An interventional study of Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease and Physician readers will be assisted with RF-CL table to calculate the probability of obstructive coronary heart disease in Coronary Heart Disease, sponsored by Tsinghua University. Active, not recruiting at 3 sites in China. Open to participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2025-04-08.
Sponsored by Tsinghua University · Not applicable, Interventional, and Screening
To determine whether an integrated AI decision support can save time and improve accuracy of assessment of obstructive coronary heart disease (CHD), the investigators are conducting a randomized controlled study of AI guided measurements of obstructive CHD probability compared to clinical assessment in preliminary evaluations by physicians.
This is a randomized controlled trial (RCT) evaluating the effectiveness of an AI-based decision support tool in the preliminary assessment of obstructive CHD by physicians. Retrospectively collected medical records of participants with chest pain or dyspnea will be randomly assigned to either guideline group or AI group after baseline assessment:
There are three settings:
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.
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.
3,639 studies on the registry are indexed under Heart Diseases; 461 are open to participants now.
This study's planned enrollment of 900 is above the median of 100 across 1,778 interventional studies indexed under Heart Diseases.
Browse Heart Diseases studies →Tsinghua University is the lead sponsor of 24 studies on the registry; 15 are open to participants now.
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Exclusion criteria:
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.
Other: Physician readers will be assisted with RF-CL table to calculate the probability of obstructive coronary heart disease
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.
Other: 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.
Physicians use a RF-CL table (risk factor weighted clinical likelihood table) to calculate the probability of obstructive CHD.
Diagnostic Accuracy of Participants with Obstructive Coronary Heart Disease
Whether AI-guided decision support improves the diagnostic accuracy of obstructive coronary heart disease (CHD) to a greater extent than standard clinical assessments (RF-CL), both compared to clinical intuition. All participants of the case records had underwent CT angiography or invasive angiography. The diagnostic accuracy, sensitivity and specificity will be compared across groups.
Time frame: Through study completion, an average of 1 week
Time Consumed by Physician Readers to Provide the Diagnosis Impression of Obstructive Coronary Heart Disease.
The time consumed by physician readers will be recorded by an algorithm implemented on the website for reading.
Time frame: Through study completion, an average of 1 week
Plan to share: No
No publications or documents are linked to this record.
This study is active, not recruiting, as verified in Apr 2025. You cannot join it, but the record below documents what was studied.
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Tsinghua University