COR-INSIGHT: Optimizing Cardiovascular and Cardiopulmonary Outcomes with AI-Driven Multiplexed Indications Using COR ECG Wearable

The COR-INSIGHT trial is a clinical study designed to evaluate the effectiveness of Peerbridge COR ambulatory ECG wearables, COR 1.0 and COR 2.0 ("CORMDX"). These devices integrate advanced AI technologies, including CardioMIND and CardioQSync, to accurately detect a broad spectrum of cardiovascular and cardiopulmonary conditions. By offering multiplexed diagnostics via direct-from-ECG analysis, the trial seeks to validate an alternative to traditional diagnostic modalities such as imaging, catheter-based techniques, and biochemical assays.

COR-INSIGHT study is validating a comprehensive, non-invasive screening framework designed to benefit cardiac patients, including those who are asymptomatic, critically ill, or awaiting procedures such as ablation, transcatheter aortic valve replacement (TAVR), transcatheter aortic valve implantation (TAVI), or implantable cardioverter defibrillator (ICD) placement. Additionally, the protocol addresses the needs of patients with cardiopulmonary conditions, offering precise diagnostics and remote monitoring capabilities in hospital, outpatient, and home-based environments.

Objectives

The COR-INSIGHT trial is structured around clearly defined objectives aimed at demonstrating the clinical efficacy and utility of COR wearable ECG:

1. Primary Objectives:

\- To achieve sensitivity (\>80%) and specificity (\>90%) in detecting each cardiovascular and cardiopulmonary indication assessed in the study. * To validate the Positive Predictive Value (PPV) and Negative Predictive Value (NPV) of AI-enabled diagnostics on per indication basis. * To establish statistical concordance between COR ECG wearable outputs and standard reference devices, ensuring robust diagnostic performance for each indication assessed. 2. Secondary Objectives:

* To evaluate the outcome and impact of continuous, non-invasive monitoring on early detection and personalized management. * To assess the scalability and feasibility of deploying COR devices in diverse healthcare settings, including underserved populations.

Device Features

COR 1.0: delivers 3-lead, 2-channel ECG monitoring with high diagnostic fidelity with continuous data acquisition for up to 7 days, optimizing mid-term diagnostic applications.

COR 2.0:

* Extends COR 1.0 functionality with cardiopulmonary metrics and advanced battery life, enabling up to 14 days of uninterrupted monitoring. * Operates in three distinct modes:

i. Extended Holter Mode: Outputs Leads II and III for standard ECG analysis.

ii. Cardiopulmonary Mode: Outputs Leads I, II, III and V2, respiratory impedance, and triaxial accelerometer data for comprehensive evaluations.

iii. Real-Time Streaming Mode: Enables seamless Lead I, II, III, V2 and accelerometer data transmission via Bluetooth Low Energy (BLE) for immediate waveform rendering and remote analysis.

Study Design

The trial employs a prospective, cross-sectional design encompassing eight distinct sub-protocols (A-H), tailored to address diverse clinical indications:

1. Subprotocol A: Short-term (30-minute) ECG monitoring focused on cardiovascular diagnostics using COR 1.0 2. Subprotocol B: 24-hour monitoring incorporating HRV and sleep analysis using COR 1.0. 3. Subprotocol C: Multi-day (2-7 days) monitoring with integrated SpO2 measurements using COR 1.0. 4. Subprotocol D: Extended monitoring (2-14 days) to provide comprehensive cardiopulmonary insights using COR 2.0. 5. Subprotocol E: Short-term up to 30-min COR 2.0 monitoring for diagnostics excluding sleep and HRV analysis. 6. Subprotocol F: Dual-modality diagnostics combining COR 2.0 and 12-lead ECG monitoring for comparative validation of COR 2.0 derived leads against QT-Medical 12-lead ECG reference. 7. Subprotocol G: Hemodynamic monitoring with dual-phase (sitting and supine) assessments using COR 2.0 against cleared Hemodynamic Reference or thermodilution reference. 8. Subprotocol H: Sequential recordings with COR 1.0 and COR 2.0 devices to evaluate cross-device efficacy for hemodynamic assessments.

Key Indications and Metrics

An indication panel report will be provided to the subject's clinician or care-team, summarizing how the subject is risk-stratified on the panel. The panels of indications will vary depending on the Subprotocol a subject is placed in. COR-INSIGHT report will display whether a patient is predicted to be at risk or negative for each indication.

Cardiovascular Diagnostics

* Detection of heart failure, to be validated through combination of reference standards, including ultrasound, MRI, BNP/NT-proBNP levels, or EMR, using 5-minute ECG windows. * Ejection Fraction (EF) severity, critical for assessing cardiac dysfunction, compared against gold-standard ultrasound metrics. * Identification of myocardial infarction (MI), including pathological Q-waves and STEMI, compared against 12-lead cleared ECG or troponin levels as reference. * Classification of HFrEF (Heart Failure with Reduced Ejection Fraction) and HFpEF (Heart Failure with Preserved Ejection Fraction) validated against ultrasound and/or cardiac MRI reference. * Diagnosis of intermittent and silent ischemia, validated against treadmill tests and/or cardiac MRI for confirmation.

Cardiopulmonary Metrics

* Monitoring key indicators - respiratory sinus arrhythmia, cardiac output (CO), and stroke volume (SV) to provide actionable insights into cardiovascular-respiratory interactions, validated against cleared CNAP 500 hemodynamic system or thermodilution using pulmonary artery (PA) catheter reference. * Advanced evaluation of stroke volume variability and cardiopulmonary interplay is validated against cleared CNAP 500 hemodynamic system or thermodilution using pulmonary artery (PA) catheter reference.

Sleep-Related Metrics

• Direct-from-ECG computation of the apnea-hypopnea index (AHI), respiratory disturbance index, and oxygen saturation variability facilitates the diagnosis of sleep-disordered breathing. AHI to be validated using PSG or cleared Home Sleep Test (HST) as reference.

Data Collection and Analysis

1. ECG Recordings: Continuous data acquisition for durations ranging from 30 minutes to 14 days depending on the sub-protocol. 2. AI-Driven Analysis: Real-time and post-hoc analyses using CardioMIND and CardioQSync to compute diagnostic metrics with high precision. 3. Blinded Validation: Comparison of device outputs against gold-standard reference systems, including 12-lead ECG with automated interpretation, and non-invasive hemodynamic monitors, and EMR for previously diagnosed patients. 4. Explainable AI: The study utilizes a GenAI model, driven by the COR-INSIGHT indication panel and metrics, to produce explainable traces for the clinician, demonstrating how risk stratification decisions align with standard care guidelines. 5. Statistical Evaluation: Use of z-tests and ROC curve analysis to validate sensitivity, specificity, PPV, and NPV.

Participant Enrollment

The study will enroll up to 15,000 participants across diverse demographic and clinical backgrounds. Inclusion criteria prioritize patients with potential cardiovascular or cardiopulmonary conditions. Key aspects of participant management include:

1. Screening and Consent: Comprehensive screening protocols to ensure eligibility and informed consent adherence. 2. Blinded Data Handling: Participant history and demographics remain blinded during analysis to minimize bias. 3. Protocol Compliance: Non-compliance or dropout cases are systematically excluded to maintain data integrity.

Safety and Ethical Considerations

The trial adheres to stringent ethical and safety standards:

1. Risk Mitigation: Risks are limited to minor skin irritation from adhesive electrodes, with proactive monitoring to address adverse events. 2. Ethical Compliance: Conducted under Good Clinical Practice (GCP) guidelines and robust data confidentiality protocols. 3. Potential Benefits: Enhanced diagnostic accuracy, reduced reliance on invasive procedures, and improved accessibility to advanced healthcare.

Primary and Secondary Endpoints

1\. Primary Endpoints:

* Achieve \>80% sensitivity and \>90% specificity for detecting key conditions. * Demonstrate statistical concordance with reference standards for cardiovascular, cardiopulmonary, and sleep-related metrics.

2\. Secondary Endpoints: * PPV \>50% and NPV \>85% for diagnostic predictions. * Area Under the Receiver Operating Characteristic Curve (AUC-ROC) exceeding 0.82.

Clinical Impact

The COR-INSIGHT trial seeks to establish a validated framework for diagnosing cardiovascular and cardiopulmonary conditions using wearable ECG technology. Specific objectives include:

1. Advancing Early Detection: Providing clinically actionable insights into conditions that often remain undiagnosed until advanced stages. 2. Enhancing Patient Outcomes: Enabling personalized care strategies through continuous, non-invasive monitoring. 3. Promoting Healthcare Accessibility: Deploying scalable, cost-effective solutions to underserved and remote populations. 4. Reducing Healthcare Costs: Minimizing dependence on invasive procedures, imaging, and hospitalizations.

• Positive Predictive Value (PPV) for Indicated Cardiovascular Condition Using CardioMIND [Срок оценки: Through study completion - average of 18-months]
• Negative Predictive Value (PPV) for Indicated Cardiovascular Condition Using CardioMIND [Срок оценки: Through study completion - average of 18-months]
• Statistical Agreement Between The Proportion Of Screen Positive Cases With Clinically Significant CO & SV Changes That Require Interventions [Срок оценки: Through study completion - average of 18-months]