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NCT Number: NCT07062848

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.

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).

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This study is active but is not currently recruiting participants.

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Key information

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Broad inclusion and exclusion criteria across all 3 objectives:

Inclusion criteria

  • Age 50-95
  • At least one retrievable ECG and/or 2D echo file (DICOM or equivalent video file) from EHR.

Exclusion criteria

  • Unavailable key demographics (age, gender, race, ethnicity)
  • Individuals who have opted out of research studies

Objective-specific inclusion and exclusion criteria:

Primary Objective:

Additional exclusion criteria:

  • 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:

Additional inclusion criteria:

  • '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:

Additional inclusion criteria:

  • 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.

Treatment and study plan

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)

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

    Time frame: At enrollment

Secondary outcomes

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

    Time frame: At enrollment

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

    Time frame: At enrollment

Sponsors and collaborators

Lead sponsor

Yale University

Other

Collaborators

  • Bridgebio Pharma, Inc

Registry information

Official study title

The Transthyretin Amyloid Cardiomyopathy Early Detection With Artificial Intelligence (TRACE-AI) Network Study

Acronym: TRACE Network

Important dates

Study start
2025
Primary completion
2027
Study completion
2027
First posted
Jul 14, 2025
Registry last updated
Jul 14, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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