Triage and Recognition of Acute Aortic Dissection in Chest Pain by Electrocardiogram-Artificial Intelligence
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Aortic Dissection Type A, Chest Pain. Basic parameters: 18 years — 80 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
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
Overview
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.
Primary outcome measures
- Diagnostic performance of the AI-based electrocardiogram model for acute type A aortic dissection [Time frame: From emergency department presentation to completion of CTA and final diagnostic confirmation during the index visit, up to 24 hours]
Secondary outcome measures (6)
- Sensitivity of the AI-based electrocardiogram model for acute type A aortic dissection [Time frame: From emergency department presentation to completion of CTA and final diagnostic confirmation during the index visit, up to 24 hours]
- Specificity of the AI-based electrocardiogram model for acute type A aortic dissection [Time frame: From emergency department presentation to completion of CTA and final diagnostic confirmation during the index visit, up to 24 hours]
- Positive predictive value of the AI-based electrocardiogram model for acute type A aortic dissection [Time frame: From emergency department presentation to completion of CTA and final diagnostic confirmation during the index visit, up to 24 hours]
- Negative predictive value of the AI-based electrocardiogram model for acute type A aortic dissection [Time frame: From emergency department presentation to completion of CTA and final diagnostic confirmation during the index visit, up to 24 hours]
- Diagnostic time from emergency department presentation to AI model output [Time frame: At the index visit, up to 24 hours]
- Diagnostic time reduction associated with the AI-based electrocardiogram workflow compared with standard care [Time frame: At the index visit, up to 24 hours]
Eligibility criteria
Inclusion criteria
- Male or female emergency department patients aged 18-80 years;
- Clear presentation of chest pain or related chest/back pain;
- Completion of standard 12-lead electrocardiography (ECG) within 24 hours after onset of chest pain;
- ECG signal quality meeting the following criteria: QRS amplitude ≥ 0.1 mV and noise proportion < 20%;
- Availability of subsequent diagnostic workup confirming whether the patient had acute type A aortic dissection (TAAD) or another definitive diagnosis.
Exclusion criteria
- Poor-quality ECG recordings, defined as missing leads in ≥ 3 leads or severe baseline instability;
- Indeterminate final diagnosis;
- History of prior surgery involving the aortic valve, aortic root, or ascending aorta.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT07536932 · B2026-106