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Using Retinal Photograph Based AI to Predict Incident Coronary Heart Disease

NCT06695273 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1570

Last updated 2024-11-19

No results posted yet for this study

Summary

To determine whether an integrated retinal AI decision support can improve predictive accuracy of coronary heart disease (CHD), the investigators are conducting a randomized controlled study of AI guided prediction of CHD compared to clinical prediction by physicians (e.g., usingPCEs), both using clinical intuition as baseline.

Conditions

  • Coronary Heart Disease (CHD)

Interventions

DIAGNOSTIC_TEST

AI-derived probability of coronary heart disease.

Physician readers will be assisted with AI-derived probability of coronary heart disease. The AI tool provides individualized obstructive CHD probabilities and diagnosis, leveraging retinal biomarkers associated with cardiovascular risk.

DIAGNOSTIC_TEST

PCEs derived ASCVD risk

Physicians use a PCEs to calculate the probability of 10 year ASCVD risk. This approach aligns with current clinical guidelines to assist in decision-making.

Sponsors & Collaborators

  • Tsinghua University

    lead OTHER

Principal Investigators

  • Tien Yin Wong · Tsinghua University

Study Design

Allocation
RANDOMIZED
Purpose
SCREENING
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
40 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-01-31
Primary Completion
2025-04-30
Completion
2025-05-31

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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 NCT06695273 on ClinicalTrials.gov