NOrthwestern Tempus AI-enaBLed Electrocardiography (NOTABLE) Trial

Study acronym: NOTABLE
StatusRecruiting
PhaseNot applicable
Started

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Trial flagged as At Risk
Primary completion moved at least 2 years later across 2 updates Aug 3, 2025 → Sep 2027
Primary endpoints added 1 → 3 primary endpoints
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Record History

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  1. Primary completion pushed from Sep 2026 to Sep 2027v3 Show 6 more changesShow less
    • Primary endpoint(s) modified
    • Primary completion pushed from Aug 3, 2025 to Sep 2026
    • Trial status changed: Unknown → Recruiting
    • Study completion pushed from Mar 2027 to Sep 2028
    • Study completion pushed from Feb 3, 2026 to Mar 2027
    • Site contact updated
  2. Trial status: Not Yet Recruiting to Recruitingv2 Show 9 more changesShow less
    • Primary completion date: Aug 3, 2025 to Sep 2026
    • Primary endpoints: 1 to 3
    • Study completion date: Feb 3, 2026 to Mar 2027
    • Start date changed from estimate of Aug 3, 2024 to Sep 16, 2024
    • Interventions: TEMPUS AI-enabled ECG-based Screening Tool (Other) to Risk-Based Assessment for Cardiac Dysfunction (Device)
    • Secondary endpoints: 2 to 5
    • Study description shortened, about 38 words
    • Site details revised
    • Collaborators expanded, about 2 words
  3. Changed Registry marked status Unknown; last known: Not Yet Recruiting
  4. Study First Submitted
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
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.
Trial Details
NCT Number NCT06511505
Lead Sponsor Northwestern University
Collaborators: Tempus AI
Conditions
(from sponsor)		 Atrial Fibrillation, Cardiovascular Diseases, Arrhythmia, Valvular Disease
Related terms Arrhythmias, Cardiac, Atrial Fibrillation, Cardiovascular Diseases
Enrollment 1,000 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov