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 | Active Not Recruiting

• 1 other identifier: 2000039184
• Study Type: observational
• Target: 1,500,000
• Locations: 1 country
• Sites: 11

Brief 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

Keywords

artificial intelligence; AI-ECG; AI-Echo; cardiac amyloidosis; transthyretin amyloid cardiomyopathy

Outcome Measures

Primary Outcomes (1)

• To describe the prevalence of probable AI-defined ATTR-CM in defined cohorts of individuals who have undergone standard cardiovascular investigations across a diverse network of US-based health care delivery systems

  At enrollment

Secondary Outcomes (2)

• Validate the diagnostic performance of AI-enabled ECG, POCUS, and TTE algorithms for ATTR-CM

  At enrollment

• To examine the association between the AI-defined probability of ATTR-CM and the incidence of adverse cardiovascular events

  At enrollment

Interventions

AI Toolkit for ATTR-CM Diagnosis DIAGNOSTIC_TEST

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

Eligibility Criteria

• Age: 50 Years - 95 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

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

You may not qualify if:

• Age 50-95
• At least one retrievable ECG and/or 2D echo file (DICOM or equivalent video file) from EHR.
• Unavailable key demographics (age, gender, race, ethnicity)
• Individuals who have opted out of research studies
• Primary Objective:
• 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:
• '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:
• 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.

Sponsors & Collaborators

• Yale University: lead
• Bridgebio Pharma, Inc: collaborator

Study Sites (11)

University of California - San Francisco (UCSF) Health

San Francisco, California, 94143, United States

Location

Yale New Haven Health System

New Haven, Connecticut, 06519, United States

Location

Henry Ford Health

Detroit, Michigan, 48202, United States

Location

Mount Sinai

New York, New York, 10029, United States

Location

Duke Health

Durham, North Carolina, 27710, United States

Location

Providence Health

Tigard, Oregon, 97224, United States

Location

Medical University of South Carolina (MUSC) Health

Charleston, South Carolina, 29425, United States

Location

UT Southwestern Medical Center

Dallas, Texas, 75390, United States

Location

Houstin Methodist

Houston, Texas, 77030, United States

Location

University of Virginia School of Medicine

Charlottesville, Virginia, 22903, United States

Location

University of Washington Medicine

Seattle, Washington, 98195, United States

Location

MeSH Terms

Conditions

Amyloid Neuropathies, Familial

Condition Hierarchy (Ancestors)

Heredodegenerative Disorders, Nervous System; Neurodegenerative Diseases; Nervous System Diseases; Amyloid Neuropathies; Peripheral Nervous System Diseases; Neuromuscular Diseases; Genetic Diseases, Inborn; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Amyloidosis, Familial; Metabolism, Inborn Errors; Metabolic Diseases; Nutritional and Metabolic Diseases; Amyloidosis; Proteostasis Deficiencies

Study Officials

• Rohan Khera, MD, MS

  Yale University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 3, 2025
• First Posted: July 14, 2025
• Study Start: January 24, 2025
• Primary Completion (Estimated): January 1, 2027
• Study Completion (Estimated): January 1, 2027
• Last Updated: July 14, 2025

Record last verified: 2025-07

Locations

US (11)