SnapDandCGMinType2Diabetes

Summary

Study Title: The Effectiveness of an AI-powered Thai food analysis (SnapD) and Continuous Glucose Monitoring on Glycemic Control in Patients with Type 2 Diabetes and Overweight or Obesity: A Randomized Controlled Pilot Study Rationale: Effective dietary management is the cornerstone of treating Type 2 Diabetes (T2DM) and obesity. However, traditional manual food logging is often inaccurate and burdensome. While digital tools and Continuous Glucose Monitoring (CGM) have shown promise internationally, there is a lack of validated AI-powered tools specifically designed for Thai cuisine. This study introduces SnapD, an AI-powered platform (utilizing Gemini 2.5 Flash) designed to recognize Thai food, estimate nutritional values, and integrate with CGM data to provide personalized feedback. The primary goal of this pilot study is to evaluate the efficacy of the SnapD application, both as a standalone tool and in combination with CGM, compared to Standard of Care in improving glycemic control (HbA1c) over 8 weeks. Additionally, the study aims to assess the feasibility, participant adherence, and safety of these digital interventions to inform a future, fully powered randomized controlled trial. Study Design: This is an 8-week, randomized, open-label, parallel-group, superiority pilot study with a 1:1:1 allocation ratio. A total of 45 participants will be enrolled and assigned to one of three arms: 1. Intervention Arm 1: SnapD application + Real-time CGM + Diabetes Self-Management Education and Support (DSMES) 2. Intervention Arm 2: SnapD application standalone + DSMES 3. Control Arm: DSMES alone Inclusion Criteria Highlights: Adults (18-65 years) diagnosed with T2D with BMI \> 23 kg/m² (overweight/obesity) with HbA1c between 6.5% and 9.0% with Must possess a compatible smartphone/tablet Procedures: Baseline (Visit 1): All participants receive 20-30 minutes of DSMES. Intervention groups receive training on SnapD. Arm 1 receives a 15-day CGM sensor.During Study: Intervention arms log meals via SnapD (at least twice daily). Nutritionists conduct bi-weekly follow-up calls to address technical issues and provide support. End-of-Study (Week 8): Assessment of HbA1c, body weight, waist circumference, lipid profile, and patient-reported outcomes (self-care activities and user satisfaction) Primary Outcome: Mean change in HbA1c from baseline to 8 weeks Secondary Outcomes: Changes in Fasting Plasma Glucose (FPG), body weight, waist circumference, and lipid profiles, Diabetes self-management scores (SDSCA questionnaire), User satisfaction with the SnapD application, Incidence of adverse events (hypoglycemia/hyperglycemia). Significance: This study will provide preliminary evidence on the synergistic benefits of AI-driven nutritional feedback and CGM in a Thai-specific context, supporting the development of scalable, culturally adapted digital health technologies for diabetes management.

Eligibility

Inclusion Criteria:

1. Aged 18 to 65 years, male or female at birth
2. Diagnosed with type 2 Diabetes Mellitus with overweight or obesity (BMI\>23 kg/m²)
3. Hemoglobin A1c (HbA1c) 6.5-9% measured within 3 months prior to the screening date
4. Willing to maintain their current antidiabetic medication regimen without dose adjustment for the entire 8-week study duration
5. Must possess an internet-enabled devices e.g. smartphone, tablet compatible with the SnapD application
6. Able and willing to adhere intervention, including using snapD and CGM

Exclusion Criteria:

1. Currently pregnant, plan pregnancy or breastfeeding during the 8-week study period
2. Current participation in another interventional clinical trial
3. Current use of insulin or incretin-based therapies (e.g., GLP-1 Receptor Agonists, GIP/GLP-1 Receptor Agonists)
4. Presence of severe hearing or visual impairment that, in the investigator's judgment, would preclude the participant from safely and effectively using the SnapD application or the CGM device
5. known contraindication to CGM usage e.g., a history of severe hypersensitivity to the device's materials or adhesive, planing to go on CT-contrasted imaging etc.

Conditions2

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