MedTrace Logo

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

NCT07536932 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 10000

Last updated 2026-04-17

No results posted yet for this study

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

Sponsors & Collaborators

  • Yan'an Hospital of Kunming City

    collaborator UNKNOWN

  • Taian City Central Hospital

    collaborator OTHER

  • Mianyang Central Hospital

    collaborator OTHER

  • Guangdong Provincial People's Hospital

    collaborator OTHER

  • Shanghai Zhongshan Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-04-30
Primary Completion
2026-12-31
Completion
2026-12-31

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07536932 on ClinicalTrials.gov