Notification of the AI ECG algorithm and the A3E scores for Cardiac Amyloidosis

Phase-Based Progress Estimates
Cardiac Amyloidosis+1 More
AI ECG Amyloid algorithm - Other
All Sexes
What conditions do you have?

Study Summary

This trial assesses whether a new AI-based tool can improve the diagnosis of cardiac amyloidosis, a heart condition.

Eligible Conditions
  • Cardiac Amyloidosis

Treatment Effectiveness

Study Objectives

1 Primary · 3 Secondary · Reporting Duration: 1 year

1 year
To assess differential costs between the intervention arm and the standard of care arm
To determine if AI ECG algorithm and enhanced algorithms and education enable earlier diagnosis of cardiac amyloidosis

Trial Safety

Trial Design

2 Treatment Groups

Usual Care
1 of 2
Notification of the AI ECG algorithm and the A3E scores
1 of 2

Active Control

Experimental Treatment

200 Total Participants · 2 Treatment Groups

Primary Treatment: Notification of the AI ECG algorithm and the A3E scores · No Placebo Group · N/A

Notification of the AI ECG algorithm and the A3E scores
Experimental Group · 1 Intervention: AI ECG Amyloid algorithm · Intervention Types: Other
Usual CareNoIntervention Group · 1 Intervention: Usual Care · Intervention Types:

Trial Logistics

Trial Timeline

Screening: ~3 weeks
Treatment: Varies
Reporting: 1 year

Who is running the clinical trial?

Mayo ClinicLead Sponsor
2,893 Previous Clinical Trials
3,698,466 Total Patients Enrolled
1 Trials studying Cardiac Amyloidosis
100 Patients Enrolled for Cardiac Amyloidosis
Angela Dispenzieri, MDPrincipal InvestigatorMayo Clinic
3 Previous Clinical Trials
156 Total Patients Enrolled

Eligibility Criteria

Age 18+ · All Participants · 5 Total Inclusion Criteria

Mark “Yes” if the following statements are true for you:
You are a patient of Mayo Clinic cardiology or hematology providers who care for adult patients.

About The Reviewer

Michael Gill preview

Michael Gill - B. Sc.

First Published: October 19th, 2021

Last Reviewed: November 19th, 2022

Michael Gill holds a Bachelors of Science in Integrated Science and Mathematics from McMaster University. During his degree he devoted considerable time modeling the pharmacodynamics of promising drug candidates. Since then, he has leveraged this knowledge of the investigational new drug ecosystem to help his father navigate clinical trials for multiple myeloma, an experience which prompted him to co-found Power Life Sciences: a company that helps patients access randomized controlled trials.