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AI-ECG Observational Study for Acute Aortic Dissection

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Summary

NIH registered a prospective multicenter observational study (NCT07536932) evaluating an AI-ECG model for diagnosing acute type A aortic dissection in emergency department patients with chest pain. The study will enroll adults at five tertiary hospitals and compare AI model predictions against CTA-confirmed diagnoses. Clinical and ECG data will be collected as part of standard care to assess diagnostic performance across centers.

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What changed

NIH registered a new prospective multicenter observational study (NCT07536932) titled 'Triage and Recognition of Acute Aortic Dissection in Chest Pain by Electrocardiogram-Artificial Intelligence' on ClinicalTrials.gov. The study aims to evaluate whether an AI-ECG model can accurately distinguish acute type A aortic dissection from other causes of chest pain in real-world emergency settings.

For healthcare providers and clinical researchers, this registry entry indicates planned data collection at five tertiary hospitals involving routine ECG testing and CTA confirmation for diagnostic comparison. The study's results may inform future AI-assisted diagnostic tools in emergency cardiac care, though this registration itself creates no compliance obligations.

Archived snapshot

Apr 18, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

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

Observational NCT07536932 Kind: OBSERVATIONAL Apr 17, 2026

Abstract

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

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Last updated

Classification

Agency
NIH
Published
April 17th, 2026
Instrument
Notice
Legal weight
Non-binding
Stage
Final
Change scope
Minor
Document ID
NCT07536932

Who this affects

Applies to
Healthcare providers
Industry sector
6211 Healthcare Providers
Activity scope
Clinical trial research Diagnostic AI development
Geographic scope
United States US

Taxonomy

Primary area
Healthcare
Operational domain
Clinical Operations
Topics
Medical Devices Artificial Intelligence Public Health

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