Using Retinal Photograph Based AI to Predict Incident Coronary Heart Disease (DeepCHD Plus)

November 16, 2024 updated by: Tien Yin Wong, Tsinghua University
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.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

This is a randomized controlled trial (RCT) evaluating the effectiveness of an AI-based decision support tool in CHD risk prediction and decision making by physicians. Prospective cohort study participant cases will be randomly assigned to either guideline group (e.g., PCEs) or AI group after baseline assessment (clinical intuition):

There are three settings: (1) Clinical Intuition (baseline assessment) Physicians' make decision about prevention strategy initiation (e.g., statin initiation) without any external assistance. Assessment relies solely on the physician's clinical judgment and experience. (2) Guideline-Based Group (Guideline Group) Physicians use a PCE table to calculate the 10 year ASCVD risk. This approach aligns with current clinical guidelines to assist in decision-making. (3) AI-Assisted Group (AI Group) Physicians receive CHD probability estimates 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 CHD to a greater extent than standard clinical assessments, both compared to clinical intuition. The accuracy could be assessed by the extent of prevention initiation (e.g., prescribing statins) corresponding with actual CHD outcomes observed.

Secondary Objective To assess whether AI-guided decision support reduces the time required to complete CHD assessments and decision making.

Participants, Readers and Randomization:

Participants: Participants in prospective cohort studies, with 10-year follow up.

Readers: Physicians performing evaluations of CHD probability and make primary prevention recommendations.

Randomization: Participants will be randomized into one of the groups (PCEs or AI) after clinical assessment at baseline using block randomization to ensure balanced group sizes.

Study Type

Interventional

Enrollment (Estimated)

1570

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion criteria:

  • Individuals without uncontrolled vascular risk factors
  • Age range: 40-75 years old
  • Can accept and cooperate with the examination and potential follow-up work after being selected for clinical trials

Exclusion criteria:

  • Severe lung disease and cancer or surgery patients
  • Statin user or pre-existing cardiovascular disease
  • Individuals with severe liver and kidney dysfunction and electrolyte imbalance

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Screening
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: AI-Assisted Group (AI Group)
Physicians receive CHD probability estimates from an AI model based on retinal photographs. The AI tool provides individualized CHD probabilities, leveraging retinal biomarkers associated with cardiovascular risk.
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.
Active Comparator: Guideline-Based Group (Guideline Group)
Physicians use a PCE calculator to calculate the 10 year ASCVD risk. This approach aligns with current clinical guidelines to assist in decision-making.
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy
Time Frame: Through study completion, an average of 1 week
To evaluate whether AI-guided decision support could improves diagnostic accuracy of CHD to a greater extent than standard clinical assessments, both compared to clinical intuition. The accuracy could be assessed by the degree to which prevention initiation (e.g., prescribing statins) align with actual CHD outcomes observed.
Through study completion, an average of 1 week

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Tsinghua University

Investigators

  • Principal Investigator: Tien Yin Wong, Tsinghua University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

January 1, 2025

Primary Completion (Estimated)

April 1, 2025

Study Completion (Estimated)

May 1, 2025

Study Registration Dates

First Submitted

November 16, 2024

First Submitted That Met QC Criteria

November 16, 2024

First Posted (Estimated)

November 19, 2024

Study Record Updates

Last Update Posted (Estimated)

November 19, 2024

Last Update Submitted That Met QC Criteria

November 16, 2024

Last Verified

November 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • DeepCHD Plus

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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