The VALVE-AI Trial

NCT07023510 | Recruiting

• 1 other identifier: VALVE-AI RCT
• Study Type: interventional
• Target: 8,648
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this clinical trial is to learn if an artificial intelligence-powered electrocardiogram (AI-ECG) can help detect moderate or severe valvular heart diseases (VHD) in adults. The main question it aims to answer is: ．Can AI-ECG screening identify patients with significant heart valve diseases who may benefit from early echocardiography? Researchers will compare the rate of moderate or severe VHD detection between the experimental group and the control group to see if AI-ECG improve the detection rate of significant VHD. Participants will:

• Be classified as high- or low-risk for VHD using an AI-ECG system
• In the experimental group, high-risk participants will receive echocardiography based on AI-ECG results
• In the control group, usual clinical care will be provided without routine echocardiography for AI-ECG high-risk results.

Conditions

Valvular Heart Disease Patients

Outcome Measures

Primary Outcomes (1)

• Composite of Any Moderate or Severe VHD by Echocardiography

  The composite endpoint is defined as detecting any moderate or severe VHD by echocardiography, including mitral regurgitation (MR), aortic regurgitation (AR), aortic stenosis (AS), and tricuspid regurgitation (TR).

  Within 90 days after randomization.

Secondary Outcomes (5)

• Number of Participants with Moderate or Severe MR by Echocardiography

  Within 90 days after randomization.

• Number of Participants with Moderate or Severe AR by Echocardiography

  Within 90 days after randomization.

• Number of Participants with Moderate or Severe AS by Echocardiography

  Within 90 days after randomization.

• Number of Participants with Moderate or Severe TR by Echocardiography

  Within 90 days after randomization.

• Number of Participants with Other Cardiac Diseases by Echocardiography

  Within 90 days after randomization.

Study Arms (2)

AI-ECG

EXPERIMENTAL

Participants whose electrocardiogram is classified as high-risk for moderate or severe valvular heart disease (VHD) by the artificial intelligence-powered electrocardiogram (AI-ECG) system will receive additional transthoracic echocardiography, regardless of whether the treating physician suspects VHD based on symptoms or physical examination. Low-risk participants continue with routine care without additional intervention.

Diagnostic Test: AI-ECG driven echocardiography

Usual care

NO INTERVENTION

Participants whose electrocardiogram is classified as high-risk for moderate or severe valvular heart diseases (VHD) by the artificial intelligence-powered electrocardiogram (AI-ECG) system receive standard care according to routine clinical practice. Transthoracic echocardiography is arranged only if the treating physician deems it clinically necessary based on the symptoms, physical examination, , or other non-AI findings. Low-risk participants continue with routine care without additional intervention.

Interventions

AI-ECG driven echocardiography DIAGNOSTIC_TEST

The intervention utilizes a previously validated deep learning model based on 12-lead electrocardiogram (ECG) data to screen for moderate-to-severe valvular heart diseases (VHD). The model processes raw ECG signals and integrates age and sex to enhance prediction. (doi: 10.18632/aging.205835.) Participants identified as high-risk for any moderate-to-severe VHD by the algorithm of artificial intelligence-powered electrocardiogram (AI-ECG) in this intervention arm will receive transthoracic echocardiography to confirm diagnosis and guide further management.

AI-ECG

Eligibility Criteria

• Age: 60 Years - 85 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• At least one 12-lead ECG within 1 year
• Age 60-85 years of age

You may not qualify if:

• Documented echocardiography within 3 years before indexed ECG
• Any known valvular heart disease
• History of any valvular surgery
• Post-heart transplant

Sponsors & Collaborators

• National Defense Medical Center, Taiwan: lead

Study Sites (1)

Tri-Service General Hospital

Taipei, Taiwan

RECRUITING

Related Publications (1)

• Lin YT, Lin CS, Tsai CS, Tsai DJ, Lou YS, Fang WH, Lee YT, Lin C. Comprehensive clinical application analysis of artificial intelligence-enabled electrocardiograms for screening multiple valvular heart diseases. Aging (Albany NY). 2024 May 16;16(10):8717-8731. doi: 10.18632/aging.205835. Epub 2024 May 16.

  PMID: 38761181 BACKGROUND

Central Study Contacts

Chin Lin

CONTACT

+886-2-8792-3100; xup6fup0629@gmail.com

Yu-Lan Liu

CONTACT

+886-2-87923311; cylgist80131@gmail.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: SCREENING
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Doctor of Medicine

Study Record Dates

• First Submitted: June 8, 2025
• First Posted: June 17, 2025
• Study Start: July 1, 2025
• Primary Completion (Estimated): July 1, 2026
• Study Completion (Estimated): July 1, 2026
• Last Updated: June 26, 2025

Record last verified: 2025-06

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)