[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100569517":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":31,"centralContacts":35,"locations":26,"responsibleParty":41,"collaborators":26,"id":43,"slug":26,"hasResults":44,"nctId":45,"briefTitle":46,"officialTitle":46,"acronym":47,"eligibilityCriteria":48,"healthyVolunteers":49,"sex":50,"minAge":51,"maxAge":52,"enrollmentInfo":53,"targetDuration":26,"studyType":56,"phases":57,"briefSummary":59,"conditions":60,"keywords":26,"overallStatus":62,"whyStopped":26,"lastUpdateSubmitDate":63,"lastUpdatePostDateStruct":64,"startDateStruct":67,"completionDateStruct":69,"leadSponsor":71,"locationsCount":26},{"fullName":5,"class":6},"Tsinghua University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"AI-Assisted Group (AI Group)","EXPERIMENTAL","Physicians receive CHD probability estimates from an AI model based on retinal photographs. The AI tool provides individualized CHD probabilities, leveraging retinal biomarkers associated with cardiovascular risk.",[13],"Diagnostic Test: AI-derived probability of coronary heart disease.",{"label":15,"type":16,"description":17,"interventionNames":18},"Guideline-Based Group (Guideline Group)","ACTIVE_COMPARATOR","Physicians use a PCE calculator to calculate the 10 year ASCVD risk. This approach aligns with current clinical guidelines to assist in decision-making.",[19],"Diagnostic Test: PCEs derived ASCVD risk",[21,27],{"type":22,"name":23,"description":24,"armGroupLabels":25,"otherNames":26},"DIAGNOSTIC_TEST","AI-derived probability of coronary heart disease.","Physician readers will be assisted with AI-derived probability of coronary heart disease. The AI tool provides individualized obstructive CHD probabilities and diagnosis, leveraging retinal biomarkers associated with cardiovascular risk.",[9],null,{"type":22,"name":28,"description":29,"armGroupLabels":30,"otherNames":26},"PCEs derived ASCVD risk","Physicians use a PCEs to calculate the probability of 10 year ASCVD risk. This approach aligns with current clinical guidelines to assist in decision-making.",[15],[32],{"name":33,"affiliation":5,"role":34},"Tien Yin Wong","PRINCIPAL_INVESTIGATOR",[36],{"name":37,"role":38,"phone":39,"phoneExt":26,"email":40},"HONGWEI JI","CONTACT","+8613120518791","hongweijicn@gmail.com",{"type":34,"investigatorFullName":33,"investigatorTitle":42,"investigatorAffiliation":5,"oldNameTitle":26,"oldOrganization":26},"Professor","100569517",false,"NCT06695273","Using Retinal Photograph Based AI to Predict Incident Coronary Heart Disease","DeepCHD Plus","Inclusion criteria:\n\n* Individuals without uncontrolled vascular risk factors\n* Age range: 40-75 years old\n* Can accept and cooperate with the examination and potential follow-up work after being selected for clinical trials\n\nExclusion criteria:\n\n* Severe lung disease and cancer or surgery patients\n* Statin user or pre-existing cardiovascular disease\n* Individuals with severe liver and kidney dysfunction and electrolyte imbalance",true,"ALL","40 Years","75 Years",{"count":54,"type":55},1570,"ESTIMATED","INTERVENTIONAL",[58],"NA","To determine whether an integrated retinal AI decision support can improve predictive accuracy of coronary heart disease (CHD), the investigators are conducting a randomized controlled study of AI guided prediction of CHD compared to clinical prediction by physicians (e.g., usingPCEs), both using clinical intuition as baseline.",[61],"Coronary Heart Disease (CHD)","NOT_YET_RECRUITING","2024-11-16",{"date":65,"type":66},"2024-11-19","ACTUAL",{"date":68,"type":55},"2025-01",{"date":70,"type":55},"2025-05",{"name":5,"class":6}]