AI-guided echocardiogram screening for cardiac amyloidosis

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This observational study evaluates the effectiveness of an artificial intelligence algorithm, EchoNet-LVH, in identifying patients at high risk for cardiac amyloidosis through echocardiographic screening. The study aims to enhance the accuracy of cardiac disease diagnosis by leveraging machine learning techniques to detect features that may be overlooked by human experts. By improving the identification of cardiac hypertrophy, the study seeks to facilitate timely and appropriate treatment for patients who may benefit from further screening. The approach addresses the limitations of traditional echocardiography, which can be subjective and variable among providers.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* Patients who have a high suspicion for cardiac amyloidosis by AI algorithm

Exclusion Criteria:

* Patients who decline to be seen at specialty clinic
* Patients who have passed away

Where it's running

• Cedars-Sinai Medical Centre (Los Angeles)
  Los Angeles, California, United States Recruiting

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

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• Higher pacemaker rate for people with cardiac amyloidosis

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• Using [64Cu]FBP8 PET/MR to find intracardiac blood clots in cardiac amyloidosis

  We'll test whether a [64Cu]FBP8 PET/MR scan can find blood clots inside the heart of people with cardiac amyloidosis who have atrial fibrillation or atrial flutter.

  Recruiting Phase 3 Brigham and Women's Hospital · Boston, Massachusetts · NCT07560306

• Chest pain screening for hidden cardiac amyloidosis

  We will test whether men over 65 who have chest pain but no coronary artery disease might have hidden cardiac amyloidosis using blood and urine tests, ECG and echocardiography, bone scintigraphy, and sometimes a heart biopsy.

  Recruiting Copenhagen University Hospital, Rigshospitalet · Copenhagen · NCT07435168

• Using advanced heart MRI to improve diagnosis and risk prediction for rare cardiomyopathies

  This project tests whether advanced cardiac MRI techniques can help diagnose and predict future risk for people with rare heart muscle diseases like Danon, Fabry, cardiac amyloidosis, Noonan syndrome, and cardiac sarcoidosis.

  Recruiting Chinese Academy of Medical Sciences, Fuwai Hospital · Beijing · NCT07336394

How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.