Home-based Outpatient Multicenter Evaluation Using Electrocardiogram (HOME-ECG)

Prospective Multicenter Validation of a Home-Based Artificial Intelligence Enabled Single-Lead Electrocardiogram for Detecting Low Ejection Fraction and Structural Heart Disease

This prospective multicenter observational study will validate the accuracy of a previously developed artificial intelligence-enabled single-lead electrocardiogram (AI-ECG) model for identifying low ejection fraction and other structural heart disease phenotypes. Adult participants receiving a model-compatible single-lead electrocardiogram (ECG) (Apple Watch and QOCA ECG102D) and transthoracic echocardiography at five hospitals in Taiwan will be enrolled between March 1, 2026 and June 30, 2026. Model predictions will be compared with echocardiographic reference standards obtained within 30 days after the index ECG.

Inclusion Criteria:

• Age 20 years or older
• Single-lead ECG recorded using a study-compatible device
• Ability to comply with study procedures and, when applicable, provide informed consent according to local institutional review board (IRB) requirements
• No transthoracic echocardiography performed within 90 days before the index ECG

Exclusion Criteria:

• ECG signal quality insufficient for prespecified AI analysis
• No transthoracic echocardiography available within 30 days after the index ECG
• Echocardiography unavailable or technically inadequate for determining left ventricular ejection fraction (EF)