NCT06511505 · Northwestern University
NOrthwestern Tempus AI-enaBLed Electrocardiography (NOTABLE) Trial
(NOTABLE)
What this study is about
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.
View original scientific description
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.
Interventions
DEVICE
Risk-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.
Primary outcome measures
Incidence of New Atrial Fibrillation Diagnosis
Time frame: 6 months from index ECG
Number of participants with a new diagnosis of atrial fibrillation, identified by ICD-10-CM diagnosis code entry in the electronic health record (EHR), among patients ≥65 years old without a prior AF diagnosis who received a 12-lead ECG as part of routine clinical care.
Incidence of New Structural Heart Disease Diagnosis (Composite)
Time frame: 6 months from index ECG
Number of participants with a new diagnosis of one or more of the following, identified by ICD-10-CM diagnosis code and/or echocardiographic report in the EHR: moderate or severe aortic stenosis, moderate or severe aortic regurgitation, moderate or severe mitral stenosis, severe mitral regurgitation, severe tricuspid regurgitation, left ventricular ejection fraction ≤40%, or interventricular septal thickness (IVSd) \>15 mm - among patients ≥40 years old without prior SHD diagnosis who received a 12-lead ECG as part of routine clinical care.
Incidence of New Cardiovascular Diagnosis (Overall Composite: AF + SHD)
Time frame: 6 months from index ECG
Number of participants with a new diagnosis of atrial fibrillation and/or any structural heart disease component listed in Primary Outcome Measure 2, identified by ICD-10-CM diagnosis code and/or echocardiographic report in the EHR.
Who can participate
This study lists these criteria on ClinicalTrials.gov. A study coordinator reviews eligibility during screening — this page does not determine whether you qualify.
Inclusion criteria
- Atrial fibrillation algorithm
- Age 65 or over
- ECG obtained as part of routine clinical care
- Structural heart disease algorithm
- Age 40 or over
- ECG obtained as part of routine clinical care
Exclusion criteria
- Atrial fibrillation algorithm
- No history of AF
- No permanent pacemaker (PPM) or implantable cardioverter defibrillator (ICD)
- No recent cardiac surgery (within the preceding 30 days)
- Structural heart disease algorithm
- No history of SHD
- No echocardiogram within the past 1 year
Where
- Chicago, Illinois
Collaborators
Tempus AI
Related conditions & keywords
Frequently asked questions
What is a clinical trial?
A clinical trial is a research study that tests new medical treatments, drugs, devices, or procedures to determine their safety and effectiveness. Trials are carefully designed and monitored to protect participants while advancing medical knowledge.
Is it safe to participate?
Clinical trials follow strict safety guidelines and ethical standards. Trials must be reviewed and approved, and participants are closely monitored by medical professionals throughout the study. You can withdraw at any time if you choose.
Will I be compensated?
Many clinical trials offer compensation for your time, travel expenses, and inconvenience. The specific compensation varies by study and will be discussed during the screening process. All study-related medical care is typically provided at no cost to participants.
Will I receive a placebo instead of treatment?
When effective treatment exists, participants typically receive either the standard treatment plus the study intervention, or the standard treatment plus placebo. You would not be denied effective care. Placebos are primarily used when no proven treatment is available, or in addition to standard care. Your trial consent form will clearly explain what treatments you may receive.
Can I leave a trial if I change my mind?
Absolutely. Participation in clinical trials is completely voluntary. You have the right to withdraw from the study at any time, for any reason, without penalty or loss of benefits to which you are otherwise entitled.
How long does a clinical trial last?
Trial duration varies widely depending on the study design and purpose. Some trials last just a few weeks, while others may continue for months or years. The study coordinator will provide specific timeline information during your screening call.
Data: ClinicalTrials.gov · synced Aug 20, 2026 · Source of record for eligibility and locations