[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100602871":3},{"organization":4,"armGroups":7,"interventions":28,"overallOfficials":33,"centralContacts":46,"locations":52,"responsibleParty":67,"collaborators":69,"id":90,"slug":91,"hasResults":92,"nctId":93,"briefTitle":94,"officialTitle":95,"acronym":33,"eligibilityCriteria":96,"healthyVolunteers":92,"sex":97,"minAge":98,"maxAge":33,"enrollmentInfo":99,"targetDuration":33,"studyType":102,"phases":103,"briefSummary":105,"conditions":106,"keywords":33,"overallStatus":54,"whyStopped":33,"lastUpdateSubmitDate":109,"lastUpdatePostDateStruct":110,"startDateStruct":113,"completionDateStruct":115,"leadSponsor":117,"locationsCount":118},{"fullName":5,"class":6},"Second Xiangya Hospital of Central South University","OTHER",[8,13,18,23],{"label":9,"type":6,"description":10,"interventionNames":11},"Control: Traditional Control","Adopt classic doctor-patient interaction management; receive diet and exercise education upon enrollment, self-monitor blood glucose at home and keep a diary.",[12],"Other: Device: No specific devices",{"label":14,"type":6,"description":15,"interventionNames":16},"Experimental: Wearable Devices + Data Management Platform","On the basis of classic management, wear CGM , load CGM management software, and monitor health data in real time via mobile software.",[17],"Other: Device: CGM,CGM management platform",{"label":19,"type":6,"description":20,"interventionNames":21},"Experimental:WeChat mini-program Smart Management","On the basis of classic management, use the \"Professor Tang\" WeChat mini-program for blood glucose recording and diet\u002Fexercise management.",[22],"Other: Device: \"Professor Tang\" WeChat Mini-program",{"label":24,"type":6,"description":25,"interventionNames":26},"Experimental:Wearable Devices + WeChat mini-program Management","On the basis of classic management, wear CGM or smartbands , and use the \"Professor Tang\" WeChat mini-program simultaneously for real-time data monitoring and personalized recommendations.",[27],"Other: Device: CGM, Smart Bracelet, \"Professor Tang\" WeChat Mini-program",[29,34,38,42],{"type":6,"name":30,"description":31,"armGroupLabels":32,"otherNames":33},"Device: No specific devices","Routine doctor-patient interaction.",[9],null,{"type":6,"name":35,"description":36,"armGroupLabels":37,"otherNames":33},"Device: CGM,CGM management platform","Wearable monitoring + CGM management platform-assisted administration",[14],{"type":6,"name":39,"description":40,"armGroupLabels":41,"otherNames":33},"Device: \"Professor Tang\" WeChat Mini-program","Mini-program-assisted health management",[19],{"type":6,"name":43,"description":44,"armGroupLabels":45,"otherNames":33},"Device: CGM, Smart Bracelet, \"Professor Tang\" WeChat Mini-program","Wearable monitoring + mini-program integrated management",[24],[47],{"name":48,"role":49,"phone":50,"phoneExt":33,"email":51},"HouDe Zhou, Prof.","CONTACT","86-0731-85292223","houdezhou@csu.edu.cn",[53],{"facility":5,"status":54,"city":55,"state":33,"zip":33,"country":56,"countryCode":57,"cosmosGeoPoint":58,"geoPoint":63,"contacts":64},"RECRUITING","Changsha","China","CN",{"type":59,"coordinates":60},"Point",[61,62],112.97087,28.19874,{"lat":62,"lon":61},[65],{"name":66,"role":49,"phone":50,"phoneExt":33,"email":51},"周",{"type":68,"investigatorFullName":33,"investigatorTitle":33,"investigatorAffiliation":33,"oldNameTitle":33,"oldOrganization":33},"SPONSOR",[70,72,74,76,78,80,82,84,87],{"name":71,"class":6},"First Hospital of China Medical University",{"name":73,"class":6},"The First Affiliated Hospital with Nanjing Medical University",{"name":75,"class":6},"First Affiliated Hospital of Harbin Medical University",{"name":77,"class":6},"Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University",{"name":79,"class":6},"First Affiliated Hospital of Kunming Medical University",{"name":81,"class":6},"Tianjin Medical University",{"name":83,"class":6},"Shanghai 6th People's Hospital",{"name":85,"class":86},"Jinjiang Municipal Hospital, Shanghai Sixth People's Hospital Fujian Campus","UNKNOWN",{"name":88,"class":89},"Sinocare","INDUSTRY","100602871","mobile-health-and-wearable-devices-for-diabetes-complication-management-100602871",false,"NCT07129148","Mobile Health and Wearable Devices for Diabetes Complication Management","Study on the Applicability of New Technologies for Diabetes Complication Management Based on Mobile Health and Wearable Devices","Inclusion Criteria:\n\n1. Confirmed diagnosis of Type 2 Diabetes;\n2. Aged ≥ 18 years;\n3. Able to accept the diabetes management model with AI-assisted management and wearable device monitoring;\n4. Able to provide complete lifestyle records, including medical history, medication status, diet, exercise, etc.;\n5. Fully understand the purpose, nature, and methods of the study, voluntarily participate in this study, accept a 3-month follow-up, and sign the informed consent form.\n\nExclusion Criteria:\n\n1. Having severe mental illness or language barriers;\n2. Suffering from malignant tumors;\n3. Pregnant or lactating women;\n4. Suspected active infections (such as active pulmonary tuberculosis, pneumonia, etc.);\n5. Severe hepatic and renal insufficiency (alanine transaminase and\u002For aspartate transaminase \\> 3 times the upper limit of normal; estimated glomerular filtration rate \\\u003C 15 mL\u002Fmin\u002F1.73 m²);\n6. A history of definite major adverse cardiovascular events and\u002For revascularization and\u002For intravenous thrombolysis and\u002For endovascular thrombectomy;\n7. Uncontrolled hyperthyroidism or hypothyroidism, pituitary-adrenal dysfunction, or other endocrine diseases;\n8. Alcoholism or drug addiction;\n9. Receiving insulin therapy;\n10. Unable to accept new comprehensive intervention technologies for various reasons (such as personal beliefs, economic factors, etc.).","ALL","18 Years",{"count":100,"type":101},6000,"ESTIMATED","INTERVENTIONAL",[104],"NA","The value of intelligent lifestyle intervention for T2D and its complications has been initially explored, but evidence-based support for the effectiveness of related AI risk prediction models and intervention models remains to be confirmed. The primary objective of this study is to verify the effectiveness of an AI model for predicting the risk of T2D complications based on phenotype, laboratory indicators and wearable device indicators, and to explore the effect and applicability of an intelligent lifestyle intervention model combining wearable devices and smartphones in preventing T2D complications.",[107,108],"Diabetes Mellitus Type 2","Diabetes Mellitus Complications","2026-05-27",{"date":111,"type":112},"2026-06-01","ACTUAL",{"date":114,"type":112},"2025-10-01",{"date":116,"type":101},"2027-10-01",{"name":5,"class":6},1]