) infections. However, disparities in the utilization of TLR have not been fully explored, particularly concerning demographic and socioeconomic factors. Objectives This study aims to examine whether disparities exist among patients hospitalized for CIED infections with respect to the utilization of TLR, focusing on sex, race, and income characteristics. Methods We utilized the 2019 National Inpatient Sample (NIS) to assess patients hospitalized with CIED infections and identify those who underwent TLR. Multiple logistic regression was used to examine risk factors for TLR utilization, including age, sex, race/ethnicity, and socioeconomic characteristics. Results A total of 56 709 patients were hospitalized for CIED infection in the United States in 2019, of which 9867 (17.4%) underwent TLR. On an adjusted analysis, females and Black patients were found to have lower odds of undergoing TLR compared to males and White patients (OR: 0.62; 95% CI: 0.59–0.78; p < 0.01; and OR: 0.47; 95% CI: 0.39–0.57; p < 0.01, respectively). Hispanic patients also had reduced odds of TLR (OR: 0.73; 95% CI: 0.58–0.93; p = 0.01). No significant associations were observed between income or insurance status and the likelihood of receiving TLR after adjustment. Conclusions This study identified significant disparities in the utilization of TLR among patients hospitalized for CIED infections. Female, Black, and Hispanic patients were significantly less likely to receive TLR.

Abstract Aims Catheter ablation is commonly performed in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) for management of ventricular arrhythmias (VAs). The impact of catheter ablation on cardiac function is unknown. The aim is to assess the impact of catheter ablation for VAs on cardiac function in patients with ARVC. Methods and results This retrospective study included consecutive patients with ARVC who underwent catheter ablation for VAs. Cardiac and valvular functions were assessed on pre- and post-procedure cardiac imaging. The severities of tricuspid regurgitation, pulmonic regurgitation, right ventricular (RV) enlargement, and RV systolic dysfunction was graded as absent (=0), mild (=1), mild-moderate (=2), moderate (=3), moderate-severe (=4), or severe (=5). Thirty-four patients were included. Median age at the time of ablation was 49 [inter-quartile range (IQR), 23] years, and 10 (29%) patients were female. After a median follow-up of 1 (IQR, 0) day, 11 (34%) patients had worsening RV function, and 4 (12%) patients had worsening left ventricular ejection fraction (LVEF) &gt;5%. Five (15%) patients required inotropic support. After a median follow-up of 6.5 (IQR, 6.4) months, 20 (59%) patients had repeat transthoracic echocardiograms. Among patients with worsening RV function post-ablation, one-sixth (17%) had improvement in the RV function at follow-up. In contrast, among patients who had an acute drop in LVEF post-ablation, two-thirds (67%) had improvement at follow-up. Conclusion Right ventricular dysfunction following catheter ablation in patients with ARVC is common, affecting one-third of patients. Patients undergoing catheter ablation of VAs should be counselled on the potential negative impact of ablation on cardiac function.

Abstract Aims Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural optimization, and patient outcome prediction. However, a standardized approach to reporting and understanding AI-related research in EP is lacking. This scientific statement aims to develop and apply a checklist for AI-related research reporting in EP to enhance transparency, reproducibility, and understandability in the field. Methods and results An AI checklist specific to EP was developed with expert input from the writing group and voted on using a modified Delphi process, leading to the development of a 29-item checklist. The checklist was subsequently applied to assess reporting practices to identify areas where improvements could be made and provide an overview of the state of the art in AI-related EP research in three domains from May 2021 until May 2024: atrial fibrillation (AF) management, sudden cardiac death (SCD), and EP lab applications. The EHRA AI checklist was applied to 31 studies in AF management, 18 studies in SCD, and 6 studies in EP lab applications. Results differed between the different domains, but in no domain reporting of a specific item exceeded 55% of included papers. Key areas such as trial registration, participant details, data handling, and training performance were underreported (&lt;20%). The checklist application highlighted areas where reporting practices could be improved to promote clearer, more comprehensive AI research in EP. Conclusion The EHRA AI checklist provides a structured framework for reporting AI research in EP. Its use can improve understanding but also enhance the reproducibility and transparency of AI studies, fostering more robust and reliable integration of AI into clinical EP practice.