Prediction of Coronary Artery Disease Based on Multimodal, Non-contact Information With Artificial Intelligence

NCT06092801 | Completed

• 1 other identifier: 2022-GSP-QN-10
• Study Type: observational
• Target: 2,978
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational study are 1) to assess the effectiveness of modalities and/or their combination of multimodal non-contact information in predicting coronary artery disease; 2) to prospectively validate the performance of the developed artificial Intelligence models in predicting coronary artery disease.

Conditions

Coronary Artery Disease

Outcome Measures

Primary Outcomes (2)

• Sensitivity of algorithm

  Sensitivity of algorithm in predicting coronary artery disease assessed in test group

  At the end of enrollment (1 mouth)

• Specificity of algorithm

  Sensitivity of algorithm in predicting coronary artery disease assessed in test group

  At the end of enrollment (1 mouth)

Secondary Outcomes (1)

• Area under receiver operating curve (AUC)

  At the end of enrollment (1 mouth)

Other Outcomes (3)

• Positive predictive value (PPV) of algorithm

  At the end of enrollment (1 mouth)

• Negative predictive value (NPV)

  At the end of enrollment (1 mouth)

• Diagnostic accuracy rate

  At the end of enrollment (1 mouth)

Study Arms (1)

Individuals suspected of coronary artery disease

Individuals suspected of coronary artery disease and referred for evaluation

Other: No intervention

Interventions

No intervention OTHER

No intervention

Individuals suspected of coronary artery disease

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Individuals suspected of coronary artery disease and referred for confirmatory evaluation

You may qualify if:

• Suspected individuals referred to for coronary angiography or coronary computer tomography angiography.

You may not qualify if:

• Prior percutaneous coronary intervention (PCI)
• Prior coronary artery bypass graft (CABG)
• Undergoing confirmatory coronary evaluation as pre-operation routines for other cardiac diseases
• With artificial body alteration (e.g. cosmetic surgery, facial trauma, or make-up) that may affect the non-contact information of study interest
• Age less than 18 years old
• Other circumstances that prevent participants from cooperating with the study process
• Decline to consent for study participation

Sponsors & Collaborators

• China National Center for Cardiovascular Diseases: lead

Study Sites (1)

Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Beijing, Beijing Municipality, China

Location

Related Publications (1)

• Lin S, Li Z, Fu B, Chen S, Li X, Wang Y, Wang X, Lv B, Xu B, Song X, Zhang YJ, Cheng X, Huang W, Pu J, Zhang Q, Xia Y, Du B, Ji X, Zheng Z. Feasibility of using deep learning to detect coronary artery disease based on facial photo. Eur Heart J. 2020 Dec 7;41(46):4400-4411. doi: 10.1093/eurheartj/ehaa640.

  PMID: 32818267 BACKGROUND

MeSH Terms

Conditions

Coronary Artery Disease

Condition Hierarchy (Ancestors)

Coronary Disease; Myocardial Ischemia; Heart Diseases; Cardiovascular Diseases; Arteriosclerosis; Arterial Occlusive Diseases; Vascular Diseases

Study Officials

• Shen Lin, M.D., Ph.D.

  Chinese Academy of Medical Sciences, Fuwai Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER GOV
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 16, 2023
• First Posted: October 23, 2023
• Study Start: November 20, 2023
• Primary Completion: April 9, 2025
• Study Completion: April 9, 2025
• Last Updated: November 28, 2025

Record last verified: 2025-11

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)