A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension
Recruiting · NCT07079592 · Interventional (participants receive a specific treatment) · Lead sponsor: National Defense Medical Center, Taiwan
View the official record on ClinicalTrials.gov →Interventions studied
AI-ECG Guidance
What this trial is about
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.
Who can take part
Age range
50 Years to 85 Years
Sex
All (male and female)
Healthy volunteers
No - a diagnosis or condition is required
Phase
Not applicable (e.g. observational or device study)
Study type
Interventional (participants receive a specific treatment)
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
Where it is running
1 location listed.
- National Defense Medical Center - Taipei, Taiwan