Skip to main content
OpenTrials
Recruiting

NCT Number: NCT07351656

A Study Of Heart Disease Using AI-Enabled Electrocardiography And Focused Cardiac Ultrasound

A study to evaluate feasibility, diagnostic yield, accuracy, and actionable thresholds of POC, immediate-feedback AI-ECG + AI FoCUS screening for cardiac disease in well described community populations.

Recruiting

Interested in participating?

Request Info

Key information

Age range

15 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Mayo Clinic in Rochester

Rochester, Minnesota, 55905, United States

Location status: Recruiting

Location contact

Amanda Priebe

CONTACT

[email protected]

507-422-6932

Paul Friedman, MD

PRINCIPAL_INVESTIGATOR

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Adolescents and young adults:

Inclusion criteria

  • Enrollment in a high-school, college or a resident in MN during the study period
  • Age 15-29 years
  • Informed consent (and assent for minors)

Exclusion criteria

  • Presence of a pacemaker or defibrillator
  • Inability to obtain a quality ECG tracing

Community dwelling adults:

Inclusion criteria

  • Adult patients (>30 years of age, with pre-specified subgroups 30-64 and 65+))

Exclusion criteria

  • Inability to provide informed consent to participate in the study

Pregnant women:

Inclusion criteria

  • Adult female aged 18 to 49 years
  • Pregnant at the time of enrollment
  • Receiving obstetric care at identified study site(s)
  • Willing and able to provide informed consent

Exclusion criteria

  • Inability to provide consent

Treatment and study plan

Focused Cardiac Ultrasound

Diagnostic Test

Focused cardiac ultrasound will utilize sonography to evaluate specific cardiac conditions, such as ventricular function, pericardial effusion, and valvular abnormalities.

6-Lead AI-ECG

Diagnostic Test

A 6-lead ECG uses six electrodes placed on the chest and limbs to record the heart's electrical activity from multiple perspectives.

12-Lead AI-ECG

Diagnostic Test

A standard 12-lead ECG consists of 12 leads: 6 limb leads and 6 chest (precordial) leads. These leads record the heart's electrical activity from different angles to provide a comprehensive assessment of cardiac function.

Primary outcomes

  1. Percentage of participants with positive AI-ECG findings confirmed by echocardiography (Adolescents and young adults)

    Time frame: 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.

  2. Number of patients with positive AI-ECG detection for left-right sided SHD (Community Dwelling Adults)

    Time frame: 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.

  3. Number of times the AI-ECG provides a correct diagnosis of clinically significant cardiac disease (Pregnant women)

    Time frame: 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.

Secondary outcomes

  1. Number of false positive AI-ECG Results (Adolescents and young adults)

    Time frame: Baseline

    Number of false positive AI-ECG results will be determined by the number of positive AI-ECG results proven false from an echocardiography

  2. Number of positive AI-ECG results for hypertrophic cardiomyopathy (HCM) (Adolescents and young adults)

    Time frame: Baseline

    The number of positive AI-ECG results for HCM will be based on how many patient ECGs indicate a possible diagnosis of HCM

  3. Number of positive AI-ECG results for congenital heart defect (CHD) (Adolescents and young adults)

    Time frame: Baseline

    The number of positive AI-ECG results for CHD will be based on how many patient ECGs indicate a possible diagnosis of CHD

  4. Proportion of patients by age group to receive a diagnosis (Community Dwelling Adults)

    Time frame: Baseline

    Proportion of patients by age group (30-39, 40-49, 50-65, 65-74, and 75 years and older) to receive a diagnosis from ultrasound that is confirmed by a comprehensive diagnostic work up.

  5. Proportion of total patients to receive a diagnosis based on screening with 6 lead ECG (Community Dwelling Adults)

    Time frame: Baseline

    Proportion of total patients to receive a diagnosis based on screening with 6 lead ECG will be determined by the number of patients to have a correct diagnosis using the 6 lead ECG confirmed by echocardiogram compared to the total number of patients.

  6. Proportion of total patients to receive a diagnosis based on screening with 12 lead ECG (Community Dwelling Adults)

    Time frame: Baseline

    Proportion of total patients to receive a diagnosis based on screening with 12 lead ECG will be determined by the number of patients to have a correct diagnosis using the 12 lead ECG confirmed by echocardiogram compared to the total number of patients.

  7. Proportion of total patients to receive a diagnosis based on screening with 12 lead only AI-ECG with adjunctive FoCUS (Community Dwelling Adults)

    Time frame: Baseline

    Proportion of total patients to receive a diagnosis based on screening with 12 lead only AI-ECG with adjunctive FoCUS will be determined by the number of patients to have a correct diagnosis using the 12 lead ECG with adjunctive FoCUS confirmed by standard of care echocardiogram compared to the total number of patients.

  8. Proportion of total patients to receive a diagnosis based on screening with 12 lead only AI-ECG without adjunctive FoCUS (Community Dwelling Adults)

    Time frame: Baseline

    Proportion of total patients to receive a diagnosis based on screening with 12 lead only AI-ECG without adjunctive FoCUS will be determined by the number of patients to have a correct diagnosis using the 12 lead ECG without adjunctive FoCUS confirmed by standard of care echocardiogram compared to the total number of patients.

  9. Number of non-cardiac adverse events (Pregnant Women)

    Time frame: Baseline

    Number of non-cardiac adverse events can include hypertensive disorders of pregnancy (gestational hypertension, pre-eclampsia, eclampsia), preterm delivery, gestational diabetes, small for gestational age delivery, placental abruption, and pregnancy loss.

Study contacts

Contact information is provided by the study sponsor or research team.

Amanda Priebe

CONTACT

[email protected]

507-422-6932

Sponsors and collaborators

Lead sponsor

Mayo Clinic

Other

Registry information

Official study title

Screening for Heart Disease Using AI-Enabled Electrocardiography and Focused Cardiac Ultrasound: the AI CVD Screen Study.

Important dates

Study start
2026
Primary completion
2028
Study completion
2028
First posted
Jan 20, 2026
Registry last updated
May 14, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.