NCT07536932

Triage and Recognition of Acute Aortic Dissection in Chest Pain by Electrocardiogram-Artificial Intelligence

A Multicenter Prospective Study to Develop and Validate an Artificial Intelligence-Based Electrocardiogram Model for the Diagnosis of Acute Type A Aortic Dissection in Patients Presenting With Chest Pain

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 10,000 (estimated)
• Sponsor: Shanghai Zhongshan Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 80 Years
• Healthy volunteers: Not accepted

Summary

The goal of this prospective multicenter observational study is to learn whether an artificial intelligence model based on electrocardiograms (ECGs) can help diagnose acute type A aortic dissection (TAAD) in adults who come to the emergency department with chest pain or related symptoms. The main question it aims to answer is: Can the AI-ECG model accurately distinguish TAAD from other causes of chest pain in a real-world emergency setting? Researchers will compare the AI model's ECG-based predictions with the final diagnosis confirmed by computed tomographic angiography (CTA), which is the reference standard. Participants will undergo routine emergency ECG testing and subsequent diagnostic evaluation as part of standard care. Clinical and ECG data will be collected from five tertiary hospitals, and the model's diagnostic performance will be assessed across centers.

Conditions

• Aortic Dissection Type A
• Chest Pain

Timeline

• Start date: 2026-04-01
• Primary completion: 2026-12-01
• Completion: 2026-12-01
• First posted: 2026-04-17
• Last updated: 2026-04-17