A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension (ADDPH)

February 23, 2026 updated by: Pang-Yen, Liu, National Defense Medical Center, Taiwan

A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension: A Randomized Controlled Trial

This study aims to validate the use of an artificial intelligence-enabled electrocardiogram (AI-ECG) to screen for elevated PAP. We hypothesize that the AI-ECG model can early identify patients with pulmonary hypertension in high-risk patients, prompting further evaluation through echocardiography, potentially resulting in improving cardiovascular outcomes.

Study Overview

Detailed Description

Pulmonary hypertension is often underdiagnosed due to extensive category of etiology. The diagnosis and treatment of pulmonary hypertension have changed dramatically through the re-defined diagnostic criteria and advanced drug development in the past decade. The application of Artificial Intelligence for the detection of elevated pulmonary arterial pressure (ePAP) was reported recently. An AI model based on electrocardiograms (ECG) has shown promise in not only detecting ePAP but also in predicting future risks related to cardiovascular mortality.

Study Type

Interventional

Enrollment (Estimated)

8666

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Chin Lin, Associate Professor
  • Phone Number: 16118 886+2-87923311
  • Email: up6fup0629@gmail.com

Study Locations

      • Taipei, Taiwan
        • Recruiting
        • National defense medical center
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Men or women, ≥ 50 to 85 years of age
  • At least one 12-lead ECG within 3 months

Exclusion Criteria:

  • A diagnosis of PH WHO Groups 1, 2, 3, 4, or 5
  • A diagnosis of hypertrophic cardiomyopathy, restrictive cardiomyopathy, constrictive pericarditis, cardiac amyloidosis, or infiltrative cardiomyopathy
  • Prior heart, lung, or heart-lung transplants
  • Any systolic pulmonary artery pressure >50 mmHg by echocardiography before
  • Echocardiography in 3 months before index ECG

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: AI-ECG guidance
Participants in this arm undergo screening using the AI-ECG system. Those identified as high-risk for pulmonary hypertension receive echocardiography to confirm the diagnosis and guide subsequent management.
Participants undergo screening using the AI-ECG system. Those identified as high-risk for pulmonary hypertension receive echocardiography to confirm the diagnosis and guide subsequent management.
No Intervention: Standard clinical care
Participants in this arm are screened using the AI-ECG system, but diagnosis and management follow the usual clinical practice without echocardiography.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Pulmonary arterial pressure > 50 mmHg
Time Frame: 90 days
The composite endpoint is defined as detecting pulmonary hypertension > 50mmHg by echocardiography, indicating high risk for pulmonary hypertension.
90 days

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Left atrial enlargement on a parasternal long axis view
Time Frame: Within 90 days after randomization.
The endpoint measures the size of left atrium > 40mm on a parasternal long axis view by echocardiography.
Within 90 days after randomization.
Left atrial enlargement by left atrium volume index
Time Frame: Within 90 days after randomization.
The endpoint measures the size of left atrium volume index > 29 mL/m2 in sinus rhythm or > 40 mL/m2 in AF by echocardiography.
Within 90 days after randomization.
Right ventricular enlargement on a parasternal long axis view
Time Frame: Within 90 days after randomization.
The endpoint measures the size of right ventricular basal dimension > 27mm by echocardiography.
Within 90 days after randomization.
New onset of left ventricular dysfunction
Time Frame: Within 90 days after randomization.
The endpoint measures the number and proportion of LVEF < 50%.
Within 90 days after randomization.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Study Director: Chin Lin, associate professor, National Defense Medical Center, Taiwan

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

February 1, 2026

Primary Completion (Estimated)

June 15, 2026

Study Completion (Estimated)

June 15, 2026

Study Registration Dates

First Submitted

July 14, 2025

First Submitted That Met QC Criteria

July 14, 2025

First Posted (Actual)

July 23, 2025

Study Record Updates

Last Update Posted (Actual)

February 24, 2026

Last Update Submitted That Met QC Criteria

February 23, 2026

Last Verified

December 1, 2025

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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