Smartphone ECG with AI could spot hidden heart disease in families
NCT ID NCT06609174
First seen Nov 05, 2025 · Last updated Jun 23, 2026 · Updated 31 times
Summary
This pilot study tested whether a portable 6-lead ECG device, paired with an artificial intelligence algorithm, can help screen first-degree relatives of people with dilated cardiomyopathy (a weakened heart muscle). The goal was to see if this mobile approach could detect reduced heart function early. The study enrolled 119 participants and measured how many relatives completed the screening and how many had a low ejection fraction (≤45%).
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the original study
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Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
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Contacts and locations
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Locations
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Mayo Clinic in Rochester
Rochester, Minnesota, 55905, United States
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
Active substance
KardiaRx 6-lead ECG device with AI interpretation
What this could lead to
If successful, this approach could make it easier and more accessible to screen at-risk family members for early signs of heart muscle disease.
What could go wrong
This is a small pilot study with only 119 participants, so results may not apply to everyone. The AI algorithm's accuracy in detecting reduced heart function needs further validation.
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.