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An Observational Study Using Artificial Intelligence (AI) Algorithms on Electrocardiography (ECG), Point-of-care Ultrasound (POCUS), and Transthoracic Echocardiophy (TTE) to Estimate the Under-diagnosis of Transthyretin Amyloid Cardiomyopathy (ATTR-CM) Across a Diverse Range of US Health Systems.

NCT07062848 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1500000

Last updated 2025-07-14

No results posted yet for this study

Summary

This is a multi-center, observational study with the overall objective to examine the scale of under-diagnosis for transthyretin amyloid cardiomyopathy (ATTR-CM) across a broad range of diverse health systems in the US using a fully federated deployment of an artificial intelligence (AI) toolkit of algorithms that detect ATTR-CM on electrocardiography (ECG), point-of-care ultrasound (POCUS), and transthoracic echocardiography (TTE).

Conditions

  • Transthyretin (TTR) Amyloid Cardiomyopathy

Interventions

DIAGNOSTIC_TEST

AI Toolkit for ATTR-CM Diagnosis

An artificial intelligence (AI) toolkit of algorithms that detect ATTR-CM on electrocardiography (ECG), point-of-care ultrasound (POCUS), and transthoracic echocardiography (TTE)

Sponsors & Collaborators

  • Bridgebio Pharma, Inc

    collaborator UNKNOWN

  • Yale University

    lead OTHER

Principal Investigators

  • Rohan Khera, MD, MS · Yale University

Eligibility

Min Age
50 Years
Max Age
95 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-01-24
Primary Completion
2027-01-31
Completion
2027-01-31

Countries

  • United States

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07062848 on ClinicalTrials.gov