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NCT Number: NCT06699056

AI-Enabled Direct-from-ECG Ejection Fraction (EF) Severity Assessment Using COR ECG Wearable Monitor

This prospective, multicenter, cluster-randomized controlled study aims to evaluate the accuracy of an investigational artificial intelligence (AI) Software as a Medical Device (SaMD) designed to compute ejection fraction (EF) severity categories based on the American Society of Echocardiography's (ASE) 4-category scale. The software analyzes continuous ECG waveform data acquired by the FDA-cleared Peerbridge COR® ECG Wearable Monitor, an ambulatory patch device designed for use during daily activities. The AI software assists clinicians in cardiac evaluations by estimating EF severity, which reflects how well the heart pumps blood.

In this study, EF severity determination will be made using 5-minute ECG recordings collected during a 15-minute resting period with participants seated upright. The results will be compared to EF severity obtained from an FDA-cleared, non-contrast transthoracic echocardiogram (TTE) predicate device. This comparison aims to validate the accuracy of the AI software.

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Key information

Conditions

Ventricular Ejection Fraction Arrhythmias, Cardiac Atrial Enlargement Atrial Remodeling Cardiomegaly Cardiomyopathies Cardiomyopathy, Dilated Cardiotoxicity Cardiovascular Diseases Chemically-Induced Disorders Conduction Defect Congenital, Hereditary, and Neonatal Diseases and Abnormalities Consciousness Disorders Dilated Cardiomyopathy Drug-Related Side Effects and Adverse Reactions Genetic Diseases, Inborn HFpEF - Heart Failure With Preserved Ejection Fraction HFrEF - Heart Failure With Reduced Ejection Fraction Heart Diseases Heart Failure Heart Valve Diseases Infarction Ischemia Ischemic Heart Disease LV Dysfunction LVF Laminopathies Myocardial Infarction Myocardial Ischemia Necrosis Nervous System Diseases Neurobehavioral Manifestations Neurologic Manifestations Pathologic Processes Pathological Conditions, Anatomical Pathological Conditions, Signs and Symptoms Radiation Injuries Remodeling, Cardiac Signs and Symptoms Syncope Unconsciousness Valvular Heart Disease Vascular Diseases Ventricular Dysfunction Ventricular Dysfunction, Left Wounds and Injuries

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Orange County Heart Institute, Orange, California, United States

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About this study

Objective This prospective study benchmarks the accuracy of CorEFS AI software in estimating ejection fraction (EF) severity categories using continuous ECG waveforms from the FDA-cleared Peerbridge Cor® ECG device, calibrated to the American Society of Echocardiography (ASE) scale.

Background Heart failure (HF) remains a significant public health issue, particularly in older adults (75+), with high morbidity and mortality rates. Half of HF cases involve reduced EF (HFrEF), a condition associated with a 75% five-year mortality rate. Despite advancements in HF management, accessible, low-cost EF monitoring is lacking.

Echocardiography (Echo) is the gold standard for EF measurement but is limited in ambulatory and home settings. Continuous ECG wearables like the Peerbridge Cor® offer a promising alternative, providing high diagnostic yield, low wear burden, and real-time EF estimation. Previous studies (References 1-11) demonstrate the potential of AI-enabled ECG analysis in EF prediction, with accuracies up to 91.4% and AUCs of 0.94 in estimating EF severity.

Successful demonstration of the proposed endpoints to clinically acceptable statistical thresholds will provide a new and alternative capability for EF severity assessments compared to ultrasound, MRI, and other imaging modalities where access is limited.

Hypothesis Specific ECG changes may identify left ventricular dysfunction (LVSD) and predict EF severity, enabling low-burden, cost-effective EF monitoring in high-risk populations.

Study Design

Participant Enrollment and Setup

Participants will receive the Peerbridge Cor® wearable, with data collection occurring through:

In-clinic setup: Study staff apply and initiate device use. Patient Home Setup (PHS): Telehealth guidance for independent device application (20% of participants).

Subprotocols

A: 30 minutes of Cor® ECG recording; 15 minutes analyzed. B: Up to 7 days of Cor® device use with periodic 15-minute sitting sessions. EF Reference Standard EF severity will be determined via FDA-cleared transthoracic echocardiography (TTE), using the Simpson's Bi-Plane Method.

Data Collection

Peerbridge Cor® ECG Data: 30 minutes recorded; 15 minutes analyzed in 5-minute segments.

Echo Study: Conducted before or during Cor® recording. 12-Lead ECG: Simultaneous recording with the Cor® device. Participants log sessions using the Cor® device's Event button. De-identified medical histories will support subgroup analyses.

Endpoints Agreement between Cor® ECG-derived EF severity and Echo results will be assessed across ASE-defined categories (Normal, Mild, Moderate, Severe). Positive predictive value (PPV) adjusted for prevalence will be calculated.

This streamlined protocol validates CorEFS software for reliable, cost-effective EF monitoring and clinical decision support.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age ≥ 18 years
  • Able and eligible to wear a Holter monitor

Exclusion criteria

  • Receiving mechanical respiratory or circulatory support, or renal support therapy, at the time of screening or during Visit #1
  • Any condition that, in the investigator's opinion, could interfere with compliance with the study protocol or pose a safety risk to the participant
  • History of poor tolerance or severe skin reactions to ECG adhesive materials

Treatment and study plan

15-minutes of sitting during COR ECG Acquistion

Device

Participants will follow a standardized protocol during a 15-minute seated session using the Peerbridge COR™ device. Participants will sit comfortably in an upright chair with a straight back; armrests are optional. Their feet must remain flat on the floor with legs uncrossed to ensure unobstructed blood flow and a stable posture. Arms should be relaxed and placed in their lap, on a flat surface (e.g., table), or on the armrest, ensuring they are not tensed or elevated. Participants will maintain a straight back with relaxed shoulders throughout the session.

To begin, participants will press the Event Button on the Peerbridge COR™ mobile device, marking the start of the session. They will remain seated in this position for 15 minutes. At the end of the session, participants will press the Event Button again to mark the conclusion of the seated event. This protocol ensures consistent data collection across all participants.

Primary outcomes

  1. Agreement of CorEFS Software EF Severity Categories Using Peerbridge COR™ ECG Data with ASE EF Severity Categories Established by Ultrasound Echocardiography

    Time frame: Through study completion, average of 9 months.

    The primary endpoint of this trial is to demonstrate substantial agreement between EF severity categories determined by the CorEFS Software using 5 minutes of Peerbridge COR™ ECG data and the subject's EF severity category established through ultrasound echocardiography, the gold standard for EF classification. The study includes four co-primary endpoints, representing agreement measures within each of the four EF severity categories defined by the American Society of Echocardiography (ASE) Scale (Normal, Mildly Abnormal, Moderately Abnormal, Severely Abnormal). For each category the endpoint is the proportion of participants correctly classified by the test device relative to the reference standard. The goal is to demonstrate at least 80% agreement within each EF severity category.

Secondary outcomes

  1. Confirmation of ≥80% Agreement Between Peerbridge Cor™ ECG Data and Reference Standard ECHO in EF Severity Categorization Using 15-Minute Continuous Monitoring: Secondary Endpoint Analysis

    Time frame: Through study completion, average of 9 months.

    The secondary endpoint is to confirm at least 80% agreement between the proportion of all participants, correctly categorized in all 4 EF Severity Categories by analyzing 15-minutes of continuous Peerbridge Cor™ ECG device data compared to those that are categorized by the Reference Standard ECHO. This will be tested with a one-sided single-sample z-test at a 97.5% confidence level to see if agreement exceeds 80%, thereby rejecting the null hypothesis of ≤80% agreement in favor of significant concordance.

Other outcomes

  1. Substantial Equivalence of Peerbridge Cor™ ECG-Derived EF Severity Results Across 2-Minute, 5-Minute, and 15-Minute Time Windows Compared to Reference Standard ECHO

    Time frame: Through study completion, average of 9 months.

    Analysis will be conducted to assess for statistical agreement between the proportion of all subjects, correctly categorized in all 4 EF Severity Categories by analyzing 2-minutes of continuous Peerbridge Cor™ ECG device data compared to those that are categorized by the Reference Standard ECHO. This will be tested with a one-sided single-sample z-test at a 97.5% confidence level to see if agreement exceeds 80%, thereby rejecting the null hypothesis of ≤80% agreement in favor of significant concordance.

Study contacts

Contact information is provided by the study sponsor or research team.

Chris Darland, MBA

CONTACT

[email protected]

814-572-7138

Sandeep Gulati, PhD

CONTACT

[email protected]

8182162958

Sponsors and collaborators

Lead sponsor

Peerbridge Health, Inc

Industry

Registry information

Official study title

AI-Enabled Direct-from-ECG Ejection Fraction (EF) Severity Using COR ECG Wearable Monitor

Acronym: EFACT

Important dates

Study start
2024
Primary completion
2027
Study completion
2027
First posted
Nov 21, 2024
Registry last updated
Jun 1, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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