Enhanced detection of atrial fibrillation in single-lead electrocardiograms using a cloud-based artificial intelligence platform.

Background: Although smartphone-based devices have been developed to record 1-lead ECG, existing solutions for automatic atrial fibrillation (AF) detection often has poor positive predictive value.

Objective: This study aimed to validate a cloud-based deep learning platform for automatic AF detection in a large cohort of patients using 1-lead ECG records.

Methods: We analyzed 8,528 patients with 30-second ECG records from a single-lead handheld ECG device.

Dispersion of Activation in Single-Beat Global Maps During Programmed Ventricular Stimulation Identifies Infarct-Related Ventricular Tachycardia Isthmus Sites.

Background: Electrophysiological characterization of ventricular tachycardia (VT) isthmus sites is complex and time-consuming. We aimed at developing and validating a global mapping strategy during programmed ventricular stimulation (PVS) to reveal the underlying electrophysiological properties of the infarct-related substrate and to enable identification of highly heterogeneous activation sites associated with protected VT isthmus sites.

Methods And Results: Experimental study that included 22 pigs with established myocardial infarction undergoing in vivo characterization of the anatomical and functional myocardial substrate associated with potential arrhythmogenicity.

Novel systematic processing of cardiac magnetic resonance imaging identifies target regions associated with infarct-related ventricular tachycardia.

Aims: There is lack of agreement on late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging processing for guiding ventricular tachycardia (VT) ablation. We aim at developing and validating a systematic processing approach on LGE-CMR images to identify VT corridors that contain critical VT isthmus sites.

Methods And Results: This is a translational study including 18 pigs with established myocardial infarction and inducible VT undergoing in vivo characterization of the anatomical and functional myocardial substrate associated with VT maintenance.

Rationale and design of the artificial intelligence scalable solution for acute myocardial infarction (ASSIST) study.

Background: Acute coronary syndrome (ACS), specifically ST-segment elevation myocardial infarction is a major cause of morbidity and mortality throughout Europe. Diagnosis in the acute setting is mainly based on clinical symptoms and physician's interpretation of an electrocardiogram (ECG), which may be subject to errors. ST-segment elevation is the leading criteria to activate urgent reperfusion therapy, but a clear ST-elevation pattern might not be present in patients with coronary occlusion and ST-segment elevation might be seen in patients with normal coronary arteries.

Artificial intelligence cloud platform improves arrhythmia detection from insertable cardiac monitors to 25 cardiac rhythm patterns through multi-label classification.

Background: Electrocardiogram (ECG) is the gold standard for the diagnosis of cardiac arrhythmias and other heart diseases. Insertable cardiac monitors (ICMs) have been developed to continuously monitor cardiac activity over long periods of time and to detect 4 cardiac patterns (atrial tachyarrhythmias, ventricular tachycardia, bradycardia, and pause). However, interpretation of ECG or ICM subcutaneous ECG (sECG) is time-consuming for clinicians.

Current and Future Use of Artificial Intelligence in Electrocardiography.

Artificial intelligence (AI) is increasingly used in electrocardiography (ECG) to assist in diagnosis, stratification, and management. AI algorithms can help clinicians in the following areas: (1) interpretation and detection of arrhythmias, ST-segment changes, QT prolongation, and other ECG abnormalities; (2) risk prediction integrated with or without clinical variables (to predict arrhythmias, sudden cardiac death, stroke, and other cardiovascular events); (3) monitoring ECG signals from cardiac implantable electronic devices and wearable devices in real time and alerting clinicians or patients when significant changes occur according to timing, duration, and situation; (4) signal processing, improving ECG quality and accuracy by removing noise/artifacts/interference, and extracting features not visible to the human eye (heart rate variability, beat-to-beat intervals, wavelet transforms, sample-level resolution, etc.); (5) therapy guidance, assisting in patient selection, optimizing treatments, improving symptom-to-treatment times, and cost effectiveness (earlier activation of code infarction in patients with ST-segment elevation, predicting the response to antiarrhythmic drugs or cardiac implantable devices therapies, reducing the risk of cardiac toxicity, etc.

Artificial intelligence augments detection accuracy of cardiac insertable cardiac monitors: Results from a pilot prospective observational study.

Background: Insertable cardiac monitors (ICMs) are indicated for long-term monitoring of patients with unexplained syncope or who are at risk for cardiac arrhythmias. The volume of ICM-transmitted information may result in long data review times to identify true and clinically relevant arrhythmias.

Objective: The purpose of this study was to evaluate whether artificial intelligence (AI) may improve ICM detection accuracy.

Rational and design of ST-segment elevation not associated with acute cardiac necrosis (LESTONNAC). A prospective registry for validation of a deep learning system assisted by artificial intelligence.

Background: Patients with chest pain and persistent ST segment elevation (STE) may not have acute coronary occlusions or serum troponin curves suggestive of acute necrosis. Our objective is the validation and cost-effectiveness analysis of a diagnostic model assisted by artificial intelligence (AI).

Methods: Prospective multicenter registry in two groups of patients with STE: I) coronary arteries without significant lesions and without serum troponin curve suggestive of acute necrosis, II) myocardial infarction with acute coronary occlusion.

A Complete and Low-Cost Cardiac Optical Mapping System in Translational Animal Models.

Clinicians, biologists, physicists, engineers, and computer scientists are coming together to better understand heart disease, which is currently the leading cause of death globally. Optical mapping, a high-speed fluorescence imaging technique that visualizes and measures key cardiac parameters such as action potentials, cytosolic calcium transients, and fibrillation dynamics, is a core research tool that has arisen from such interdisciplinary collaborations. In an effort to broaden its use, especially among clinical scientists and students, we developed a complete and low-cost optical mapping system, including a constant-flow Langendorff perfusion system, which minimizes the economic threshold to widespread use of this powerful tool in cardiac electrophysiology research.

Personalized monitoring of electrical remodelling during atrial fibrillation progression via remote transmissions from implantable devices.

Aims: Atrial electrical remodelling (AER) is a transitional period associated with the progression and long-term maintenance of atrial fibrillation (AF). We aimed to study the progression of AER in individual patients with implantable devices and AF episodes.

Methods And Results: Observational multicentre study (51 centres) including 4618 patients with implantable cardioverter-defibrillator +/-resynchronization therapy (ICD/CRT-D) and 352 patients (2 centres) with pacemakers (median follow-up: 3.

Bicuspid aortic valve behaviour in elite athletes.

Aims: To determine the prevalence and characteristics of bicuspid aortic valve (BAV) among elite athletes and to analyse the effect of long-term exercise training on their aortas.

Methods And Results: Consecutive BAV and tricuspid aortic valve (TAV) elite athletes from a population of 5136 athletes evaluated at the Sports Medicine Center of the Spanish National Sports Council were identified using echocardiography. A total of 41 BAV elite athletes were matched with 41 TAV elite athletes, and 41 BAV non-athletic patients from three Spanish tertiary hospitals.

Three-dimensional cardiac fibre disorganization as a novel parameter for ventricular arrhythmia stratification after myocardial infarction.

Aims: Myocardial infarction (MI) alters cardiac fibre organization with unknown consequences on ventricular arrhythmia. We used diffusion tensor imaging (DTI) of three-dimensional (3D) cardiac fibres and scar reconstructions to identify the main parameters associated with ventricular arrhythmia inducibility and ventricular tachycardia (VT) features after MI.

Methods And Results: Twelve pigs with established MI and three controls underwent invasive electrophysiological characterization of ventricular arrhythmia inducibility and VT features.

Early prognostic value of an Algorithm based on spectral Variables of Ventricular fibrillAtion from the EKG of patients with suddEn cardiac death: A multicentre observational study (AWAKE).

Objective: Ventricular fibrillation (VF)-related sudden cardiac death (SCD) is a leading cause of mortality and morbidity. Current biological and imaging parameters show significant limitations on predicting cerebral performance at hospital admission. The AWAKE study (NCT03248557) is a multicentre observational study to validate a model based on spectral ECG analysis to early predict cerebral performance and survival in resuscitated comatose survivors.

Single coronary artery presenting as acute myocardial infarction.

A single coronary artery is one of the most rarely seen coronary artery anomalies. In addition, the specific subtype (Lipton RII-A) that our patient presented is one of the least common, and its clinical presentation as myocardial infarction and cardiac arrest has not been described in the literature. The case shows that although it is essential to exclude a malignant interarterial course of the vessel, cardiac arrest is a possible clinical presentation produced by myocardial ischemia in the context of acute myocardial infarction and should be managed according to clinical practice guidelines.

Reference Values of Aortic Root in Male and Female White Elite Athletes According to Sport.

Background: There is limited information regarding the aortic root upper physiological limits in all planes in elite athletes according to static and dynamic cardiovascular demands and sex.

Methods And Results: A cross-sectional study was performed in 3281 healthy elite athletes (2039 men and 1242 women) aged 23.1±5.

Endoscopic Ultrasound for the Detection of Left Atrial Appendage Thrombus: A Useful Technique in Patients with Transesophageal Echocardiography Contraindication.

Endoscopic ultrasound is a diagnostic and therapeutic technique used in specialized centers for patients that have undergone digestive procedures. This technique enables highly precise real-time imaging of the digestive tract wall and surrounding organs. Endoscopic ultrasound is also useful in patients with cardiovascular diseases such as atrial fibrillation.

Safety threshold of R-wave amplitudes in patients with implantable cardioverter defibrillator.

Objective: A safety threshold for baseline rhythm R-wave amplitudes during follow-up of implantable cardioverter defibrillators (ICD) has not been established. We aimed to analyse the amplitude distribution and undersensing rate during spontaneous episodes of ventricular fibrillation (VF), and define a safety amplitude threshold for baseline R-waves.

Methods: Data were obtained from an observational multicentre registry conducted at 48 centres in Spain.