Artificial Intelligence to Assess the Association Between Facial Characteristics and Coronary Artery Diseases
Studienübersicht
Status
Bedingungen
Intervention / Behandlung
Detaillierte Beschreibung
Several age-related appearance factors were described associated with increased risk of coronary artery diseases (CAD). However, several limitations made these facial risk factors hard to be utilized in clinical practice, including 1) low prevalence in CAD patients, 2) lack of specific definition, 3) poor reproducibility in artificial recognition.
Thus, the investigators designed a multi-center, cross-sectional study to explore the association between facial characteristics and CAD and evaluate the diagnostic efficacy of appearance factors for CAD. The investigators will recruit patients undergoing coronary angiography or coronary computer tomography angiography. Patients' baseline information and facial images will be collected. First, the investigators will explore the facial factors associated with CAD by using artificial intelligence technology to compare facial photographs between patients with CAD and without CAD. Secondary, the investigators will evaluate the dose-response relationship between facial characteristics and CAD. Third, the investigators will establish a CAD risk model based on facial factors, and evaluate the diagnostic effect of the model.
Studientyp
Einschreibung (Tatsächlich)
Kontakte und Standorte
Studienorte
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Beijing
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Beijing, Beijing, China, 100032
- Fuwai Hospital
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Beijing, Beijing, China, 100032
- Beijing Anzhen Hospital
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Beijing, Beijing, China, 100032
- Guanganmen Hospital, Chinese Academy of Traditional Chinese Medicine
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Hubei
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Wuhan, Hubei, China, 430000
- Wuhan Union Hospital
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Jiangsu
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Xuzhou, Jiangsu, China, 221000
- Xuzhou Third People's Hospital
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Liangning
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Dalian, Liangning, China, 116000
- The First Affiliated Hospital of Dalian Medical University
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Shanghai
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Shanghai, Shanghai, China, 200000
- Shanghai East Hospital
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Shanghai, Shanghai, China, 200000
- Shanghai Renji Hospital
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Zhejiang
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Wenzhou, Zhejiang, China, 325000
- The fisrt affiliated hospital of Wenzhou medical university
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Teilnahmekriterien
Zulassungskriterien
Studienberechtigtes Alter
Akzeptiert gesunde Freiwillige
Studienberechtigte Geschlechter
Probenahmeverfahren
Studienpopulation
Beschreibung
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
Studienplan
Wie ist die Studie aufgebaut?
Designdetails
Kohorten und Interventionen
Gruppe / Kohorte |
Intervention / Behandlung |
|---|---|
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Model establishment and test group
Patients undergoing coronary angiography or coronary computer tomography angiography will be enrolled.
Patients data will be used to establish the facial based diagnostic model of coronary artery diseases, and to prospectively validate the diagnostic effectiveness of the model.
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Kein Eingriff
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Was misst die Studie?
Primäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
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Sensitivity of diagnostic model
Zeitfenster: at the end of enrollment (6 months)
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The sensitivity of coronary artery diagnostic model assessed in model test group
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at the end of enrollment (6 months)
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Sekundäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
|---|---|---|
|
Specificity of diagnostic model
Zeitfenster: at the end of enrollment (6 months)
|
The specificity of coronary artery diagnostic model assessed in model test group
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at the end of enrollment (6 months)
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Specificity of diagnostic model
Zeitfenster: at the end of enrollment (6 months)
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Area under receiver operating curve (AUC) of diagnostic model assessed in model test group
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at the end of enrollment (6 months)
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Positive predictive value (PPV)
Zeitfenster: at the end of enrollment (6 months)
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PPV of diagnostic model assessed in model test group
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at the end of enrollment (6 months)
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Negative predictive value (NPV)
Zeitfenster: at the end of enrollment (6 months)
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NPV of diagnostic model assessed in model test group
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at the end of enrollment (6 months)
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Diagnostic accuracy rate
Zeitfenster: at the end of enrollment (6 months)
|
Diagnostic accuracy rate of diagnostic model assessed in model test group
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at the end of enrollment (6 months)
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Mitarbeiter und Ermittler
Studienaufzeichnungsdaten
Haupttermine studieren
Studienbeginn (Tatsächlich)
Primärer Abschluss (Tatsächlich)
Studienabschluss (Tatsächlich)
Studienanmeldedaten
Zuerst eingereicht
Zuerst eingereicht, das die QC-Kriterien erfüllt hat
Zuerst gepostet (Tatsächlich)
Studienaufzeichnungsaktualisierungen
Letztes Update gepostet (Tatsächlich)
Letztes eingereichtes Update, das die QC-Kriterien erfüllt
Zuletzt verifiziert
Mehr Informationen
Begriffe im Zusammenhang mit dieser Studie
Schlüsselwörter
Zusätzliche relevante MeSH-Bedingungen
Andere Studien-ID-Nummern
- 20181104-2017-907
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Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt
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