[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"diabetes-mellitus-type-2-t2dm\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:diabetes-mellitus-type-2-t2dm":27},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,2,0,[8,44],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":18,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":23,"briefSummary":25,"conditions":26,"keywords":29,"overallStatus":31,"whyStopped":4,"lastUpdateSubmitDate":32,"lastUpdatePostDateStruct":33,"startDateStruct":36,"completionDateStruct":38,"leadSponsor":40,"locationsCount":43},"100589644","therapeutic-efficacy-and-safety-evaluation-of-ai-in-the-management-of-diabetes-a-rct-trial-100589644",false,"NCT06957093","Therapeutic Efficacy and Safety Evaluation of AI in the Management of Diabetes: A RCT Trial","Evaluation of the Therapeutic Efficacy and Safety of Artificial Intelligence-based Decision-making Technology in the Integrated Management of Diabetes Mellitus: a Longitudinal, Open-labeled, Randomized Controlled Trial","Inclusion Criteria：\n\n* Age: ≥18 years，≤75 years;\n* Diagnosed with type 2 diabetes for ≥1 year;\n* 7.0% ≤HbA1c ≤11%;\n* Body mass index ≥18.5 kg\u002Fm2;\n* Proficient ability to use smart phones;\n* Agreed to utilize a digital integrated healthcare platform for diabetes care and research;\n* Informed consents are obtained from the participants.\n\nExclusion Criteria:\n\n* Presence of other types of diabetes, such as type 1 diabetes and gestational diabetes;\n* Severe diabetic complications;\n* Medical history of chronic liver diseases, including hemochromatosis, hepatocellular carcinoma, autoimmune liver disease, cirrhosis, viral hepatitis (including hepatitis A, B, and C), or hepatolenticular degeneration;\n* Kidney injury (serum creatinine ≥1.5 times the upper limit of the reference) ; Serum ALT and AST levels elevated \\>2-fold;\n* Medical history of mental disorders, such asschizophrenia, depression, or bipolar affective disorder;\n* Excessive alcohol intake or drug abuse in the past 3 months;\n* Use of medications affecting glucose metabolism, such as corticosteroids or ·consumption of immunosuppressive and anti-obesity medications in the past 3 months;\n* Pregnancy, planning for pregnancy, or lactation; or any other conditions unsuitable for trial participation;\n* Participatingor plan to participate in other clinical trials; and other cases that are inappropriate to participate.","ALL","18 Years","75 Years",{"count":20,"type":21},400,"ESTIMATED","INTERVENTIONAL",[24],"NA","Purpose: To evaluate the efficacy of artificial intelligence (AI)-based decision-making technology in managing glycated hemoglobin (HbA1c) and blood glucose levels compared to the control group.\n\nMethods: For the AI Intervention group, the patients will be trained to independently use the diabetes telemedicine platform application. Each patient will be equipped with a glucometer and exercise bracelet, and the data will be automatically transmitted to the medical server via Bluetooth. The healthcare platform will analyze the uploaded data and provide feedback suggestions on medication, diet, and exercise automatically. The platform will also monitor the medical and lifestyle data of the patients every two weeks, offer feedback based on the analyses, and remind the patient to adhere to the self-management protocol based on the platform. The platform is a digitally integrated healthcare platform that patients can use independently without the need for monitoring and assistance by healthcare professionals. The glucometer and pedometer bracelet will automatically connect to the platform through Bluetooth. The patient lab sheet identification and structured conversion system, AI for food picture identification and calorie calculation systems, and the AI decision-making system are on the cloud server. Patients upload image information, such as lab sheets and meal pictures, through the patient's diabetes mobile health system, and the cloud platform intelligently analyzes the patient's disease, medication, and daily life status to develop personalized solutions according to individual control goals. Free outpatient visits will be provided to both the intervention and control groups every twelve weeks. For the conventional treatment group, patients will receive a free blood glucometer and will have regular outpatient appointments. There is no limit to the number of outpatient visits; however, they are required to regularly monitor and record their blood glucose, diet, and exercise data to ensure that the medical team objectively conduct their diagnosis and treatment activities. The medical team will provide free outpatient visits every 12 weeks, along with advice on medication, diet, and exercise based on the individual's blood glucose level.\n\nExpected results: A significant difference in HbA1c change from baseline to 48 weeks and improved FPG and 2-hour postprandial blood glucose levels in the AI intervention group were observed.",[27,28],"Diabetes Mellitus Type 2 (T2DM)","Artificial Intelligence (AI)",[30,28],"Diabetes mellitus type 2 (T2DM)","RECRUITING","2025-12-02",{"date":34,"type":35},"2025-12-09","ACTUAL",{"date":37,"type":35},"2025-06-15",{"date":39,"type":21},"2026-12",{"name":41,"class":42},"The First Hospital of Jilin University","OTHER",1,{"id":45,"slug":46,"hasResults":11,"nctId":47,"briefTitle":48,"officialTitle":48,"acronym":49,"eligibilityCriteria":50,"healthyVolunteers":11,"sex":16,"minAge":51,"maxAge":52,"enrollmentInfo":53,"targetDuration":4,"studyType":55,"phases":4,"briefSummary":56,"conditions":57,"keywords":58,"overallStatus":31,"whyStopped":4,"lastUpdateSubmitDate":61,"lastUpdatePostDateStruct":62,"startDateStruct":64,"completionDateStruct":66,"leadSponsor":68,"locationsCount":43},"100580807","relationship-between-hemodynamic-changes-and-cardiopulmonary-fitness-in-type-2-diabetes-mellitus-patients-100580807","NCT06842108","Relationship Between Hemodynamic Changes and Cardiopulmonary Fitness in Type 2 Diabetes Mellitus Patients","diabetes","Inclusion Criteria:\n\n* Subjects who agreed to sign the informed consent form.\n* Subject with an age group 30-50yrs.\n* Female and male.\n* Controlled type 2 Diabetes Mellitus patients.\n\nExclusion Criteria:\n\n* Patient performing any exercise.\n* cardiovascular diseases.\n* Patients with Cerebrovascular diseases.\n* Patients with Peripheral artery diseases.\n* Patients with pulmonary dysfunction.","30 Years","50 Years",{"count":54,"type":21},162,"OBSERVATIONAL","Diabetes mellitus being metabolic disorder, chronic in nature, is characterized by high levels of glucose in our blood, which often lead to organ dysfunction. Approximately 10.5 % of adult (20-79 years) have diabetes according to international Diabetes federation. Cardiorespiratory fitness (CRF) is the capability of our cardiopulmonary system to make oxygen available to our skeletal muscles during physical activities for prolonged time, and is known to be decreased with diabetes. Hemodynamic parameters are correlated with various cardiovascular disorders but little evidence of hemodynamic changes in diabetes patients is present and more studies must be done. This study aims to establish the link between hemodynamic changes and cardiopulmonary fitness in T2DM patients, which could inform clinical practices and interventions to improve management, reduce cardiovascular risks, and enhance the quality of life for these patients.",[27],[59,60],"Diabetes Mellitus","Hemodynamic changes","2025-02-19",{"date":63,"type":35},"2025-02-24",{"date":65,"type":35},"2024-10-01",{"date":67,"type":21},"2025-04-15",{"name":69,"class":42},"Bahria University"]