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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:
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| SnapD + CGM | Experimental | Use of the AI-powered SnapD application to log meals (at least 2 times/day) combined with a 15-day real-time CGM session. Participants also receive one session of Diabetes Self-Management Education and Support (DSMES). |
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| SnapD Application only | Experimental | Use of the SnapD application as a standalone digital food diary to log meals (at least 2 times/day) throughout the 8-week study. Participants receive one session of DSMES. |
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| Standard Care (DSMES) | Placebo Comparator | Standard of care including one session of DSMES (20-30 minutes) and self-directed behavioral changes. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| SnapD | Device | SnapD, developed by the Division of Endocrinology and Metabolism, Department of Medicine, Ramathibodi Hospital, is a Progressive Web App. It is built using React 18.3.1, TypeScript, and Vite for responsive performance on both mobile and desktop platforms. The application utilizes Supabase for database management, which operates on a PostgreSQL backend. |
| Measure | Description | Time Frame |
|---|---|---|
| To evaluate the efficacy of two intervention arms on glycemic control | HbA1c level(%) | baseline, 8 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| To assess changes in other glycemic parameter | Fasting plasma glucose(mg/dL) | baseline, 8 weeks |
| To assess changes in anthropometric measurements | Body Mass Index(Kg/m2) |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Supasuta Wongdama, MD | Contact | +6690-575-4190 | supasuta.won@gmail.com |
| Name | Affiliation | Role |
|---|---|---|
| Supasuta Wongdama | Ramathibodi Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Department of Medicine, Ramathibodi Hospital, | Recruiting | Bangkok | Bangkok | 10400 | Thailand |
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| ID | Term |
|---|---|
| D009765 | Obesity |
| ID | Term |
|---|---|
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
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This is a randomized, open-label, parallel-group, superiority pilot study designed with a 1:1:1 allocation ratio. The study compares two digital intervention arms against a standard of care control group over an 8-week period.
Arm 1 (SnapD + CGM): Participants use the SnapD AI-powered application for food logging combined with a 15-day session of real-time Continuous Glucose Monitoring (CGM).
Arm 2 (SnapD only): Participants use the SnapD application as a standalone digital food diary.
Control Arm: Participants receive standard Diabetes Self-Management Education and Support (DSMES) only.
The randomization uses a permuted variable block size design to ensure balanced allocation. Allocation concealment is maintained using sequentially numbered, opaque, sealed envelopes. The study aims to evaluate the feasibility and preliminary efficacy of these tools in patients with type 2 diabetes and overweight or obesity.
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This is an open-label study. Blinding of participants and investigators is not feasible due to the distinct procedural nature of the assigned interventions (e.g., the visible use of a wearable CGM device and a specific mobile application). However, to minimize bias in the assignment, allocation concealment is ensured by using sequentially numbered, opaque, sealed envelopes prepared by a non-investigator.
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| Linx CGM | Device | The Linx CGM system, manufactured by Connect Diagnostics, is a real-time device that measures glucose concentrations in the interstitial fluid. It is an all-in-one device, integrating the glucose sensor, applicator, and transmitter into a single unit. The device has a diameter not exceeding 22 mm and a weight not exceeding 2.2 g. The sensor has a maximum operational life (wear time) of 15 days. It demonstrates a Mean Absolute Relative Difference (MARD) not exceeding 8.67%, which meets the standard accuracy requirement of <10%. This device was registered as a medical device by the Thai Food and Drug Administration (Thai FDA), Ministry of Public Health, in January 2025, for the indication of management of diabetes in adults age 18 and older (as shown in the attached document) . |
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| Diabetes Self-Management Education (DSMES) | Other | Participants will receive 1 single session of DSMES, 20-30 minutes/session. This single session will be delivered at the baseline visit only. All personnel providing DSMES are Certified Dietitians (CD) and/or have passed the Certified Diabetes Educator (Thai CDE) examination |
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| baseline, 8 weeks |
| To evaluate changes in metabolic parameters | • change in systolic and diastolic blood pressure (mmHg) | baseline, 8 weeks |
| To evaluate changes in diabetic self-management activities via questionnaire | A modified version of the SDSCA tool, developed by Rattanaporn Jeerawattana, encompassing domains of diet, exercise, self-monitoring, foot care, and medication. The total score ranges from 0 to 133, where higher scores indicate better diabetes self-care activities. | Baseline, 8 weeks |
| • To evaluate user satisfaction scores for the SnapD application | Name of the questionnaire is User satisfaction with the SnapD and CGM application. It was an a self-developed questionnaire validated by experts. The total score ranges from 7 to 35, where higher scores indicate better user satisfaction. | 8 weeks |
| • To assess adverse events about glycemic control | • Incidence of hypoglycemia and/or hyperglycemia | up to 8 weeks |
| To assess changes in anthropometric measurements | change in waist circumference(cm) | baseline, 8 weeks |
| Change in metabolic parameters | change in lipid profile including serum Total Cholesterol, Triglyceride-Cholesterol, HDL-Cholesterol, LDL-Cholesterol | baseline, 8 weeks |
| D001835 |
| Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |