Clinical Research Directory

REstoration of SYNChronous Cardiac Function Due to Physiologic cArdiac Pacing Modalities With Clinical Endpoints

The goal of this observational study is to evaluate the long-term clinical outcomes of physiologic cardiac resynchronization therapy (CRT) using conduction system pacing strategies compared with conventional biventricular CRT in patients with heart failure with reduced ejection fraction (HFrEF) and electrical dyssynchrony. The main questions it aims to answer are: * Does physiologic CRT (including left bundle branch area pacing \[LBBAP\] and LBBAP-optimized CRT) reduce the combined risk of all-cause mortality and heart failure hospitalization compared with conventional biventricular CRT? * Does physiologic CRT improve cardiac function and reverse ventricular remodeling more effectively than conventional CRT? Participants receiving physiologic CRT as part of routine clinical care will undergo standard follow-up evaluations, including electrocardiography, echocardiography, laboratory testing, and device interrogation. Clinical outcomes will be collected prospectively for 24 months and compared with a historical cohort of patients treated with conventional biventricular CRT. The study will assess clinical outcomes, echocardiographic response, electrical resynchronization parameters, and device-related safety in a real-world heart failure population.

Machine Learning for Diagnosis of Occlusive MI in LBBB Patients

This study investigates a new way to diagnose severe heart attacks in patients who have a specific electrical heart pattern called a Left Bundle Branch Block (LBBB). When patients present to the emergency department with chest pain, doctors routinely perform an electrocardiogram (ECG) to check for a heart attack. However, the presence of an LBBB can alter the heart's electrical signals on the ECG, effectively masking or hiding the typical signs of an ongoing acute coronary occlusion (a completely blocked artery). This making it highly challenging for emergency physicians to make an accurate and rapid diagnosis. The primary purpose of this prospective and observational research is to develop and evaluate an artificial intelligence/machine learning (ML) model that can analyze digital 12-lead ECG signals to accurately predict a true blocked coronary artery in patients with LBBB. The machine learning model will analyze raw digital ECG waveforms to detect subtle, microscopic patterns that might be missed by the human eye. To confirm the accuracy of the model, its predictions will be compared directly with invasive coronary angiography results, which is the gold standard reference method used to visualize blocked vessels. Additionally, the study aims to evaluate if the model can differentiate between a true heart attack caused by a blocked artery (Type 1 MI) and other non-occlusive conditions that cause elevated heart enzymes (Type 2 MI). Ultimately, the investigators intend to determine whether integrating this machine learning tool into emergency care can safely reduce the rate of unnecessary emergency invasive procedures for patients who do not have a true coronary blockage.

UHF ECG in LBBB and Response to CRT Prediction

The main objective of the project is to demonstrate that in patients with heart failure and QRS complex of nonRBBB morphology lasting over 130 ms, UHF-ECG can differentiate patients with trueLBBB from IVCD better than existing approaches based on the assessment of QRS complex morphology and duration from 12-lead ECG. Another goal of the proposed study is to demonstrate that trueLBBB patients will benefit more from CRT using left bundle branch pacing than from CRT using biventricular pacing. The final aim of the project is to demonstrate that the echocardiographic and clinical response in patients with intraventricular conduction disturbance will be dependent on the degree of reduction in ventricular dyssynchrony after CRT.

EArly Effect of Glucocorticoid on Incidence of Persistent Left BundlE Branch Block (LBBB) Post-TAVR (EAGLE-TAVR Trial)

Transcatheter aortic valve replacement (TAVR) has become an established alternative for the treatment of severe symptomatic aortic stenosis irrespective of surgical risk. The development of new-onset left bundle branch block (LBBB) is the most common complication, which impairs outcomes after TAVR. Glucocorticoid has been proven safe and effective in arrythmia after cardiac surgery. The anti-inflammatory effect of glucocorticoid may alleviate the occurrence of LBBB and thus the prognosis. EAGLE-TAVR is a multi-center, randomized, double blind, placebo-controlled trial. A total of 200 patients selected to undergo TAVR will be randomized in a 1:1 ratio to the treatment with intravenous Methylprednisolone 1mg/kg/day or placebo for 3 days started from the day of the procedure. According to the definition of the Valve Academic Research Consortium 3, persistent LBBB is defined as present LBBB at discharge or \>7 days post-TAVR. The primary endpoint is the occurrence of new-onset LBBB at 30 days post TAVR.