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Introduction: Unexplained high-grade AV block (AVB) in patients age <65 years is among the salient features of cardiac sarcoidosis (CS). Guidelines recommend that CS patients with high-grade AVB should receive an implantable cardioverter-defibrillator (ICD) or cardiac resynchronization therapy-defibrillator (CRT-D) rather than a permanent pacemaker (PPM). However, in clinical practice, CS may be recognized after PPM implantation for high-grade AVB. Aims: To evaluate the characteristics and outcomes of patients diagnosed with CS after PPM implantation for high-grade AVB and assess the decision-making and rationale for upgrade to ICD/CRT-D. Methods: Retrospective review of the Mayo Clinic Sarcoid Registry (n=848) was performed to identify all patients for which a PPM was implanted for high-grade AVB prior to the diagnosis of CS. Baseline clinical and imaging characteristics were collected during index evaluation at our institution. Decision-making for ICD upgrade, lead management strategy, immunosuppression initiation, and outcomes were assessed. Results: Overall, 29 of 848 (3.4%) of CS patients (62% probable/definite CS; 77% male; median (IQR) age 56 (48-61) years; and median (IQR) LVEF 58% (50-62) received a PPM for high-grade AVB prior to a CS diagnosis. Median (IQR) interval between PPM implant and index evaluation was 10 (3-23) months. Eight of 29 patients underwent upgrade to ICD (n=4) or CRT-D (n=4). Among them, the pacing lead was extracted in 4. All patients were upgraded for primary prevention of sudden cardiac death (SCD), with 3 of them also having LVEF<50% requiring upgrade to CRT-D. Twenty-two (79%) patients in the total cohort were treated with immunosuppression. During median (IQR) follow-up 37 months (11-74), 1 patient in the upgrade group had sustained VT appropriately treated with anti-tachycardia pacing. No events were documented among patients in the non-upgrade group. At last follow-up, 6 (75%) patients in the upgrade group and 12 (57%) in the non-upgrade group were pacemaker dependent. Median LVEF change was 0% in patients who underwent upgrade to CRT-D and –0.2% in those who underwent upgrade to ICD or no upgrade. Conclusions: In this cohort of patients diagnosed with CS several months after a PPM had been implanted for high-grade AVB, incident VT/VF was infrequent with contemporary CS management. In the absence of other SCD risk factors, CS patients who received a PPM for high-grade AVB prior to their CS diagnosis may not require ICD upgrade.

Background: In recent years, catheter ablation has emerged as a sustainable, first-line therapy for the management of ventricular tachycardia (VT). Given the rise of the “obesity paradox” theory in atrial ablation outcomes, we sought to study the effect of BMI on patients undergoing structural VT ablation. Purpose: To assess the outcomes of VT ablation, specifically VT recurrence, in patients with elevated vs. normal BMI. Methods: Clinical characteristics and demographic data were collected for VT patients who underwent ablation at Mayo Clinic Rochester from 2012-2022. Patient BMI was classified as non-obese (<30 kg/m2), obese (30-40 kg/m2), and morbidly obese (≥40 kg/m2). The endpoint was a composite of initial monomorphic VT recurrence and repeat ablation after adjusting for age, sex, and comorbidities. Results: A total of 399 patients underwent 508 ablations. 51.4% of ablations had a BMI <30, 39.2% were between 30-40, and 9.4% were ≥40. There was a greater prevalence of hypertension and type 2 diabetes mellitus in morbidly obese patients (p <0.01). Morbidly obese individuals also had a significantly increased rate of general anesthesia during ablation and long VT cycle lengths. The Kaplan-Meier curve demonstrates no statistically significant differences in time to VT recurrence among the three BMI groups (p = 0.324). Neither morbid-obesity (aHR= 1.20; CI = 0.94-1.56, p = 0.14) nor nonmorbid-obesity (aHR = 0.92; CI = 0.76-1.10, p = 0.4), compared to non-obesity was a significant independent predictor of VT recurrence or repeat ablation on multivariate regression after adjusting for age, sex and comorbidities. Conclusion: There was no significant association between BMI groups and VT recurrence or repeat ablation, and no difference in complications. We did not find the obesity paradox to be relevant for VT ablation in our patient population. Further study would be needed with larger samples to corroborate these findings.

Introduction: The prevalence and prognostic significance of PVC and NSVT in cardiac sarcoidosis (CS), especially in patients with normal or mildly decreased LV function, are not well known and were investigated in the current study. Methods: We included 192 patients with definite and probable CS with LVEF>35%, no prior history of VT/VF or sudden cardiac death, who underwent up to 48 hours of Holter monitoring. They were followed retrospectively for the composite endpoint of sustained VT/VF, advanced heart failure therapy, and all-cause mortality. We performed multivariable analysis for the association of PVC burden and NSVT with the composite endpoint. Covariates were considered if they were present in at least 95% of the study sample and were significantly associated with the composite endpoint in univariable analysis. Results: The median PVC burden in the overall population was 0.3% (IQR 0.02-2.5%) and 36 (18.8%) patients had a PVC burden ≥5%. Sixty-two (32.3%) patients had NSVT detected during monitoring. The PVC burden and prevalence of NSVT in patient subgroups are shown in Figures 1 and 2. A total of 33 (17.2%) patients experienced one of the composite endpoints at a median follow-up of 3 years. In the multivariable analysis (Figure 3), PVC burden ≥5% versus <5% (HR 3.96 [1.19, 5.97], p-value <0.01) and presence of NSVT (HR 4.55 [2.09, 9.94], p-value <0.01) were associated with the composite outcome. Conclusion: Our results suggest that a high PVC burden and the presence of NSVT carry isolated prognostic value in CS. In addition, ventricular ectopy does not appear to be an indicator of disease activity based on abnormal uptake on PET scan.

Background Hyperlipidemia is a major cardiovascular disease (CVD) risk factor, but there are limited data on its mortality trends in CVD over time. We assessed annual hyperlipidemia‐related CVD mortality trends in the United States, including the COVID‐19 pandemic's impact. Methods and Results Mortality data were obtained from the Centers for Disease Control and Prevention repository between 1999 and 2020 among patients ≥15 years old, using International Classification of Diseases, Tenth Revision ( ICD‐10 ) codes for hyperlipidemia (E78.0–E78.5) and CVD (I00–I99). Age‐adjusted mortality rates (AAMRs) per 1 000 000 population were standardized to the 2000 US population. Log‐linear regression models were used to evaluate mortality shifts. Average annual percentage change from 1999 to 2019 was used to project 2020 AAMRs, estimating pandemic‐attributed excess deaths. From 1999 to 2020, 483 155 hyperlipidemia‐related CVD deaths occurred. Despite a general CVD mortality decline, hyperlipidemia‐related CVD AAMRs rose from 36.33 in 1999 to 99.77 in 2019. Ischemic heart diseases (AAMR 49.39) were the leading cause, whereas hypertension had the highest mortality increase (average annual percentage change +10.23%). Mortality rates were higher in men (AAMR 104.87) and non‐Hispanic (AAMR 82.49), and rural populations (AAMR 89.98). Highest mortality was observed in Black populations (AAMR 84.35), those ≥75 years old (AAMR 646.45), and Western US regions (AAMR 96.88). During the first pandemic year, deaths exceeded projections by 10.55%, with notable increases among ages 35 to 75 (14.23%), Hispanic (17.96%), Black (14.82%), and urban (11.68%) groups. Conclusions Hyperlipidemia‐related CVD mortality has risen over the past 2 decades, further heightened by the COVID‐19 pandemic, with higher impact on men, Black Americans, the older population, and rural residents. Further study is needed to understand contributing factors and mitigate disparities.

Abstract Background Heart failure (HF) and atrial fibrillation (AF) are intertwined, sharing common risk factors and influencing each other in a reciprocal manner. While left ventricular diastolic dysfunction (LVDD) stands as a hallmark of HF's hemodynamic profile, its direct correlation with heightened AF risk remains uncertain. Our recent validation of an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm for LVDD detection has opened new avenues. Yet, whether AI-ECG-detected LVDD correlates with long-term AF risk remains unexplored. Methods We performed a retrospective study among all patients with a comprehensive LVDD assessment from the test population of the AI-ECG LVDD study between September 2001 and June 2022. Patients with prior documented AF according to health records or previous ECG were excluded. Patients were classified by AI-ECG as normal diastolic function (DF), grade 1 (G1), grade 2 (G2), or grade 3 (G3) LVDD. We assessed the risk of AF across AI-ECG LVDD grade, with normal DF as reference, with competing risk models. Results Of 97,023 patients free of AF at baseline, 63,533 (65.4%), 10,776 (11.1%), 18,940 (19.5%), and 3,774 (3.9%) were classified as normal DF, G1-LVDD, G2-LVDD, and G3-LVDD, respectively. Worse AI-ECG LVDD was associated with older age, lower left ventricular ejection fraction (LVEF), and higher rates of HF, diabetes, hypertension, chronic pulmonary disease, renal failure, and cardiovascular disease (p-of-trend&lt;0.001 for all). Over a median follow-up of 4.8 years (interquartile range 1.8-9.2 years), new-onset AF occurred in 6,795 (7.0%) patients. In multivariable survival analysis, adjusted to multiple risk factors including LVEF and clinical HF, G2 and G3 LVDD, representing patients with high filling pressures, were independently associated with a higher AF-risk [G2-LVDD: adjusted hazard ratio (aHR) 1.64 (95% confidence interval (95%CI) 1.52-1.73), G3-LVDD: aHR 2.24 (95%CI 2.02-2.48)]. Conclusion The AI-ECG LVDD algorithm independently predicts long-term AF risk, regardless of LVEF and clinical HF status, highlighting its potential for identifying high-risk populations and guiding proactive monitoring and management.

Abstract Background The determination of left ventricular diastolic dysfunction (LVDD) and filling pressure in patients with significant (&gt;moderate) mitral regurgitation (MR) poses a complex challenge. We recently validated an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm to detect LVDD and estimate LV filling pressures. Methods This retrospective study sought to examine the risk of all-cause mortality across AI-ECG LVDD grades. Patients from the AI-ECG LVDD study test cohort who underwent transthoracic echocardiography confirming significant MR and an ECG within fourteen days of each other at Mayo Clinic between 09/2001 and 06/2022 were included. LVDD status was determined based on the index ECG, and patients were categorized into groups representing normal diastolic function (NDF) or LVDD grades 1 (G1), 2 (G2), or 3 (G3). Results Of 4,019 patients with significant MR (mean age 69.8, 49.0% women), 1,175 (29.2%), 1,881 (46.8%), and 963 (24.0%) were classified by AI-ECG as NDF/G1-LVDD, G2-LVDD, and G3-LVDD, respectively. The median mitral effective regurgitant orifice area was 26 mm² (interquartile range 20-36 mm²). Over a median follow-up of 3.5 years, 1,636 (40.7%) patients died. In multivariable survival analysis adjusted for multiple risk factors, a worse AI-ECG LVDD grade was independently associated with an increased death risk [G2DD: adjusted hazard ratio (aHR) 1.98 (95% confidence interval (95% CI) 1.63-2.40), G3DD: aHR 2.59 (95% CI 2.09-3.20)]. These findings were consistent when accounting for mitral valve intervention and among patients with &gt;moderate MR or after mitral valve intervention. Conclusion In patients with significant MR, the grading of LVDD by AI-ECG is independently associated with all-cause mortality.

BACKGROUND: Differentiating wide complex tachycardias (WCTs) into ventricular tachycardia (VT) and supraventricular wide tachycardia via 12-lead ECG interpretation is a crucial but difficult task. Automated algorithms show promise as alternatives to manual ECG interpretation, but direct comparison of their diagnostic performance has not been undertaken. METHODS: Two electrophysiologists applied 3 manual WCT differentiation approaches (ie, Brugada, Vereckei aVR, and VT score). Simultaneously, computerized data from paired WCT and baseline ECGs were processed by 5 automated WCT differentiation algorithms (WCT Formula, WCT Formula II, VT Prediction Model, Solo Model, and Paired Model). The diagnostic performance of automated algorithms was compared with manual ECG interpretation approaches. RESULTS: A total of 212 WCTs (111 VT and 101 supraventricular wide tachycardia) from 104 patients were analyzed. WCT Formula demonstrated superior accuracy (85.8%) and specificity (87.1%) compared with Brugada (75.2% and 57.4%, respectively) and Vereckei aVR (65.3% and 36.4%, respectively). WCT Formula II achieved higher accuracy (89.6%) and specificity (85.1%) against Brugada and Vereckei aVR. Performance metrics of the WCT Formula (accuracy 85.8%, sensitivity 84.7%, and specificity 87.1%) and WCT Formula II (accuracy 89.8%, sensitivity 89.6%, and specificity 85.1%) were similar to the VT score (accuracy 84.4%, sensitivity 93.8%, and specificity 74.2%). Paired Model was superior to Brugada in accuracy (89.6% versus 75.2%), specificity (97.0% versus 57.4%), and F1 score (0.89 versus 0.80). Paired Model surpassed Vereckei aVR in accuracy (89.6% versus 65.3%), specificity (97.0% versus 75.2%), and F1 score (0.89 versus 0.74). Paired Model demonstrated similar accuracy (89.6% versus 84.4%), inferior sensitivity (79.3% versus 93.8%), but superior specificity (97.0% versus 74.2%) to the VT score. Solo Model and VT Prediction Model accuracy (82.5% and 77.4%, respectively) was superior to the Vereckei aVR (65.3%) but similar to Brugada (75.2%) and the VT score (84.4%). CONCLUSIONS: Automated WCT differentiation algorithms demonstrated favorable diagnostic performance compared with traditional manual ECG interpretation approaches.

AbstractIntroductionThe impact of mRNA‐based coronavirus disease‐2019 (COVID‐19) vaccines on atrial arrhythmias (AA) and ventricular arrhythmias incidence is unknown.MethodsBIOTRONIK Home Monitoring data and Medicare Claims data were utilized to identify individuals implanted with a cardiac implantable electronic device (CIED) between 2010 and 2020 who received one or more doses of COVID‐19 vaccine in 2021. The burden of AA (%) in the 3 months postvaccination was compared to those noted in the preceding 3 months using the Wilcoxon signed rank test. Sub‐analyses comparing the effects of the influenza vaccine against the COVID‐19 vaccine were also evaluated for individuals who received the influenza vaccine in 2020. A 1:1 propensity score match comparison between COVID‐19 vaccine and non‐vaccinated patients was also performed.ResultsFirst and second doses of the COVID‐19 vaccine were administered to 7757 and 6579 individuals with a CIED (age 76.2 ± 9.0 years, 49% males), respectively. While a small but statistically significant increase in the burden of AA was noted in the 3 months postvaccination compared to the preceding 3 months after the first dose of the COVID‐19 vaccine (0.43 ± 9.04%, p = .028) a similar rise in AA was found following the influenza vaccine and for matched patients who did not receive the COVID‐19 vaccine. No significant difference in device therapies was seen pre‐ and postvaccination.ConclusionsThough we report a small but significant increase in the number of CIED‐detected AAs following vaccination for COVID‐19 over a 3‐month window, we believe these results correlate more with time and the progressive nature of AF rather than the vaccine itself. While these data should not dissuade from the use of these vaccines, increased vigilance and prompt treatment of AF is required for high‐risk groups, specifically males over 70 years of age, following vaccination.

AbstractIntroductionWe performed a cross‐sectional study using the Centers for Disease Control and Prevention's (CDC's) Wide‐Ranging Online Data for Epidemiologic Research (WONDER) database to analyze the trends in cardiac implantable electronic device (CIED) infection‐related mortality from 1999 to 2020.MethodsWe analyzed the death certificate data from the CDC WONDER database from 1999 to 2020 for CIED infections in the US population aged ≥25 years using International Classification of Diseases, Tenth Revision (ICD‐10) codes, listed as the underlying or contributing cause of death. Age‐adjusted mortality rates (AAMR) and 95% confidence intervals (CIs) were computed per 1 million population by standardizing crude mortality rates to the 2000 US census population. To assess annual mortality trends, we employed the Joinpoint regression model, calculating the annual percent change (APC) in AAMR and corresponding 95% CIs.ResultsOverall, there was an observed declining trend in AAMRs related to CIED infection‐related mortality. Males accounted for 55% of the total deaths, with persistently higher AAMRs compared to females over the study duration. Both males and females had an overall decreasing trend in AAMRs throughout the study duration. On race/ethnicity stratified analysis, non‐Hispanic (NH) Blacks exhibited the highest overall AAMR, followed by NH American Indians or Alaska Natives, NH Whites, Hispanic or Latinos, and NH Asian or Pacific Islanders. On a stratified analysis based on region, the South region had the highest overall AAMR, followed by the Midwest, West, and Northeast regions.ConclusionOur study demonstrates a significant decline in CIED infection‐related mortality in patients over the last two decades. Notable gender, racial/ethnic, and regional differences exist in the rates of mortality related to CIED infections.