NOrthwestern Tempus AI-enaBLed Electrocardiography (NOTABLE) Trial
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age40+
SponsorNorthwestern University
About this trial
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 criteria
This trial accepts healthy volunteersQualifiers
Atrial fibrillation algorithm
Age 65 or over
ECG obtained as part of routine clinical care
Structural heart disease algorithm
Disqualifiers
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)
Trial design
Design model
Parallel
Treatments tested in this trial
Risk-Based Assessment for Cardiac Dysfunction
DeviceThe 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.
Treatment groups
1,000 Participants
are divided into 2 treatment groupsGroup A: InterventionExperimental treatment 1 intervention
Group B: ControlNo intervention 0 interventions
Trial outcomes
Primary outcomes
1
Incidence of New Atrial Fibrillation Diagnosis
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.
Time frame
6 months from index ECG2
Incidence of New Structural Heart Disease Diagnosis (Composite)
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.
Time frame
6 months from index ECG3
Incidence of New Cardiovascular Diagnosis (Overall Composite: AF + SHD)
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.
Time frame
6 months from index ECGSecondary outcomes
1
Incidence of New Atrial Fibrillation-Related Therapy (Composite)
Number of participants initiated on one or more of the following after index ECG, identified by EHR medication order/administration record and procedural (CPT) codes: antiarrhythmic medication, atrioventricular (AV) nodal blocking agent, anticoagulant medication, or AF ablation procedure.
Time frame
6 months from index ECG2
Incidence of New Structural Heart Disease-Related Therapy (Composite)
Number of participants initiated on one or more of the following after index ECG, identified by EHR medication order/administration record and procedural (CPT) codes: medication for left ventricular systolic dysfunction (beta blocker, ACE-I/ARB/ARNI, MRA, or SGLT2 inhibitor); valvular heart disease therapy (valve repair or replacement); or new therapy for hypertrophic cardiomyopathy, cardiac amyloidosis, or hypertensive heart disease.
Time frame
6 months from index ECG3
Incidence of Cardiovascular Death
Number of participants who died from a cardiovascular cause, identified by EHR mortality data and/or documented cause of death.
Time frame
6 months from index ECG4
Incidence of Myocardial Infarction
Number of participants with a new myocardial infarction, identified by ICD-10-CM diagnosis code in the EHR.
Time frame
6 months from index ECGOther outcomes
1
Total Cost of Care
Total cost of care per participant managed by Northwestern Medicine clinicians using ECG-based predictive models compared to that of patients managed by Northwestern Medicine clinicians that are not using ECG-based predictive models, in US dollars, calculated from billing and procedural (CPT) codes recorded in the EHR and converted to cost using standard procedural code cost estimates.
Time frame
Up to 5 years from index ECG2
Incidence of Cardiovascular Death, Myocardial Infarction, or Hospitalization for a Cardiovascular Cause (Long-Term)
Number of participants experiencing cardiovascular death, myocardial infarction, or hospitalization for a cardiovascular cause (including heart failure and stroke), identified by EHR mortality data, ICD-10-CM diagnosis codes, and inpatient encounter records.
Time frame
Up to 5 years from index ECGSponsors and contacts
Click on the lead sponsor to view all of their trials.
Northwestern University
Lead sponsor
Tempus AI
Collaborator
Source ClinicalTrials.gov