Study of Heart Disease Using AI-Enabled Electrocardiography and Focused Cardiac Ultrasound
This study is looking at new ways to screen for heart disease using artificial intelligence (AI). It will use two diagnostic tests: Focused Cardiac Ultrasound (an ultrasound to look at your heart) and AI-ECG (a heart tracing test that uses AI to help read the results). There are two types of AI-ECG being tested: 6-Lead AI-ECG and 12-Lead AI-ECG. The study wants to see how well these AI-powered tests can find heart problems in different groups of people, including adolescents, young adults, and pregnant women. They are looking for how many people with positive AI-ECG results also have heart problems confirmed by a standard echocardiogram (another type of heart ultrasound). You might be able to join if you are 15 years or older, and meet specific criteria for your age group, such as being enrolled in school or living in Minnesota. The study is currently recruiting a large number of participants.
- Study design
- This is an interventional study planning to enroll 19,300 participants. It is designed to evaluate the usefulness and accuracy of AI-powered screening tools for heart disease.
- What's involved
- Not specified in the trial record.
- Compensation
- Not stated in the trial record.
- Follow-up
- The primary outcomes are measured at Baseline, meaning at the start of your participation.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
A Study Of Heart Disease Using AI-Enabled Electrocardiography And Focused Cardiac Ultrasound
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- Paul Friedman, MD · PRINCIPAL_INVESTIGATOR · Mayo Clinic
Who to contact
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Do you actually qualify for this trial?
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Inclusion
Exclusion
What this trial measures
- Percentage of participants with positive AI-ECG findings confirmed by echocardiography (Adolescents and young adults)Baseline
The percentage will be calculated as the number of participants whose AI-ECG results indicate a positive finding and are subsequently confirmed by echocardiography, divided by the total number of participants assessed, multiplied by 100.
- Number of patients with positive AI-ECG detection for left-right sided SHD (Community Dwelling Adults)Baseline
Number of patients with positive AI-ECG detection for left-right sided SHD, defined as any of the following: LVEF \<50%, \>moderate right ventricular systolic dysfunction, \>moderate aortic, mitral, or tricuspid valve regurgitation or stenosis, pulmonary hypertension (right ventricular systolic pressure \> 50 mmHg), or elevated left-sided filling pressure.
- Number of times the AI-ECG provides a correct diagnosis of clinically significant cardiac disease (Pregnant women)Baseline
Diagnostic performance of the AI-ECG will be determined by the accurate diagnosis of cardiomyopathy (left ventricular ejection fraction \[LVEF\] ≤50% or 10% or more decline in LVEF) or clinically significant structural heart disease (SHD; ≥ moderate right ventricular systolic dysfunction, ≥ moderate aortic, mitral, or tricuspid valve regurgitation or stenosis, pulmonary hypertension \[right ventricular systolic pressure \> 50 mmHg\], or myocardial disease such as hypertrophic cardiomyopathy) in pregnant patients and those up to 6 weeks postpartum compared to standard of care.