Factors Associated With Response to Cardiac Resynchronization Therapy in Heart Failure Patients With Non-LBBB ECG Pattern

NCT ID: NCT06977217

Last Updated: 2025-05-18

Basic Information

• Recruitment Status: ACTIVE_NOT_RECRUITING
• Total Enrollment: 270 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-03-21
• Study Completion Date: 2026-06-30

Brief Summary

Cardiac resynchronization therapy with a defibrillator (CRT-D) in heart failure (HF) patients without left bundle branch block (non-LBBB) has been less beneficial to improve outcomes despite being a guideline indicated therapy, posing a significant treatment challenge. However, non-LBBB patients with echocardiography response to CRT-D have better outcomes, and pre-implant variables could predict response, identifying patients who benefit the most. In this study, we plan to enroll 270 HF patients with non-LBBB and guideline-indicated CRT-D implantation to validate our prior echocardiography predictor score, and to identify novel ECG and echocardiography predictors using conventional statistics and machine learning analysis. We will also assess the applicability of such a score for clinical outcomes of HF, ventricular arrhythmias, or death.

Detailed Description

Morbidity, mortality, and health care costs of the treatment of systolic heart failure (HF) are rapidly increasing. Cardiac resynchronization therapy with a defibrillator (CRT-D) is cost-effectively reducing HF events and death in HF patients with a wide QRS and low ejection fraction. However, response to CRT-D is not unequivocally present in all patients, with less benefit in those without the presence of an ECG abnormality, left bundle branch block (non-LBBB), posing a significant treatment challenge.

Because of the conflicting and limited data on response to CRT-D in this cohort, it is possible that we currently treat a large proportion of HF patients with non-LBBB who have limited or no benefit from the device. Therefore, better selection of patients for this expensive therapy is warranted. One of our recent studies suggested a clinical benefit in patients with non-LBBB and marked echocardiography response, and identified predictors. However, there is a need to prospectively validate these predictors of echocardiography response to CRT-D in non-LBBB in this hard-to-treat patient population, and identify potential novel ECG and echocardiography predictors, utilizing novel statistical methods of machine learning. We propose a prospective, observational, single-arm study in a currently guideline-indicated cohort to validate and identify predictors of echocardiography response to CRT-D, including novel ECG and echocardiography markers, and to assess subsequent clinical outcomes in 270 HF patients with an implanted CRT-D and non-LBBB ECG pattern.

The primary aim of the study is to prospectively validating our previously identified clinical predictors of echocardiography response to CRT-D in HF patients with non-LBBB that could enable better patient selection.

Our secondary aim is to identify the incremental value of novel ECG and echocardiography variables to predict echocardiography response to CRT-D in non-LBBB patients, including ECG variables of sum absolute QRST integral and ventricular electrical activation delay, and echocardiography-derived variables of left ventricular dyssynchrony and contractility. Then we will apply the developed predictive model to prospectively identify non-LBBB patients with CRT-D at a risk of heart failure, ventricular arrhythmias, or death. Tertiary aim is to identify novel ECG and echocardiography predictors of response in non-LBBB using machine learning analysis.

Study population will include 270 HF patients with non-LBBB and an implanted CRT-D with 6 months echocardiography follow-up analyzed by an echocardiography core lab, and assessing clinical outcomes of heart failure, ventricular arrhythmias, or death.

Conditions

Cardiomyopathies; Heart Failure; Non-left Bundle Branch Block; Cardiac Resynchronization Therapy

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Interventions

CRT-D implantation

Cardiac resynchronization therapy with a defibrillator (CRT-D). This combination device uses a pacemaker and an implantable cardioverter-defibrillator (ICD). It may be recommended for people with heart failure who also have a risk of sudden cardiac death. It can find dangerous heart rhythms and correct them. It can pace the heartbeat or shock the heart out of a dangerous heart rhythm.

Intervention Type: PROCEDURE

Eligibility Criteria

Inclusion Criteria

• Age 18 years or older (no upper limit)
• Optimal medical therapy for heart failure as established by current guidelines;
• Class IIa or IIb guideline-based indication for CRT-D in non-LBBB patients, including one of the following:
• New York Heart Association (NYHA) class II HF symptoms, LVEF ≤ 30% and QRS≥ 150 ms (IIb);
• NYHA class III-IVa HF, LVEF ≤ 35%, and QRS duration ≥ 150 ms (IIa);
• NYHA class III-IVa HF, LVEF ≤ 35%, and QRS duration 120- 149 ms (IIb)
• Successful CRT-D generator implant

Exclusion Criteria

• Unable to obtain imaging data from echocardiogram within 1 year prior to CRT-D implant
• Unable to obtain the 20-minute ECG prior to CRT-D implant
• Unable to enroll within 14 days following successful CRT-D generator implant
• Unable or unwilling to follow the study protocol
• Less than 24 months life expectancy at enrollment
• Pregnancy or planned pregnancy in the next 24 months

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

University of Rochester

OTHER

Sponsor Role: lead

Responsible Party

Valentina Kutyifa

Professor of Medicine (Cardiology), Tenured

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Valentina Kutyifa, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

University of Rochester

Locations

University of Rochester Medical Center

Rochester, New York, United States

Countries

United States

Other Identifiers

STUDY00006153

Identifier Type: -

Identifier Source: org_study_id