Artificial Intelligence-based Methods to Predict Disease Progression in Youth With Type 2 Diabetes (NCT07116902)
Artificial Intelligence-based Methods to Predict Disease Progression in Youth With Type 2 Diabetes: A Digital Twin Study
🩺 Plain-English Summary (8th-Grade Level)
Currently, clinicians are unable to predict a patient's risk of long-term disease progression and development of a long-term complication based on the data that is available to them. The first aim of this is to develop and validate an Artificial Intelligence (AI) powered prediction model for Type 2 Diabetes (T2D) disease progression using existing data from previously collected studies and real-world electronic health medical data. Investigators will use clinical, pharmacologic, and genomic factors to develop the prediction model based on the most relevant clinical outcomes of change in Hemoglobin A1c (HbA1c) and the development of a microvascular complication. Despite the availability of newer medication options, lifestyle intervention is not effective in most youth and current therapeutic options are ineffective at producing sustained glycemic control. Newer and innovative methods are needed to identify the youth at highest risk of progression in terms of increase in HbA1c and development of long-term complications and to motivate behavioral change in youth. The goal of this aim is to create an AI-powered digital twin model for 50 youth with T2D using their baseline clinical, genetic, pharmacologic and lifestyle data and utilize AI algorithms developed in Aim 1 to simulate disease progression and treatment response. Investigators will then evaluate the digital twin model in an randomized controlled trail and prospectively compare the generated digital twin data to observed values over one year. Investigators will also measure whether knowledge of the digital twin prediction with targeted healthcare recommendations influence medication and lifestyle change adherence in the digital twin arm (n= 25) compared to the control arm (n= 25).
Who can join: Review the eligibility criteria below.
Location: UCSF Benioff Children's Hospital Oakland, Pediatric Diabetes Clinic — Oakland, California
Age range: 10 Years to 21 Years
🧪 Interventions in This Study
📋 "Do I Qualify?" — 1-Minute Self Screener
Instant ChecklistFull eligibility criteria are available on the official NIH protocol. View the criteria ↗
📍 All Participating Trial Locations (2 Sites)
- UCSF Benioff Children's Hospital Oakland, Pediatric Diabetes Clinic — Oakland, California
- UCSF Benioff Children's Hospital San Francisco, Madison Clinic for Pediatric Diabetes — San Francisco, California
📞 Contact the Study Coordinator
Phone: (415) 530-8047
Email: avani.narayan@ucsf.edu
Coordinator details come directly from the registered NIH protocol. Confirm the study is still recruiting before traveling.
💰 Cost, Insurance & Patient Rights
- 100% Free Items: The investigational treatment and protocol-required procedures are supplied at zero cost by the sponsor.
- Routine Patient Care: Under federal law (ACA § 2709) and many state statutes, routine care costs are covered during participation.
- Voluntary Participation: You may withdraw at any time without affecting your standard medical care.
More studies in Type 2 Diabetes
- Continuous Glucose Monitoring System Feasibility in Youth With T2D — San Francisco, California
- Diabetes Nutrition Education and Healthy Food Resource for AIANs With T2D — Oklahoma City, Oklahoma
- Personalized Nutrition Therapy Using Continuous Glucose Monitoring to Improve Outcomes in Type 2 Diabetes Mellitus — Minneapolis, Minnesota
- Diabetes Medical Nutrition Therapy in Southeastern African American Women — Nashville, Tennessee
- E3 Diabetes - Closing the Gap in Diabetes Control — Chicago, Illinois
- Recreational Basketball to Increase Participation in Diabetes Prevention — Atlanta, Georgia
Explore by condition: All Type 2 Diabetes clinical trials
💡 How to Participate
- Check the checklist above to see if you may qualify.
- Contact the study coordinator using the phone/email above.
- Ask about the visit schedule, what is covered at no cost, and any travel support.
- Confirm with your own doctor before making a decision.