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AI eyes hidden heart condition: could algorithms catch what doctors miss?

NCT ID NCT07062848

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing This study
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jul 29, 2026 · Last updated Jul 30, 2026 · Updated 1 time

Summary

This study is testing whether artificial intelligence can detect transthyretin amyloid cardiomyopathy (ATTR-CM), a serious and often underdiagnosed heart condition, earlier than usual. Researchers will use AI algorithms to analyze routine ECGs and heart ultrasounds from up to 1.5 million people aged 50 to 95 across diverse US health systems. The goal is to see how common the condition really is and whether the AI tools can reliably flag it.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
an artificial intelligence toolkit that analyzes ECGs and ultrasounds to detect signs of transthyretin amyloid cardiomyopathy
What this could lead to
If successful, this AI approach could enable earlier, faster detection of a underdiagnosed heart condition, potentially improving outcomes for thousands of patients.
What could go wrong
This is an observational study, not a treatment trial. The AI algorithms may not perform equally well across all populations or healthcare settings.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 1,500,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

Jan 2025

Expected to finish

Jan 2027

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

The study will include US adults ages 50-95 with at least one retrievable ECG and/or 2D echo file from HER.

Ages

50 to 95 years

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Broad inclusion and exclusion criteria across all 3 objectives: Inclusion Criteria: * Age 50-95 * At least one retrievable ECG and/or 2D echo file (DICOM or equivalent video file) from EHR. Exclusion Criteria: * Unavailable key demographics (age, gender, race, ethnicity) * Individuals who have opted out of research studies Objective-specific inclusion and exclusion criteria: Primary Objective: Additional exclusion criteria: * For subgroup analyses: when evaluating the prevalence of probable ATTR-CM status across demographic groups, we will exclude those with missing baseline demographic information (age, sex, race, geographic region). Secondary Objective 1: Additional inclusion criteria: * 'Cases': ATTR-CM diagnosis defined by ICD-10 codes (Table 1) OR abnormal bone scintigraphy testing consistent with ATTR-CM OR treatment with an approved transthyretin stabilizer or other ATTR-CM-specific therapy * 'Controls': any individuals not meeting the case definition. In these participants, we will consider all eligible ECG, POCUS, or TTE studies performed up to 12 months before diagnosis (first date of ICD code appearance, abnormal bone scintigraphy or treatment onset, whichever happened first) and any time after. 'Controls' will be drawn from ECGs, POCUS, or TTE studies performed in individuals not meeting the 'case' criteria above, including individuals who have never undergone dedicating testing or those who underwent e.g., bone scintigraphy, but with negative (or equivocal) findings. Secondary Objective 2: Additional inclusion criteria: * Having at least two years of follow-up time between the index test (ECG, POCUS, or TTE) and the date of analysis. * Having at least one healthcare encounter every two years across care settings from their first entry into the cohort through death or end of the follow-up period.

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Conditions

The condition(s) this trial relates to.

Amyloid Neuropathies, Familial wild type ATTR amyloidosis

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Contacts and locations

Locations

  • Henry Ford Health

    Detroit, Michigan, 48202, United States

  • Houstin Methodist

    Houston, Texas, 77030, United States

  • Medical University of South Carolina (MUSC) Health

    Charleston, South Carolina, 29425, United States

  • Montefiore

    The Bronx, New York, 10467, United States

  • Mount Sinai

    New York, New York, 10029, United States

  • Providence Health

    Tigard, Oregon, 97224, United States

  • The University of Chicago

    Chicago, Illinois, 60637, United States

  • UT Southwestern Medical Center

    Dallas, Texas, 75390, United States

  • University of California - San Francisco (UCSF) Health

    San Francisco, California, 94143, United States

  • University of Virginia School of Medicine

    Charlottesville, Virginia, 22903, United States

  • University of Washington Medicine

    Seattle, Washington, 98195, United States

  • Yale New Haven Health System

    New Haven, Connecticut, 06519, United States

More trials for these conditions

Other studies related to the condition(s) this trial covers.