Background: Multimorbidity is common in patients with atrial fibrillation (AF), yet comorbidity patterns are not well documented.
Methods: The prevalence of 18 chronic conditions (6 cardiometabolic, 7 other somatic, 5 mental health) was obtained in patients with new-onset AF from 2013-2017 from a 27-county region and controls matched 1:1 on age, sex, and county of residence. For AF patients and controls separately, clustering of conditions and co-occurrence beyond chance was estimated (using the asymmetric Somers' D statistic), overall and for ages <65, 65-74, 75-84, and ≥85 years.
Background: The ability to predict recovery of left ventricular ejection fraction (LVEF) in response to guideline-directed therapy among patients with nonischemic cardiomyopathy is desired. We sought to determine whether left ventricular endocardial unipolar voltage measured during invasive electroanatomic mapping could be used to predict LVEF recovery among those with recent-onset nonischemic cardiomyopathy.
Methods: We analyzed the left ventricular voltage maps of patients included in the eMAP trial (Electrogram-Guided Myocardial Advanced Phenotyping; NCT03293381), a prospective, nonrandomized, interventional trial conducted at 2 institutions between 2017 and 2020.
Arrhythm Electrophysiol Rev
August 2024
Background: Atrioventricular (AV) conduction ablation has been achieved by targeting the area of penetration of the conduction axis as defined by recording a His bundle potential. Ablation of the His bundle may reduce the possibility of a robust junctional escape rhythm. It was hypothesised that specific AV nodal ablation is feasible and safe.
View Article and Find Full Text PDFAims: Recently, deep learning artificial intelligence (AI) models have been trained to detect cardiovascular conditions, including hypertrophic cardiomyopathy (HCM), from the 12-lead electrocardiogram (ECG). In this external validation study, we sought to assess the performance of an AI-ECG algorithm for detecting HCM in diverse international cohorts.
Methods And Results: A convolutional neural network-based AI-ECG algorithm was developed previously in a single-centre North American HCM cohort (Mayo Clinic).
Background And Aims: Incidence and types of secondary tricuspid regurgitation (TR) are not well defined in atrial fibrillation (AFib) and sinus rhythm (SR). Atrial secondary TR (A-STR) is associated with pre-existing AFib; however, close to 50% of patients with A-STR do not have AFib. The aim of this study was to assess incidence, types, and outcomes of ≥ moderate TR in AFib vs.
View Article and Find Full Text PDFBackground: The study aimed to describe the patterns and trends of initiation, discontinuation, and adherence of oral anticoagulation (OAC) in patients with new-onset postoperative atrial fibrillation (POAF), and compare with patients newly diagnosed with non-POAF.
Methods And Results: This retrospective cohort study identified patients newly diagnosed with atrial fibrillation or flutter between 2012 and 2021 using administrative claims data from OptumLabs Data Warehouse. The POAF cohort included 118 366 patients newly diagnosed with atrial fibrillation or flutter within 30 days after surgery.
Background: The effects of disease-causing MYBPC3 or MYH7 genetic variants on atrial myopathy, atrial fibrillation (AF) clinical course, and catheter ablation efficacy remain unclear.
Objectives: The aim of this study was to characterize the atrial substrate of patients with MYBPC3- or MYH7-mediated hypertrophic cardiomyopathy (HCM) and its impact on catheter ablation outcomes.
Methods: A retrospective single-center study of patients with HCM who underwent genetic testing and catheter ablation for AF was performed.
Aims: Mobile devices such as smartphones and watches can now record single-lead electrocardiograms (ECGs), making wearables a potential screening tool for cardiac and wellness monitoring outside of healthcare settings. Because friends and family often share their smart phones and devices, confirmation that a sample is from a given patient is important before it is added to the electronic health record.
Methods And Results: We sought to determine whether the application of Siamese neural network would permit the diagnostic ECG sample to serve as both a medical test and biometric identifier.