Sorajja, Dan

Abstract Background Recurrence of symptomatic atrial fibrillation (AF) after catheter ablation (CA) is not uncommon. However, real-world long-term data on clinical outcomes of rhythm control strategies in patients with recurrent AF after CA remain limited. Methods Using the TriNetX database, we identified adult patients (≥18 years) with recurrent AF after index CA. A 3-month blanking period was applied, during which no rhythm-control therapy was received. Patients were classified into two groups: repeat CA or initiation of antiarrhythmic drug (AAD) therapy. Propensity score matching (PSM) was performed to balance baseline characteristics. Hazard ratios (HR) with 95% confidence intervals (CI) were calculated. Outcomes included all-cause mortality, all-cause hospitalization, heart failure (HF) exacerbation, ischemic stroke, and major bleeding over 5 years. Results Among 4,056 patients with recurrent AF post-CA, 17.2% underwent repeat CA. After PSM, 697 patients in the repeat CA group (mean age 68.9 ± 9.6 years; 35.7% female) and 697 in the AAD group (mean age 68.4 ± 10.0 years; 37.6% female) were analyzed. Repeat CA was associated with lower all-cause mortality (3.3% vs 8.2%; HR 0.44; 95% CI, 0.27–0.72; P < 0.01), all-cause hospitalization (42.8% vs 56.4%; HR 0.71; 95% CI, 0.61–0.82; P < 0.01) and HF exacerbation (12.5% vs 24.8%; HR 0.50; 95% CI, 0.39–0.64; P < 0.01). No differences were observed in ischemic stroke (5.3% vs 4.7%; HR 1.22; 95% CI, 0.77–1.96; P = 0.40) or major bleeding (4.6% vs 6.2%; HR 0.82; 95% CI, 0.52–1.29; P = 0.39). Conclusions Repeat CA was associated with lower mortality, hospitalization, and HF exacerbation over 5 years.

ABSTRACT Background Atrial fibrillation (AF) is prevalent in cardiac amyloidosis (CA) and is associated with adverse clinical outcomes. Catheter ablation is increasingly used for rhythm control in this population, yet its clinical outcomes remain uncertain. We performed a systematic review and meta‐analysis to evaluate arrhythmia recurrence and clinical outcomes following catheter ablation compared with medical therapy in patients with CA. Methods We systematically searched MEDLINE, Embase, and Scopus from inception through December 2025 for studies evaluating catheter ablation of atrial arrhythmias in CA. Cohort studies reporting arrhythmia recurrence and/or clinical outcomes were included. The primary outcome was freedom from atrial arrhythmia (AA) following ablation. Secondary outcomes included all‐cause mortality, heart failure hospitalization, and stroke. Random‐effects models were used to pool event rates and odds ratios (ORs). Results Thirteen observational studies comprising 797 patients with CA and AF were included. The pooled rate of freedom from AA following catheter ablation was approximately 50% (95% CI 37%–63%; I 2 = 71.7%). The all‐cause mortality analysis included 4 observational studies comprising 616 patients. Catheter ablation was associated with lower odds of all‐cause mortality (OR 0.26, 95% CI 0.11–0.60; I 2 = 18.4%); however, this association should be interpreted with caution given the retrospective design and risk of bias. No statistically significant differences were observed for heart failure hospitalization or stroke. Conclusions In patients with CA, catheter ablation was associated with modest arrhythmia‐free survival and lower odds of all‐cause mortality. However, all contributing studies were observational cohorts. Randomized studies are needed to confirm these findings.

Abstract Introduction Despite its prevalence, risk stratification for tachycardia-induced cardiomyopathy remains poorly understood. A deep learning model developed at Mayo Clinic uses standard 12-lead electrocardiograms (ECGs) to predict reduced LVEF (≤35%) in the general population with high accuracy (AUC 0.93) Purpose We investigated the performance of AI-ECG in predicting systolic dysfunction among patients with atrial fibrillation and rapid ventricular response, and compared it with NT-proBNP. Methods We conducted a retrospective study (IRB approval #25-000904) of adult patients (age ≥ 18 years) evaluated across our Clinic enterprise with atrial fibrillation and rapid ventricular response (heart rate >100 bpm), including AF occurring in-hospital and AF at presentation, between January 2017 and May 2025. We excluded patients with a known history of heart failure with reduced EF (<50%). We also collected data on NT-proBNP levels when available within one week of the ECG and echocardiogram. Results A total of 11,801 patients were included, with a mean age of 73.2 +- 12.6 years, 48.6% female and 94.8% White. A combination of AI ECG low EF probability cutoff of 75% had specificity of 96% and 98% NPV in ruling out LVEF < 35%. A combination of AI ECG low EF probability cutoff of 17% and LVEF <35% provided the best balance of sensitivity and specificity, 66% and 78%, respectively with an accuracy of 78%. NT-proBNP data was available on 5,279 patients (48%). Mean NT-proBNP level was 4090 pg/mL. Based on ROC curve analysis, AI ECG was superior to NT-proBNP in predicting LVEF <35% (AUC 0.72 vs 0.59), with accuracy of 77% versus 47% at Youden’s cutpoints of AI-ECG probability of 17% and NT-proBNP level of 1767 pg/mL, respectively Conclusions Our study demonstrates the utility of AI-ECG in predicting reduced LVEF among patients with AF RVR. AI-ECG demonstrated excellent specificity and NPV in ruling out reduced LVEF, serving as a powerful clinical screening tool to assist with the pharmacologic choice of rate control and could change the timing of further echocardiographic evaluation. Our study offers novel insights paving the way for future investigations to help fine-tune and further delineate the role of AI ECG in risk stratifying patients with suspected tachycardia-induced cardiomyopathy, guiding therapeutic and diagnostic clinical decisions

This cross-sectional study investigates the association between lipoprotein(a) levels and risk of ventricular arrhythmias among patients with heart failure with reduced ejection fraction receiving implantable cardioverter-defibrillator therapy.

ABSTRACT Background Prolonged QT interval is common in end‐stage renal disease (ESRD) on dialysis, but its long‐term cardiovascular (CV) implications remain unclear. Methods Using TriNetX network (2010–2024), we identified adults with ESRD on dialysis and categorized them by QTc status. After 1:1 propensity score matching ( n = 3428/group), outcomes (hazard ratio [HR]) were assessed using Cox regression. Results Prolonged QTc (> 500 ms) was associated with higher risk of all‐cause mortality (HR 1.67; p < 0.001), MACEs (HR 1.40; p < 0.001), cardiac arrest (HR 1.75; p < 0.001), sustained ventricular arrhythmia (HR 1.66; p < 0.001), new‐onset atrial fibrillation (HR 1.12; p = 0.01), and acute myocardial infarction (HR 2.19; p < 0.001). Conclusions In ESRD patients on dialysis, prolonged QT interval was independently associated with adverse CV outcomes and mortality.

Key Points Atrial fibrillation after kidney transplantation is common and is associated with poor prognosis. Artificial intelligence applied to 12-lead electrocardiograms pretransplant accurately predicts the risk of new-onset atrial fibrillation in our cohort. High-risk artificial intelligence electrocardiography score was independently associated with increased risk of mortality and allograft failure. Background Incident atrial fibrillation (AF) is common after kidney transplantation (KTx) and is associated with worse clinical outcomes. Artificial intelligence electrocardiography (AI-ECG) algorithms have demonstrated efficacy in predicting risk of new-onset AF in the general population; however, their prognostic value in KTx recipients is relatively unknown. Methods Retrospective analysis was conducted on KTx recipients without AF, with at least one pretransplant ECG between 2011 and 2021 across three tertiary centers in the United States (Mayo Clinic sites in MN, AZ, and FL). A previously validated AI-ECG algorithm estimated the probability of incident AF for each patient. Based on AI-ECG probabilities, patients were categorized into high-risk and low-risk groups, with the optimal AI-ECG score cutoff determined. The incidence of new-onset AF, allograft failure, and mortality was compared between groups. Results Overall, 6246 patients (age 53.5±13.8 years; 58.9% male) were included. Pretransplant AI-ECG probability of AF ≥5% was the optimal cutoff for high risk of incident AF (sensitivity 72%, specificity 62%). High-risk scores were associated with true new-onset AF at 30 days (adjusted hazard ratio [aHR], 2.89; 95% confidence intervals [CI], 2.05 to 4.09; P < 0.001), 3 years (aHR, 2.54; 95% CI, 1.99 to 3.26, P < 0.001), and 5 years post-transplant (aHR, 2.48; 95% CI, 1.99 to 3.09, P < 0.001). High-risk AI-ECG scores were also associated with increased mortality (aHR, 1.56; 95% CI, 1.30 to 1.88, P < 0.001) and overall allograft failure (aHR, 1.50; 95% CI, 1.30 to 1.75, P < 0.001) through the 5-year follow-up. Conclusions This pretransplant AI-ECG parameter identified patients at increased risk of new-onset AF post-KTx and provided prognostic utility. Overall, this easy to obtain tool allows for risk stratification of patients who may benefit from closer monitoring, targeted risk factor modification, and early intervention.

Abstract Introduction/Background Transthyretin amyloidosis (ATTR) is a debilitating disease that leads to progressive cardiac dysfunction. Tafamidis is the gold standard therapy for ATTR cardiomyopathy. In recent observational studies, sodium-glucose cotransporter-2 inhibitors (SGLT2-Is) have demonstrated cardiovascular benefits in ATTR cardiomyopathy, but their role in ATTR cardiomyopathy as combination therapy with tafamidis remains unclear. Purpose To investigate the impact of combination therapy with tafamidis and SGLT2-Is versus just tafamidis in patients with known ATTR cardiomyopathy. Methods This retrospective cohort study utilized data from the TriNetX multinational database. Patients diagnosed with ATTR cardiomyopathy who received tafamidis were identified and stratified into two cohorts based on SGLT2-I use. Outcomes were assessed over three years, including all-cause mortality, all-cause hospitalizations, acute myocardial infarction (AMI), acute heart failure (HF) hospitalizations, ischemic stroke, atrial fibrillation/flutter, end-stage renal disease (ESRD) or requirement for renal replacement therapy, and ventricular tachycardia. Propensity score matching was used to balance both cohorts based on clinical comorbidities, medication use, and laboratory data. Adjusted odds ratios (OR) were calculated by logistic regression models. Results After propensity score matching, 409 patients were included in each cohort with a follow-up duration of 722 days (SD 320.87) for the SGLT2-I cohort and and 755.90 days (SD 363.26) for the non-SGLT2-I cohort. SGLT2-Is were associated with significantly lower rates of all-cause hospitalizations (41.1% vs. 50.9%; OR 0.67 [p = 0.005]) and AMI (6.6% vs. 13.9%, OR 0.44 [p = 0.001]), which persisted by three years (all-cause hospitalizations: 52.1% vs. 61.4%, OR 0.67 [p = 0.006] and myocardial infarction: 11.2% vs. 18.3%, OR 0.56 [p = 0.004]). No significant differences among the two cohorts were observed for all-cause mortality, acute HF hospitalizations, ischemic stroke, atrial fibrillation/flutter, ventricular tachycardia, or ESRD/need for renal replacement therapy. Conclusions SGLT2-Is, in combination with tafamidis, are associated with decreased all-cause hospitalizations and AMI in ATTR cardiomyopathy. While a mortality benefit was not demonstrated, these results depict the magnitude of clinical benefit derived from combination therapy with tafamidis and SGLT2-Is as opposed to prior observational studies which investigated SGLT2-I single therapy