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Completed

NCT Number: NCT04941560

Assessing the Association Between Multi-dimension Facial Characteristics and Coronary Artery Diseases

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.

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Key information

Conditions

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

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Fuwai hospital

Beijing, Beijing Municipality, 100032, China

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Undergoing coronary angiography or coronary computer tomography angiography
  • Written informed consent

Exclusion criteria

  • Prior percutaneous coronary intervention (PCI)
  • 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

Treatment and study plan

No intervention

Other

No intervention

Primary outcomes

  1. Area under receiver operating curve (AUC)

    Time frame: At the end of enrollment (1 mouth)

    Area under receiver operating curve of algorithm assessed in test group

Secondary outcomes

  1. Sensitivity of algorithm

    Time frame: At the end of enrollment (1 mouth)

    Sensitivity of algorithm assessed in test group

  2. Specificity of algorithm

    Time frame: At the end of enrollment (1 mouth)

    Specificity of algorithm assessed in test group

  3. Positive predictive value (PPV)

    Time frame: At the end of enrollment (1 mouth)

    PPV of algorithm assessed in test group

  4. Negative predictive value (NPV)

    Time frame: At the end of enrollment (1 mouth)

    NPV of algorithm assessed in test group

  5. Diagnostic accuracy rate

    Time frame: At the end of enrollment (1 mouth)

    Diagnostic accuracy rate of algorithm assessed in test group

Sponsors and collaborators

Lead sponsor

China National Center for Cardiovascular Diseases

Other Gov

Registry information

Official study title

Artificial Intelligence to Assess the Association Between Multi-dimension Facial Characteristics and Coronary Artery Diseases

Important dates

Study start
2021
Primary completion
2023
Study completion
2023
First posted
Jun 28, 2021
Registry last updated
Mar 21, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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