[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100591410":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":31,"centralContacts":36,"locations":26,"responsibleParty":42,"collaborators":46,"id":60,"slug":61,"hasResults":62,"nctId":63,"briefTitle":64,"officialTitle":65,"acronym":26,"eligibilityCriteria":66,"healthyVolunteers":62,"sex":67,"minAge":68,"maxAge":69,"enrollmentInfo":70,"targetDuration":26,"studyType":73,"phases":74,"briefSummary":76,"conditions":77,"keywords":26,"overallStatus":85,"whyStopped":26,"lastUpdateSubmitDate":86,"lastUpdatePostDateStruct":87,"startDateStruct":90,"completionDateStruct":92,"leadSponsor":94,"locationsCount":26},{"fullName":5,"class":6},"Tongji Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Intervention group (AI smartwatch assisted diagnosis)","EXPERIMENTAL","Participants in the intervention group will be required to wear a smartwatch continuously for 24 hours. After this period, the collected data will be processed using a pre-trained foundational model for disease diagnosis, generating preliminary diagnostic suggestions. General pratitioners will then integrate these smartwatch-derived findings with clinical interviews and aforementioned baseline examination results to formulate a final diagnosis.",[13],"Diagnostic Test: Smartwatch + GP",{"label":15,"type":16,"description":17,"interventionNames":18},"Control group (general pratitioner only)","ACTIVE_COMPARATOR","Participants in the control group will not wear smart watches. General pratitioners will base their diagnoses solely on clinical interviews and the aforementioned baseline examinations.",[19],"Diagnostic Test: GP only",[21,27],{"type":22,"name":23,"description":24,"armGroupLabels":25,"otherNames":26},"DIAGNOSTIC_TEST","Smartwatch + GP","Participants in the intervention group will be required to wear a smartwatch continuously for 24 hours. After this period, the collected data will be processed using a pre-trained foundational model for disease diagnosis, generating preliminary diagnostic suggestions. GPs will then integrate these smartwatch-derived findings with clinical interviews and aforementioned baseline examination results to formulate a final diagnosis.",[9],null,{"type":22,"name":28,"description":29,"armGroupLabels":30,"otherNames":26},"GP only","GPs will make diagnosis with clinical interviews and aforementioned baseline examination results to formulate a final diagnosis.",[15],[32],{"name":33,"affiliation":34,"role":35},"Cuntai Zhang, PhD","Wuhan TongJi Hospital","STUDY_CHAIR",[37],{"name":38,"role":39,"phone":40,"phoneExt":26,"email":41},"Yucong Zhang, PhD","CONTACT","86 13627115411","u201110541@hust.edu.cn",{"type":43,"investigatorFullName":44,"investigatorTitle":45,"investigatorAffiliation":5,"oldNameTitle":26,"oldOrganization":26},"PRINCIPAL_INVESTIGATOR","Zhang Cuntai","Professor",[47,49,51,54,56,58],{"name":48,"class":6},"Geriatric Hospital of Nanjing Medical University",{"name":50,"class":6},"Yangzhou University",{"name":52,"class":53},"Shanghai Health and Medical Center","UNKNOWN",{"name":55,"class":6},"Weifang Hospital of Traditional Chinese Medicine",{"name":57,"class":53},"CR & WSICO general hospital",{"name":59,"class":53},"Xunxian People's Hospital","100591410","wearable-devices-assist-in-the-detection-screening-and-management-of-major-diseases-in-middle-aged-and-elderly-populations-100591410",false,"NCT06980064","Wearable Devices Assist in the Detection, Screening, and Management of Major Diseases in Middle-aged and Elderly Populations","Wearable Devices Assist in the Detection, Screening, and Management of Major Diseases in Middle-aged and Elderly Populations: a Multicenter Randomized Controlled Trial","The inclusion criteria are as follows:\n\n1. Aged more than equal to 40 years, less than 69 years.\n2. Having at least one of the following conditions (with one risk factor for cardiovascular and cerebrovascular diseases):\n\n   ① Male ≥ 55 years old, female ≥ 65 years old; ② Smokers or those who quit smoking within the past 3 months prior to the visit; ③ Diabetes (type 1 or 2); ④ Hypertension (systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg) or currently taking antihypertensive medication; ⑤ Dyslipidemia: total cholesterol ≥ 5.18mmol\u002FL, triglycerides ≥ 1.70mmol\u002FL, high-density lipoprotein\\\u003C1.04mmol or low-density lipoprotein ≥ 3.37mmol\u002FL; ⑥ hsCRP\\>3.0 mg\u002FL; ⑦ 10-year ASCVD risk of 20% or more (calculated according to the formula designed in the PREVENT study)\n3. Agree to receive coronary CTA if suspected to have coronary artery stenosis.\n4. Voluntarily joined and signed the informed consent.\n\nThe exclusion criteria:\n\n1. Previously diagnosed with CAD or considered moderate to severe coronary stenosis (CAD-RADS grade 3 or above: stenosis degree of 50% or above) through coronary CTA or coronary angiography examination.\n2. Pregnant women or women planning to become pregnant within the next year.\n3. During the onset of the disease and needs in-hospital treatment.\n4. Tattoos or other substances that affect optical signals on the wrist.\n5. Severe arrhythmia patients, including third degree atrioventricular block, ventricular escape rhythm, severe sinus bradycardia, sick sinus syndrome, supraventricular tachycardia, ventricular tachycardia, atrial fibrillation, atrial flutter, ventricular fibrillation, ventricular flutter.\n6. Physical disability, blindness, and deafness.\n7. Allergic history of contrast agent containing iodine.","ALL","40 Years","69 Years",{"count":71,"type":72},800,"ESTIMATED","INTERVENTIONAL",[75],"NA","The goal of this randomized controlled trial is to evaluate the effectiveness of wearable devices (Huawei smartwatches) in aiding the detection, and screening of major diseases (e.g., coronary artery disease, hypertension) in middle-aged and elderly populations aged 40-69 years with cardiovascular risk factors (e.g., smoking, diabetes, hypertension, dyslipidemia). The main questions it aims to answer are:\n\nDoes AI-assisted diagnosis using wearable device data improve the detection rate of coronary artery stenosis (CAD-RADS ≥3) compared to standard physician assessment without AI assistance?\n\nDoes the intervention reduce the incidence of coronary artery disease-related events (e.g., angina, myocardial infarction) within one year?\n\nResearchers will compare the intervention group (AI model-assisted diagnosis based on Huawei smartwatch data) with the control group (standard assessment) to determine if the AI-aided smartwatch approach enhances diagnostic accuracy and clinical outcomes.\n\nParticipants will:\n\n（Intervention group）Wear a Huawei smartwatch for 24 hours to collect physiological data (e.g., PPG signals, heart rate, motion).\n\nUndergo baseline assessments, including medical history review, physical exams, and laboratory tests.\n\nReceive a preliminary diagnosis from a general practitioner.\n\nComplete a follow-up evaluation after one year to track cardiovascular events and other disease outcomes.\n\nUndergo coronary CTA if suspected of coronary stenosis.",[78,79,80,81,82,83,84],"Coronary Stenosis","Cerebral Arterial Diseases","Hypertension","Parkinson Disease","Heart Failure","Peripheral Arterial Occlusive Disease","Thyroid Dysfunction","NOT_YET_RECRUITING","2025-05-16",{"date":88,"type":89},"2025-05-20","ACTUAL",{"date":91,"type":72},"2025-06-01",{"date":93,"type":72},"2026-12-31",{"name":5,"class":6}]