RecruitingNot ApplicableNCT06511505

NOrthwestern Tempus AI-enaBLed Electrocardiography (NOTABLE) Trial

NOrthwestern Tempus AI-enaBLed Electrocardiography (NOTABLE) Trial: A Pragmatic, Real-world Study of an Artificial-intelligence Enabled Electrocardiogram Algorithms to Improve the Diagnosis of Cardiovascular Disease


Sponsor

Northwestern University

Enrollment

1,000 participants

Start Date

Sep 16, 2024

Study Type

INTERVENTIONAL

Conditions

Summary

The goal of this clinical trial is to determine if a machine learning/artificial intelligence (AI)-based electrocardiogram (ECG) algorithm (rECHOmmend and ECG-AF) can identify undiagnosed cardiovascular disease in patients. It will also examine the safety and effectiveness of using this AI-based tool in a clinical setting. The main questions it aims to answer are: 1. Can the AI-based ECG algorithm improve the detection of atrial fibrillation and structural heart disease? 2. How does the use of this algorithm affect clinical decision-making and patient outcomes? Researchers will compare the outcomes of healthcare providers who receive the AI-based ECG results to those who do not. Participants (healthcare providers) will: Be randomized into two groups: one that receives AI-based ECG results and one that does not. In the intervention group, receive an assessment of their patient's risk of atrial fibrillation or structural heart disease with each ordered ECG. Decide whether to perform further clinical evaluation based on the AI-generated risk assessment as part of routine clinical care.


Eligibility

Min Age: 40 Years

Plain Language Summary

Simplified for easier understanding

This clinical trial is studying a medical device called Risk-Based Assessment for Cardiac Dysfunction for people with arrhythmia, atrial fibrillation, and other related conditions. The study is currently recruiting participants at 1 location.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Interventions

DEVICERisk-Based Assessment for Cardiac Dysfunction

The AI-enabled ECG-based screening tool analyzes 12-lead ECG recordings to identify patients at increased risk for undiagnosed cardiovascular diseases, specifically atrial fibrillation (AF) and structural heart disease (SHD). Clinicians in the intervention group will receive a risk assessment for AF and SHD each time they order an ECG for their patients.


Locations(1)

Northwestern University

Chicago, Illinois, United States

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NCT06511505


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