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

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.

NCT Number	NCT07536932
Lead Sponsor	Shanghai Zhongshan Hospital Collaborators: Yan'an Affiliated Hospital of Kunming Medical University, Taian City Central Hospital, Mianyang Central Hospital, Guangdong Provincial People's Hospital
Conditions	Aortic Dissection Type A, Chest Pain
Enrollment	10,000 participants
Start Date	2026-04
Primary Completion	2026-12 (estimated)
Study Completion	2026-12 (estimated)
Updated on ClinicalTrials.gov	2026-04-17