An observational study in Coronary Artery Disease, sponsored by China National Center for Cardiovascular Diseases. Completed at 1 site in China. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2023-03-21.
Sponsored by China National Center for Cardiovascular Diseases · Observational
The purposes of this study are 1) to explore the association between multi-dimension facial characteristics and the increased risk of coronary artery diseases (CAD); 2) to evaluate the diagnostic efficacy of multi-dimension appearance factors for coronary artery diseases.
Previous study demonstrated the feasibility of using deep learning to detect coronary artery disease based on facial photos. However, several limitations made the algorithm hard to be utilized in clinical practice, including low specificity and lack of external validation. Adding multi-dimension facial characteristics may further increase the algorithm effect.
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.
5,598 studies on the registry are indexed under Coronary Artery Disease; 957 are open to participants now.
This study's enrollment of 460 is above the median of 336 across 1,947 observational studies indexed under Coronary Artery Disease.
Browse Coronary Artery Disease studies →China National Center for Cardiovascular Diseases is the lead sponsor of 256 studies on the registry; 134 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Patients who undergo coronary angiography or coronary computer tomography angiography from both resident patients and outpatient.
Exclusion Criteria:
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.
Other: No intervention
No intervention
Area under receiver operating curve (AUC)
Area under receiver operating curve of algorithm assessed in test group
Time frame: At the end of enrollment (1 mouth)
Sensitivity of algorithm
Sensitivity of algorithm assessed in test group
Time frame: At the end of enrollment (1 mouth)
Specificity of algorithm
Specificity of algorithm assessed in test group
Time frame: At the end of enrollment (1 mouth)
Positive predictive value (PPV)
PPV of algorithm assessed in test group
Time frame: At the end of enrollment (1 mouth)
Negative predictive value (NPV)
NPV of algorithm assessed in test group
Time frame: At the end of enrollment (1 mouth)
Diagnostic accuracy rate
Diagnostic accuracy rate of algorithm assessed in test group
Time frame: At the end of enrollment (1 mouth)
Plan to share: No
No publications or documents are linked to this record.
This study is completed, as verified in Mar 2023. You cannot join it, but the record below documents what was studied.
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China National Center for Cardiovascular Diseases