AI spots silent heart condition in seconds
NCT ID NCT06469372
First seen Jun 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This study tested a computer model that uses a patient's age, sex, medical history, and heart tests (ECG and echocardiogram) to estimate their risk of having cardiac amyloidosis, a serious but often undiagnosed heart condition. Researchers invited 50 high-risk patients for further testing to see if the model could find new cases. The goal is to see if this AI tool can help doctors catch the disease earlier than usual.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- Active substance
- deep learning model (device)
- What this could lead to
- If successful, this could lead to earlier detection of cardiac amyloidosis, a serious heart condition that is often missed.
- What could go wrong
- This is a small, single-center study with only 50 participants. The model may not work as well in other populations or 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.
- Phase
-
Not a phased trial
Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.
- Participants
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50 people
The number who actually took part.
- Started
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May 2024
- Finished
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Aug 2025
- Lead sponsor
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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.
- Ages
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50 years and older
- Sex
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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 Hide 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.
Inclusion Criteria: * High predicted probability of having cardiac amyloidosis as determined by deep learning model. * Age ≥ 50 years. * Electronically stored ECG and echocardiogram within 5 years of study start date. * Ability for the patient or health care proxy to understand and sign the informed consent after the study has been explained. Exclusion Criteria: * Primary amyloidosis (AL) or secondary amyloidosis (AA). * Prior liver or heart transplantation. * Active malignancy or non-amyloid disease with expected survival of less than 1 year. * Previous testing for cardiac amyloidosis such as amyloid nuclear scintigraphy, cardiac, or fat pad biopsy. * Impairment from stroke, injury or other medical disorder that precludes participation in the study. * Disabling dementia or other mental or behavioral disease * Nursing home resident.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Locations
-
Columbia University Irving Medical Center / NewYork-Presbyterian Hospital
New York, New York, 10032, United States
More trials for these conditions
Other studies related to the condition(s) this trial covers.
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- Heart ultrasound may spot a rare heart disease earlier
- A sharper eye on amyloid: could quantitative scans revolutionize cardiac monitoring?
- Can a new PET tracer light up amyloid in the heart?
- Liver clues: a new way to stage heart amyloidosis?
- A carpal tunnel clue to a silent heart threat?