Performance Evaluation of Artificial Intelligence Screening Model in Coronary Heart Disease Detection
NCT ID: NCT06658600
Last Updated: 2025-04-08
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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ACTIVE_NOT_RECRUITING
NA
900 participants
INTERVENTIONAL
2025-01-10
2025-05-31
Brief Summary
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Detailed Description
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There are three settings:
1. Clinical Intuition (baseline assessment) Physicians assess obstructive CHD probability without any external assistance. Assessment relies solely on the physician's clinical judgment and experience.
2. Guideline-Based Group (Guideline Group) Physicians use a RF-CL table (risk factor weighted clinical likelihood table) to calculate the probability of obstructive CHD.
This approach aligns with current clinical guidelines to assist in decision-making.
3. AI-Assisted Group (AI Group) Physicians receive CHD probability estimates and diagnostic recommendations from an AI model based on retinal photographs.
The AI tool provides individualized obstructive CHD probabilities, leveraging retinal biomarkers associated with cardiovascular risk.
Primary Objective To evaluate whether AI-guided decision support could improves diagnostic accuracy of obstructive CHD to a greater extent than standard clinical assessments, both compared to clinical intuition.
Secondary Objective To assess whether AI-guided decision support reduces the time required to complete preliminary assessments of obstructive CHD.
Participants, Readers and Randomization Participants: Case records of participants with chest pain or dyspnea, all underwent CT coronary angiography or invasive coronary angiography.
Readers: Physicians performing preliminary evaluations of obstructive CHD patients.
Randomization: Participants and readers will be randomized into one of the groups (RF-CL or AI) after clinical assessment at baseline using block randomization to ensure balanced group sizes.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
SCREENING
SINGLE
Study Groups
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Guideline-Based Group (Guideline Group)
Physicians use a RF-CL table (risk factor weighted clinical likelihood table) to calculate the probability of obstructive CHD.
This approach aligns with current clinical guidelines to assist in decision-making.
Physician readers will be assisted with RF-CL table to calculate the probability of obstructive coronary heart disease
Physicians use a RF-CL table (risk factor weighted clinical likelihood table) to calculate the probability of obstructive CHD.
AI-Assisted Group (AI Group)
Physicians receive CHD probability estimates and diagnostic recommendations from an AI model based on retinal photographs.
The AI tool provides individualized obstructive CHD probabilities, leveraging retinal biomarkers associated with cardiovascular risk.
Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease
Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease. The AI tool provides individualized obstructive CHD probabilities and diagnosis, leveraging retinal biomarkers associated with cardiovascular risk.
Interventions
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Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease
Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease. The AI tool provides individualized obstructive CHD probabilities and diagnosis, leveraging retinal biomarkers associated with cardiovascular risk.
Physician readers will be assisted with RF-CL table to calculate the probability of obstructive coronary heart disease
Physicians use a RF-CL table (risk factor weighted clinical likelihood table) to calculate the probability of obstructive CHD.
Eligibility Criteria
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Inclusion Criteria
* Age range: 18-75 years old
* Can accept and cooperate with the examination and potential follow-up work after being selected for clinical trials
Exclusion Criteria
* Complex arrhythmia (atrial fibrillation, atrial flutter, frequent premature beats)
* Severe lung disease and chest malformation or surgery patients
* Acute myocardial infarction occurring less than 3 months ago
* Individuals with severe liver and kidney dysfunction and electrolyte imbalance
18 Years
75 Years
ALL
No
Sponsors
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Shanghai Jiao Tong University Affiliated Sixth People's Hospital
OTHER
Shanghai Health and Medical Center
UNKNOWN
Tsinghua University
OTHER
Responsible Party
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Tien Yin Wong
Professor
Principal Investigators
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Tien Yin Wong, PhD
Role: PRINCIPAL_INVESTIGATOR
Tsinghua University
Locations
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Tsinghua University
Beijing, Beijing Municipality, China
Shanghai Health and Medical Center
Shanghai, Shanghai Municipality, China
Shanghai Sixth People's Hospital
Shanghai, Shanghai Municipality, China
Countries
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Other Identifiers
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DeepCHD
Identifier Type: -
Identifier Source: org_study_id
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