Artificial intelligence MacHIne learning for the detection and treatment of atrial fibrillation guidelines in the emergency department setting (AIM HIGHER): Assessing a machine learning clinical decision support tool to detect and treat non-valvular atrial fibrillation in the emergency department.

Objective: Advanced machine learning technology provides an opportunity to improve clinical electrocardiogram (ECG) interpretation, allowing non-cardiology clinicians to initiate care for atrial fibrillation (AF). The Lucia Atrial Fibrillation Application (Lucia App) photographs the ECG to determine rhythm detection, calculates CHA2DS2-VASc and HAS-BLED scores, and then provides guideline-recommended anticoagulation. Our purpose was to determine the rate of accurate AF identification and appropriate anticoagulation recommendations in emergency department (ED) patients ultimately diagnosed with AF.

Successful implantation of cardiac defibrillators without induction of ventricular fibrillation using upper limit of vulnerability testing.

Introduction: Conventionally, the implantable cardioverter-defibrillator (ICD) is tested at implantation by measurement of defibrillation threshold (DFT), which involves repeated induction of ventricular fibrillation (VF). We report our data on successful ICD implantation without VF induction using a modified upper limit of vulnerability (ULV) testing method, compared to standard DFT testing.

Methods: Fourteen patients underwent ICD implantation using a modified ULV testing method by delivering a 15 J shock during the vulnerable period on the peak of the T wave, and if VF was not induced 15 J shocks were repeated at -20 and -40 msec before the peak of T wave.

Electrophysiologic and antiarrhythmic effects of the new class III antiarrhythmic drug KCB-328 in experimental canine atrial flutter.

Background: The electrophysiologic and antiarrhythmic effects of a new class III antiarrhythmic drug (KCB-328), a delayed rectifier potassium current (IKr) blocker with minimal reverse use-dependent effect on atrial repolarization, were evaluated in the canine night atrial crush-injury model of atrial flutter (AFL).

Methods: Ten anesthetized, open-chest dogs, were studied after right atrial crush-injury. Atrial effective refractory period (ERP), conduction velocity (CV), wavelength, and dispersion of refractoriness were determined during programmed stimulation (S1S2 at S1S1 = 200, 300, 400, and 500 msec) at four sites via a mapping plaque sutured on the right atrial free wall.

Persistence of Atrial Fibrillation After Its Induction-Importance of the Duration and Dispersion of Atrial Refractoriness and Electrical Remodeling.

BACKGROUND: The electrophysiologic mechanisms of the persistence of atrial fibrillation (AF) after its initiation are not well understood. Therefore, the electrophysiologic characteristics of the right atrium were evaluated in an acute, pacing-induced model of AF in the pig in order to identify parameters associated with persistence of AF. METHODS AND RESULTS: AF was induced by rapid atrial pacing in 30 anesthetized, open-chest, juvenile pigs.

Identification of functional angiotensin II receptors on rat cardiac fibroblasts.

Background: Cardiac hypertrophy results in an increased deposition of the extracellular matrix (ECM) proteins fibronectin and collagen. Recent evidence indicates that angiotensin II (Ang II) might have an important role in the development of myocardial fibrosis accompanying cardiac hypertrophy. We sought to determine whether fibroblasts of cardiac origin (isolated from neonatal and adult animals) express receptors for Ang II and to examine the ability of this peptide to regulate fibronectin and collagen gene expression in a cultured adult cardiac fibroblast cell preparation.