[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100615101":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":12,"centralContacts":25,"locations":12,"responsibleParty":31,"collaborators":12,"id":35,"slug":36,"hasResults":37,"nctId":38,"briefTitle":39,"officialTitle":40,"acronym":12,"eligibilityCriteria":41,"healthyVolunteers":37,"sex":42,"minAge":43,"maxAge":44,"enrollmentInfo":45,"targetDuration":12,"studyType":48,"phases":49,"briefSummary":51,"conditions":52,"keywords":12,"overallStatus":55,"whyStopped":12,"lastUpdateSubmitDate":56,"lastUpdatePostDateStruct":57,"startDateStruct":60,"completionDateStruct":62,"leadSponsor":64,"locationsCount":12},{"fullName":5,"class":6},"RenJi Hospital","OTHER",[8,13],{"label":9,"type":10,"description":11,"interventionNames":12},"The guideline-guided traditional management group","NO_INTERVENTION","As the control group, wearable data will be collected but not shared with the participant and responding physician or used for clinical management during the study period. All management in the participants is based on updated clinical guidelines.",null,{"label":14,"type":15,"description":16,"interventionNames":17},"The guideline-guided and wearable-assisted management group","EXPERIMENTAL","As the intervention group, in addition to clinical guidelines, wearable data and AI analytical results will be made available to both patients and their physicians. These insights will be discussed during follow-ups and used to support lifestyle modification, medication adjustment, and clinical decision-making.",[18],"Combination Product: Optimized Integrated Management Based on AI-Guided Wearable Data",[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":12},"COMBINATION_PRODUCT","Optimized Integrated Management Based on AI-Guided Wearable Data","The collected data will be shared with both patients and their treating physicians during follow-up visits. Based on these insights, the clinical team will offer personalized recommendations regarding medication adjustment, lifestyle modification, diet optimization, and physical activity guidance.",[14],[26],{"name":27,"role":28,"phone":29,"phoneExt":12,"email":30},"ZHIGUO ZOU, MD, PhD","CONTACT","+86 13524596108","zouzhiguo@renji.com",{"type":32,"investigatorFullName":33,"investigatorTitle":34,"investigatorAffiliation":5,"oldNameTitle":12,"oldOrganization":12},"PRINCIPAL_INVESTIGATOR","Zhiguo Zou","Doctor","100615101","the-benefits-of-wearable-ai-in-post-discharge-management-of-ami-patients-100615101",false,"NCT07288229","The Benefits of Wearable AI in Post-Discharge Management of AMI Patients","The Benefits of Wearable Device-Based Artificial Intelligence in Post-Discharge Management of Patients With Acute Myocardial Infarction","Inclusion Criteria:\n\n* Adults aged 18 to 75 years.\n* Confirmed diagnosis of acute myocardial infarction (AMI), including both ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI).\n* Underwent successful percutaneous coronary intervention (PCI) during index hospitalization.\n* Hemodynamically stable at the time of hospital discharge.\n* Willing and able to wear a smartwatch continuously for the study period.\n* Compatible with the data collection application and have stable internet access.\n\nExclusion Criteria:\n\n* Planned staged or elective PCI or any coronary revascularization scheduled within 3 months after discharge.\n* Unable to tolerate or contraindicated for wearing metal or electronic monitoring devices.\n* Pregnant or breastfeeding women.\n* Residence in an area without stable network connectivity or inability to use a smartphone for data upload and communication.\n* Severe comorbidities that limit 3-month survival or follow-up.","ALL","18 Years","75 Years",{"count":46,"type":47},200,"ESTIMATED","INTERVENTIONAL",[50],"NA","Myocardial infarction (MI) remains a major threat to human health. Although interventional treatment techniques have advanced rapidly, many patients still experience major adverse cardiovascular events (MACE) and require hospital readmission after discharge. Artificial intelligence (AI) based on wearable device data has shown great potential in the diagnosis and management of cardiovascular diseases.\n\nThis study aims to explore the clinical value of wearable device-based data analysis and AI-driven risk stratification models in post-discharge management of acute myocardial infarction (AMI) patients.",[53,54],"Acute Myocardial Infarction","Heart Failure","NOT_YET_RECRUITING","2025-12-15",{"date":58,"type":59},"2025-12-17","ACTUAL",{"date":61,"type":47},"2025-12-30",{"date":63,"type":47},"2026-12-30",{"name":5,"class":6}]