Rosenthal, Julie L.

Background. Solid organ transplant recipients (SOTRs) are at heightened risk for cardiovascular implantable electronic device-related complications, particularly infection, because of chronic immunosuppression and comorbidities. Although leadless pacemakers (LPs) reduce infection risk by eliminating transvenous leads and generator pockets, adoption in SOTRs has remained limited, largely because earlier systems were restricted to single-chamber ventricular pacing and lacked physiologic atrioventricular synchrony. The helix-fixation Aveir LP platform enables atrial, ventricular, and dual-chamber leadless pacing, but clinical experience in transplant recipients remains limited. Methods. We conducted a retrospective, multisite analysis across an integrated health system, identifying all adult SOTRs who underwent Aveir LP implantation between January 2022 and October 2025. Clinical characteristics, transplant details, pacing indications, device configuration, procedural outcomes, and follow-up data were collected. Primary outcomes included procedural success, complications, and device-related infection. Secondary outcomes included pacing performance, need for system revision or upgrade, and early device durability. Results. Thirteen SOTRs (mean age 64 ± 15 y; 15% female) underwent Aveir LP implantation, including atrial (n = 4), ventricular (n = 5), and dual-chamber (n = 4) systems. Transplanted organs included heart (46%), lung (31%), kidney (38%), and liver (15%), with 31% having multiple organ transplants. Over half of patients were critically ill at implantation, and 46% were dialysis-dependent, representing a high-risk cohort. All procedures were acutely successful with no intraprocedural complications. During a median follow-up of 258 d (interquartile range, 216–641 d), no device-related infections occurred. Electrical performance remained stable, with 1 atrial device replacement at 2.5 y for elevated capture thresholds. Conclusions. In a high-risk population of SOTRs, atrial and atrioventricular synchronous leadless pacing using the Aveir platform was feasible, achieved high acute procedural success, and demonstrated favorable early safety signals, including absence of device-related infection over available follow-up. Larger studies with longer-term follow-up are needed to define durability and long-term outcomes.

Abstract Aims Cardiac amyloidosis (CA) is common in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Cardiac amyloidosis has poor outcomes, and its assessment in all TAVR patients is costly and challenging. Electrocardiogram (ECG) artificial intelligence (AI) algorithms that screen for CA may be useful to identify at-risk patients. Methods and results In this retrospective analysis of our institutional National Cardiovascular Disease Registry (NCDR)-TAVR database, patients undergoing TAVR between January 2012 and December 2018 were included. Pre-TAVR CA probability was analysed by an ECG AI predictive model, with >50% risk defined as high probability for CA. Univariable and propensity score covariate adjustment analyses using Cox regression were performed to compare clinical outcomes between patients with high CA probability vs. those with low probability at 1-year follow-up after TAVR. Of 1426 patients who underwent TAVR (mean age 81.0 ± 8.5 years, 57.6% male), 349 (24.4%) had high CA probability on pre-procedure ECG. Only 17 (1.2%) had a clinical diagnosis of CA. After multivariable adjustment, high probability of CA by ECG AI algorithm was significantly associated with increased all-cause mortality [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.01–1.96, P = 0.046] and higher rates of major adverse cardiovascular events (transient ischaemic attack (TIA)/stroke, myocardial infarction, and heart failure hospitalizations] (HR 1.36, 95% CI 1.01–1.82, P = 0.041), driven primarily by heart failure hospitalizations (HR 1.58, 95% CI 1.13–2.20, P = 0.008) at 1-year follow-up. There were no significant differences in TIA/stroke or myocardial infarction. Conclusion Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.