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AI-based Methods to Predict Disease Progression in Youth With Type 2 Diabetes

This study is looking at new ways to predict how Type 2 Diabetes (T2D) might progress in young people. Researchers are testing an Artificial Intelligence (AI) powered phone application. If you're in the "digital twin" group, you'll get information about your disease progression based on projected changes in your HbA1C (a measure of average blood sugar over 2-3 months) and recommendations for medication and lifestyle. The other group will receive standard care, which includes medication changes based on HbA1C and blood sugar every three months, plus standard lifestyle education. The study wants to see if the AI-based phone application can improve HbA1C levels over one year. You might be able to join if you are between 10 and 21 years old, have had T2D for at least three months, and your HbA1C is 7% or higher. The study is currently enrolling 50 participants, but its exact status is unclear.

Study design
This is an interventional study with 50 planned participants. It compares a phone application intervention to standard of care.
What's involved
Participants will have their HbA1C and blood glucose values checked every three months. Those in the digital twin arm will also use a phone application and wear a Continuous Glucose Monitor (CGM). The study lasts for one year.
Compensation
Not stated in the trial record.
Follow-up
Participants are followed until the close-out visit at the 1-year mark.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07116902

Artificial Intelligence-based Methods to Predict Disease Progression in Youth With Type 2 Diabetes

Not Yet Recruiting
NAAges 10–21InterventionalDiagnostic
University of California, San Francisco
~50 participants
Updated 2025-12-04 on ClinicalTrials.gov
What's tested:phone applicationStandard of Care (SOC)

At a glance

Recruiting sites
0 of 2 listed sites are recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Change in HbA1C
Measured over From enrollment to the close out visit at the 1-year mark

Conditions

Type 2 Diabetes

Explore related trials

Type 2 Diabetes Mellitus

Where it's being run

2 sites across 1 states
California2

Study leadership

  • Shylaja A Srinivasan, MD · PRINCIPAL_INVESTIGATOR · University of California, San Francisco

Who to contact

Avani A Narayan, MS
[email protected]
415-530-8047
Email the study team

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Do you actually qualify for this trial?

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Eligibility criteria

Inclusion

Age 10- 21 years
Diagnosis of T2D based on clinical diagnosis or ICD 9 and 10 codes
Duration of T2D ≥ 3 months
HbA1C ≥ 7% which is the target HbA1C recommended by the American Diabetes Association
Stable medication regimen (No medication changes and no change in basal insulin dose by more than 20% in the 2 weeks prior to enrollment)
Ability to wear CGM for a total of 6 weeks while in the study.
English or Spanish speakers.
Willing to abide by recommendations and study procedures.
Willing and able to sign the Informed Consent Form (ICF) and/or has a parent or guardian willing and able to sign the ICF.

Exclusion

Pancreatic autoantibody positivity (GAD-65, insulin, IA-2, ICA 512, ZnT8).
Plan for undergoing bariatric surgery during the study period
Anticipated use of systemic glucocorticoids during the study period
Unable to stop taking more than 500mg/day of Vitamin C during the study period as this may affect the sensor readings.
Presence of a condition or abnormality that in the opinion of the Investigator would compromise the safety of the patient or the quality of the data.
Presence of a condition or abnormality that in the opinion of the Investigator would cause repeated hospitalizations or significant changes in medications.

What this trial measures

  • Change in HbA1CFrom enrollment to the close out visit at the 1-year mark

    The primary outcome will be the ability of the digital twin model to accurately predict longitudinal disease progression measured as the digital twin predicted HbA1C versus measured HbA1C and the difference in HbA1C between the digital twin arm and control arms.