A Deep-Learning-Enabled Electrocardiogram and Chest X-Ray for Detecting Pulmonary Arterial Hypertension.
Pang-Yen Liu, Shi-Chue Hsing, Dung-Jang Tsai...
https://pubmed.ncbi.nlm.nih.gov/39136826Actively Recruiting
Phase Not Applicable
Age: 50Years - 85Years
All Genders
ID07079592
A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension: A Randomized Controlled Trial
Led by National Defense Medical Center, Taiwan · Updated on 2026-02-24
8666
Participants Needed
1
Research Sites
N/A
Total Duration
On this page
AI-Summary
What this Trial Is About
Pulmonary hypertension is a condition that is often underdiagnosed due to its many causes. Researchers are evaluating an artificial intelligence-enabled electrocardiogram (AI-ECG) to screen for elevated pulmonary arterial pressure (PAP) in patients at high risk. This approach aims to identify pulmonary hypertension earlier, leading to further testing and potentially improving heart-related outcomes. The study is a randomized controlled trial sponsored by the National Defense Medical Center, Taiwan. Participants are divided into two groups. One group is screened with the AI-ECG system, and if they are identified as high-risk for pulmonary hypertension, they receive an echocardiogram to confirm the diagnosis and help guide treatment. The other group undergoes AI-ECG screening but continues with usual clinical care without additional echocardiography. The study uses this comparison to assess the value of AI-ECG-guided screening. During the study, participants will have ECGs and may have echocardiograms depending on their group and risk. Researchers will monitor heart measurements like pulmonary arterial pressure, left atrial size, right ventricular size, and left ventricular function within 90 days after starting the study. The main focus is on whether pulmonary arterial pressure exceeds 50 mmHg. The study lasts at least three months from randomization, with detailed heart imaging and function assessments to understand the AI-ECG's effectiveness in detecting pulmonary hypertension early.
CONDITIONS
Brief Title
A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension
Who Can Participate
Age: 50Years - 85Years
All Genders
Eligibility Criteria
You may qualify if you...
- Men or women aged 50 to 85 years
- At least one 12-lead ECG performed within the past 3 months
You will not qualify if you...
- Diagnosis of pulmonary hypertension WHO Groups 1, 2, 3, 4, or 5
- Diagnosis of hypertrophic cardiomyopathy, restrictive cardiomyopathy, constrictive pericarditis, cardiac amyloidosis, or infiltrative cardiomyopathy
- Prior heart, lung, or heart-lung transplant
- Systolic pulmonary artery pressure greater than 50 mmHg by echocardiography before enrollment
- Echocardiography performed within 3 months before the index ECG
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
1
2
3
Your Study Journey
Screening
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Diagnostic Evaluation
Duration - Up to 90 days after randomization
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.
1 to 2 visits depending on risk assessment
Long-term Monitoring
Duration - Up to 90 days after randomization
Participants are monitored for pulmonary arterial pressure and cardiac function changes within 90 days after randomization.
Follow-up visits as scheduled within 90 days
Trial Site Locations
Total: 1 location
1
National Defense Medical Center
Taipei, Taiwan
Actively Recruiting
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Research Team
C
Chin Lin, Associate Professor
How is the study designed?
Study Type
INTERVENTIONAL
Masking
NONE
Allocation
RANDOMIZED
Model
PARALLEL
Primary Purpose
DIAGNOSTIC
Number of Arms
2
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