Artificial Intelligence Enhanced ECG to Detect Cardiac Amyloidosis

NCT ID: NCT05557162

Last Updated: 2025-10-10

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Clinical Phase

NA

Total Enrollment

20143 participants

Study Classification

INTERVENTIONAL

Study Start Date

2023-06-19

Study Completion Date

2025-12-31

Brief Summary

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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).

Detailed Description

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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.

Conditions

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Cardiac Amyloidosis

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SCREENING

Blinding Strategy

NONE

Study Groups

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Notification of the AI ECG algorithm and the A3E scores

Provider-facing recommendation report that alerts to provider for positive AI ECG Amyloid Score, standardized amyloid order set, diagnostic algorithm and reminders

Group Type EXPERIMENTAL

AI ECG Amyloid algorithm

Intervention Type OTHER

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

Usual Care

No alerts to provider for positive AI ECG Amyloid Score, standardized amyloid order set, diagnostic algorithm and reminders

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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AI ECG Amyloid algorithm

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

Intervention Type OTHER

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Mayo Clinic

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Angela Dispenzieri, MD

Role: PRINCIPAL_INVESTIGATOR

Mayo Clinic

Locations

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Mayo Clinic in Arizona

Scottsdale, Arizona, United States

Site Status

Mayo Clinic in Florida

Jacksonville, Florida, United States

Site Status

Mayo Clinic in Rochester

Rochester, Minnesota, United States

Site Status

Mayo Clinic Health System - Eau Claire

Eau Claire, Wisconsin, United States

Site Status

Countries

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United States

Related Links

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Other Identifiers

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NCI-2024-00928

Identifier Type: REGISTRY

Identifier Source: secondary_id

PREDICT-AMY

Identifier Type: OTHER

Identifier Source: secondary_id

22-005311

Identifier Type: OTHER

Identifier Source: secondary_id

PREDICT-AMY

Identifier Type: -

Identifier Source: org_study_id

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