Extended Rhythm Monitoring to Assess for Ventricular Arrhythmias After Transcatheter Pulmonary Valve Replacement With the Harmony Valve.

Background: Varying rates of nonsustained ventricular tachycardia (NSVT) have been reported early after transcatheter pulmonary valve replacement (TPVR) with the Harmony valve, but data regarding rhythm outcomes beyond hospital discharge are limited. This study aims to characterize ventricular arrhythmias after Harmony TPVR from implant through mid-term follow-up.

Methods: Ventricular arrhythmia data from postimplant telemetry and follow-up extended rhythm monitoring (ERM) were analyzed after Harmony TPVR.

EFFICACY OF INTRAVENOUS IMMUNOGLOBULIN ALONE ON CORONARY ARTERY LESION REDUCTION IN KAWASAKI DISEASE.

Background: Though Aspirin and intravenous immunoglobulin (IVIG) remain the standard treatments for Kawasaki Disease (KD) to minimize coronary artery damage, the duration and dosage of aspirin are inconsistent across hospitals. However, the lack of multi-center randomized trials prevents definitive answers to the impact of high-dose aspirin.

Methods: This clinical trial was structured as a prospective, evaluator-blinded, multi-center randomized controlled trial with two parallel arms, aiming to assess the effectiveness of IVIG as a standalone primary therapy of KD in comparison to the combination of IVIG with high-dose aspirin therapy.

Multisite Validation of a Functional Assay to Adjudicate Brugada Syndrome-Associated Variants.

Background: Brugada syndrome is an inheritable arrhythmia condition that is associated with rare, loss-of-function variants in . Interpreting the pathogenicity of missense variants is challenging, and ≈79% of missense variants in ClinVar are currently classified as variants of uncertain significance. Automated patch clamp technology enables high-throughput functional studies of ion channel variants and can provide evidence for variant reclassification.

Digital twinning of cardiac electrophysiology for congenital heart disease.

In recent years, blending mechanistic knowledge with machine learning has had a major impact in digital healthcare. In this work, we introduce a computational pipeline to build certified digital replicas of cardiac electrophysiology in paediatric patients with congenital heart disease. We construct the patient-specific geometry by means of semi-automatic segmentation and meshing tools.