Therapeutic Efficacy and Safety Evaluation of AI in the Management of Diabetes: A RCT Trial

Condition(s) studied

Investigational drug(s) / intervention(s)

artificial intelligence: 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.

Routine diagnosis and treatment group for diabetes: There is no limit to the number of outpatient visits for the control group; however, they are required to regularly monitor and record their blood glucose, diet, and exercise data to ensure that the medical team (endocrinologist and nutritionist) objectively conducttheir 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.

Study summary

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.

Methods: 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.

Expected 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.

Eligibility

Primary outcome measure(s)

• HbA1c — 48weeks
  Change From Baseline in HbA1c levels at 24 and 48 Weeks
• Fasting Blood Glucose (FBG) — 48 weeks
  Change from baseline in mean fasting blood glucose at 48 weeks
• 2-hour Postprandial Blood Glucose (2hPPG) — 48 weeks
  Change from baseline in mean 2-hour postprandial blood glucose at 48 weeks
• Hypoglycemic events — 48 weeks
  Number of hypoglycemic events from baseline to 48 weeks

Trial sites (1)

More The First Hospital of Jilin University trials in China

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