Citations

Spontaneous type-1 Brugada patterns are associated with an elevated risk of major arrhythmic events, yet the relationship between varying degrees of pattern burden and the occurrence of a first major arrhythmic event remains unclear. This retrospective cohort study included 64 adult patients with a spontaneous type-1 Brugada pattern, who were identified at Mayo Clinic sites and followed for ≥12 months after the initial diagnosis. All patients underwent at least three 12-lead electrocardiograms (ECGs) within the first year. Individuals with prior major arrhythmic events were excluded. The percentage of ECGs showing a type-1 pattern was calculated and categorized as paroxysmal (<50%), persistent (50–99%), or permanent (100%). During a median follow-up of 92 months, seven patients (11%) experienced their first major arrhythmic event. Of these, one had paroxysmal, four had persistent, and two had permanent spontaneous type-1 Brugada patterns. Although statistical significance was not reached, the hazard ratios suggested a trend toward increased risk with persistent and permanent patterns compared to paroxysmal patterns. No sudden cardiac deaths occurred during follow-up. These findings suggest that a higher burden of spontaneous type-1 Brugada patterns may be associated with increased arrhythmic risk.

Abstract Cardioneuroablation has emerged as a potential alternative to cardiac pacing in selected cases with vasovagal reflex syncope, extrinsic vagally induced sinus bradycardia-arrest or atrioventricular block. The technique was first introduced decades ago, and its use has risen over the past decade. However, as with any intervention, proper patient selection and technique are a prerequisite for a safe and effective use of cardioneuroablation therapy. This document aims to review and interpret available scientific evidence and provide a summary position on the topic.

Introduction: Carcinoid heart disease (CHD) is a rare sequelae of hormonally active neuroendocrine tumors that often requires cardiac surgical intervention. Little is reported on cardiac implantable electronic device (CIED) implantation in the CHD patient population. Hypothesis: We sought to establish the safety and efficacy of CIED implantation in patients with CHD. Methods: We retrospectively reviewed patients with a diagnosis of CHD who underwent CIED implantation at our institution (Mayo Clinic) and evaluated indications for implant, perioperative complications, and mortality. Results: A total of 27 patients with a cumulative follow up of 75 patient-years were identified during the study period. The most common indication for device implant was high grade atrioventricular block (n=18, 66.7%). 14 (51.8%) had baseline conduction disease and 26 (96.2%) underwent cardiac surgery prior to CIED implant. The majority of devices implanted were dual chamber permanent pacemakers (PPM) (n=17, 63.0%), while other devices included single chamber PPM, epicardial PPM, chronic resynchronization devices, and intracardiac defibrillators. Peri-operative complication occurred in 6 patients (22.2%), with 2 patients requiring ICU level care. No patient suffered carcinoid crisis during implantation and there was no peri-implant mortality. Long term, 3 patients required device extraction: 1 for infection, 1 for lead related pain, and 1 for generator migration. The median time to death from implant was 2.5 years, with one-year mortality at 15%. Conclusions: In this unique cohort of patients with CHD, CIED can be performed safely. CIED most often occurred in the post cardiac surgical period and carcinoid crisis was uncommon.

AbstractCardiac physiologic pacing (CPP), encompassing cardiac resynchronization therapy (CRT) and conduction system pacing (CSP), has emerged as a pacing therapy strategy that may mitigate or prevent the development of heart failure (HF) in patients with ventricular dyssynchrony or pacing‐induced cardiomyopathy. This clinical practice guideline is intended to provide guidance on indications for CRT for HF therapy and CPP in patients with pacemaker indications or HF, patient selection, pre‐procedure evaluation and preparation, implant procedure management, follow‐up evaluation and optimization of CPP response, and use in pediatric populations. Gaps in knowledge, pointing to new directions for future research, are also identified.

Background: Atypical Atrial Flutter (AAFL) prevalence is increasing due to the escalating Atrial Fibrillation (AF) ablations and cardiac surgeries. We wanted to explore the outcome of the AAFL ablation, considering the recent changes in mapping and ablation. Methods: This study was approved by the Institutional Review Board (IRB) of Mayo Clinic hospital. We retrospectively studied 419 patients who had undergone AAFL ablation at Mayo Clinic from January 2017 to June 2022. Thirteen patients declined research authorization, and 19 patients were lost to follow-up during the 90-day blanking period, resulting in a sample size of 387. The median follow-up time for patients was 25.7 months (95% CI 23.7, 32.3). Results: Recurrent symptoms with documentation of atrial arrhythmia Occurred in 226/387 (58.4%) patients, of which 151/226 (66.8%) occurred within the first year. The median time to recurrence was 8.5 months (max 57.8 months). Eleven patients died during the study period, 9 of whom experienced recurrence prior to death. Overall, the median recurrence-free survival (RFS) time was 16.6 months (95% CI 13.2, 20.0) with a 1-year RFS rate of 57.2% (95% CI 52.2, 62.7%). Acute termination occurred 324/387 (83.7%) during the ablation. The 1-year RFS rate was 58.9% (95% CI 53.5%, 64.9%) for patients with acute termination and 49.0% (95% CI 37.9%, 63.4%) for those without acute termination. The rate was not significantly different based on acute termination status (p = 0.11). Conclusions: The one-year RFS rate of 57.2% following AAFL ablation, even though 83.7% achieved acute termination during the procedure, signifies the extent of the underlying substrate abnormalities.

Aims:Increased left ventricular (LV) wall thickness is frequently encountered in transthoracic echocardiography (TTE). While accurate and early diagnosis is clinically important, given the differences in available therapeutic options and prognosis, an extensive workup is often required to establish the diagnosis. We propose the first echo-based, automated deep learning model with a fusion architecture to facilitate the evaluation and diagnosis of increased left ventricular (LV) wall thickness. Methods and Results: Patients with an established diagnosis of increased LV wall thickness (hypertrophic cardiomyopathy (HCM), cardiac amyloidosis (CA), and hypertensive heart disease (HTN)/others) between 1/2015 and 11/2019 at Mayo Clinic Arizona were identified. The cohort was divided into 80%/10%/10% for training, validation, and testing sets, respectively. Six baseline TTE views were used to optimize a pre-trained InceptionResnetV2 model. Each model output was used to train a meta-learner under a fusion architecture. Model performance was assessed by multiclass area under the receiver operating characteristic curve (AUROC). A total of 586 patients were used for the final analysis (194 HCM, 201 CA, and 191 HTN/others). The mean age was 55.0 years, and 57.8% were male. Among the individual view-dependent models, the apical 4-chamber model had the best performance (AUROC: HCM: 0.94, CA: 0.73, and HTN/other: 0.87). The final fusion model outperformed all the view-dependent models (AUROC: HCM: 0.93, CA: 0.90, and HTN/other: 0.92). Conclusion: The echo-based InceptionResnetV2 fusion model can accurately classify the main etiologies of increased LV wall thickness and can facilitate the process of diagnosis and workup.

AbstractIntroductionBrugada syndrome is an inherited arrhythmic disease associated with major arrhythmic events (MAE). The importance of primary prevention of sudden cardiac death (SCD) in Brugada syndrome is well recognized; however, ventricular arrhythmia risk stratification remains challenging and controversial. We aimed to assess the association of type of syncope with MAE via systematic review and meta‐analysis.MethodsWe comprehensively searched the databases of MEDLINE and EMBASE from inception to December 2021. Included studies were cohort (prospective or retrospective) studies that reported the types of syncope (cardiac, unexplained, vasovagal, and undifferentiated) and MAE. Data from each study were combined using the random‐effects, generic inverse variance method of DerSimonian and Laird to calculate the odds ratio (OR) and 95% confidence intervals (CIs).ResultsSeventeen studies from 2005 to 2019 were included in this meta‐analysis involving 4355 Brugada syndrome patients. Overall, syncope was significantly associated with an increased risk of MAE in Brugada syndrome (OR = 3.90, 95% CI: 2.22–6.85, p < .001, I2 = 76.0%). By syncope type, cardiac (OR = 4.48, 95% CI: 2.87–7.01, p < .001, I2 = 0.0%) and unexplained (OR = 4.71, 95% CI: 1.34–16.57, p = .016, I2 = 37.3%) syncope was significantly associated with increased risk of MAE in Brugada syndrome. Vasovagal (OR = 2.90, 95% CI: 0.09–98.45, p = .554, I2 = 70.9%) and undifferentiated syncope (OR = 2.01, 95% CI: 1.00–4.03, p = .050, I2 = 64.6%, respectively) were not.ConclusionOur study demonstrated that cardiac and unexplained syncope was associated with MAE risk in Brugada syndrome populations but not in vasovagal syncope and undifferentiated syncope. Unexplained syncope is associated with a similar increased risk of MAE compared to cardiac syncope.

Aims Increased LV wall thickness is frequently encountered in transthoracic echocardiography (TTE). While accurate and early diagnosis is clinically important, given the differences in available therapeutic options and prognosis, an extensive workup is often required to establish the diagnosis. We propose the first echo-based, automated deep learning model with a fusion architecture to facilitate the evaluation and diagnosis of increased left ventricular (LV) wall thickness. Methods and Results Patients with an established diagnosis of increased LV wall thickness (hypertrophic cardiomyopathy (HCM), cardiac amyloidosis (CA), and hypertensive heart disease (HTN)/others) between 1/2015 to 11/2019 at Mayo Clinic Arizona were identified. The cohort was divided into 80%/10%/10% for training, validation, and testing sets, respectively. Six baseline TTE views were used to optimize a pre-trained InceptionResnetV2 model. Each model output was used to train a meta-learner under a fusion architecture. Model performance was assessed by multiclass area under the receiver operating characteristic curve (AUROC). A total of 586 patients were used for the final analysis (194 HCM, 201 CA, and 191 HTN/others). The mean age was 55.0 years, and 57.8% were male. Among the individual view-dependent models, the apical 4 chamber model had the best performance (AUROC: HCM: 0.94, CA: 0.73, and HTN/other: 0.87). The final fusion model outperformed all the view-dependent models (AUROC: CA: 0.90, HCM: 0.93, and HTN/other: 0.92). Conclusion The echo-based InceptionResnetV2 fusion model can accurately classify the main etiologies of increased LV wall thickness and can facilitate the process of diagnosis and workup.