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Completed

NCT Number: NCT05557162

Artificial Intelligence Enhanced ECG to Detect Cardiac Amyloidosis

The purpose of this study is to assess a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis of cardiac amyloidosis (CA).

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Key information

Conditions

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

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Mayo Clinic in Arizona, Scottsdale, Arizona, United States

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About this study

This pragmatic trial will be the first study to prospectively evaluate the use of the AI ECG dashboard along with an augmented report in everyday practice. The findings will also guide future implementation strategies and inform the translation of many of the current and future AI algorithms into the clinical setting. The participants are the providers. Basic demographic information about the providers will be collected as well as their reactions to the trial based educational guidance supplied to them. Patient health information will be collected on their patients using a HIPPA waiver. There will be no patient contact.

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • Mayo Clinic cardiology or hematology providers who care for adult patients
  • Mayo Clinic providers who consent to participate on this study

Exclusion criteria

  • None

Treatment and study plan

AI ECG Amyloid algorithm

Other

Artificial intelligence enabled electrocardiogram screening tool used to identify the predictive model that best differentiates those at greatest risk for an amyloidosis diagnosis

Primary outcomes

  1. To determine if AI ECG algorithm and enhanced algorithms and education enable earlier diagnosis of cardiac amyloidosis

    Time frame: 1 year

    The number of patients diagnosed with cardiac amyloidosis in cardiology and hematology practices will be compared between those providers undergoing the AI ECG intervention to those randomized to standard practice arm

Secondary outcomes

  1. To determine if AI ECG and enhanced algorithms and education enable earlier diagnosis of cardiac amyloidosis intervention across different practice types (strata)

    Time frame: 1 year

    Performance of AI ECG intervention across cardiology and hematology practices and between community and tertiary facilities will be analyzed by measuring rates of cardiac amyloidosis diagnosis across these strata

  2. To assess provider satisfaction with the AI ECG intervention

    Time frame: 1 year

    For a screening tool to be effective, it has to be user friendly. The providers randomized to the AI ECG intervention arm will be surveyed to understand their experience. This endpoint will be descriptive. Providers will answer a 6 question using a 5-point Likert scale (higher number is more favorable).

  3. To assess differential costs between the intervention arm and the standard of care arm

    Time frame: 1 year

    Upon trial completion, the difference in clinical expenditures between the intervention and standard of care arms will be compared. To this end, the rates of test ordering will be counted and compared between the interventional arm and the standard of care arm. A cost will be assigned to each test to calculate expenditures per correct diagnosis. The test of interest will include: NT-proBNP, troponin, protein electrophoresis with isotyping, serum immunoglobulin free light chains, 24-hour urinary protein with immunofixation, cardiac magnetic resonance imaging, echocardiogram, technetium pyrophosphate nuclear cardiac scintigraphy , endomyocardial biopsy, and fat aspirate.

Sponsors and collaborators

Lead sponsor

Mayo Clinic

Other

Registry information

Official study title

Artificial Intelligence Enhanced ECG to Detect Cardiac Amyloidosis: Protocol for a Pragmatic Cluster Randomized Clinical Trial (PREDICT-AMY)

Important dates

Study start
2023
Primary completion
2025
Study completion
2025
First posted
Sep 27, 2022
Registry last updated
Feb 17, 2026

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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