Assessing the Association Between Multi-dimension Facial Characteristics and Coronary Artery Diseases
NCT ID: NCT04941560
Last Updated: 2023-03-21
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
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
COMPLETED
460 participants
OBSERVATIONAL
2021-09-06
2023-02-10
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Deep Learning CAD Screening on Chest CT
NCT07181512
Trustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS
NCT06410690
Atherosclerotic Plaque Characterization
NCT00861653
Risk Evaluation by COronary Imaging and Artificial intelliGence Based fuNctIonal analyZing tEchniques - IV
NCT06793787
Risk Evaluation by COronary CTA and Artificial intelliGence Based fuNctIonal analyZing tEchniques - I
NCT05884008
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Thus, the investigators designed a single-center, cross-sectional study to explore the association between multi-dimension facial characteristics and CAD and to evaluate the predictive efficacy of multi-dimension appearance factors for CAD. The investigators will recruit patients undergoing coronary angiography or coronary computer tomography angiography. Patients' baseline information and multi-dimension facial images will be collected. The investigators will train and validate a deep learning algorithm based on multi-dimension facial photos.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
OTHER
PROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Algorithm training and test group
Patients undergoing coronary angiography or coronary computer tomography angiography will be enrolled. Patients data will be used to training and validate the algorithm for CAD detection based on facial photos.
No intervention
No intervention
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
No intervention
No intervention
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* Written informed consent
Exclusion Criteria
* Prior coronary artery bypass graft (CABG)
* Screening coronary artery disease before treating other heart diseases
* Without blood biochemistry outcome
* With artificially facial alteration (i.e. cosmetic surgery, facial trauma or make-up)
* Other situations which make patients fail to be photographed
18 Years
ALL
Yes
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
China National Center for Cardiovascular Diseases
OTHER_GOV
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Fuwai hospital
Beijing, Beijing Municipality, China
Countries
Review the countries where the study has at least one active or historical site.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
20210621-2021-1471
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.