| Unique ID issued by UMIN | UMIN000060579 |
|---|---|
| Receipt number | R000069291 |
| Scientific Title | Efficacy of a Diabetes Onset Prevention App System Utilizing Continuous Glucose Monitoring and Artificial Intelligence in Individuals at High Risk for Type 2 Diabetes |
| Date of disclosure of the study information | 2026/02/13 |
| Last modified on | 2026/02/04 14:53:13 |
Efficacy of a Diabetes Onset Prevention App System Utilizing Continuous Glucose Monitoring and Artificial Intelligence in Individuals at High Risk for Type 2 Diabetes
Evaluation of an AI and Continuous Glucose Monitoring Based App to Support the Prevention of Type 2 Diabetes
Efficacy of a Diabetes Onset Prevention App System Utilizing Continuous Glucose Monitoring and Artificial Intelligence in Individuals at High Risk for Type 2 Diabetes
Evaluation of an A- and Continuous Glucose Monitoring Based App to Support the Prevention of Type 2 Diabetes
| Japan |
Prediabetes
| Endocrinology and Metabolism |
Others
NO
As existing evidence is limited to improvements in surrogate markers, this study will conduct a 1-year randomized controlled trial using an improved system, with diabetes incidence as the primary endpoint, to establish empirical evidence for the prevention of type 2 diabetes.
Efficacy
The incidence of diabetes mellitus before and after the intervention will be compared between the intervention group and the control group.
Interventional
Parallel
Randomized
Individual
Open -no one is blinded
Active
NO
YES
2
Prevention
| Behavior,custom |
Intervention using a continuous glucose monitoring function + AI-powered disease prevention application system
Standard diabetes prevention guidance
| 20 | years-old | <= |
| 70 | years-old | >= |
Male and Female
1. Individuals with HbA1c < 6.5 percent and fasting blood glucose < 126 mg/dL and random blood glucose < 200 mg/dL
2. Individuals meeting condition 1 HbA1c >= 6.0 percent and fasting blood glucose >= 103 mg/dL or condition 2 HbA1c >= 6.2 percent or condition 3 fasting blood glucose >= 112 mg/dL
3. Individuals aged 20 years or older and 70 years or younger at the time of consent acquisition
4. Individuals with a BMI >= 25 kg/m2 and < 40 kg/m2
5.Individuals capable of using the smartphone application employed in the research
6. Individuals who have received an explanation of the research content and have provided consent to participate in the study
1.Individuals currently receiving treatment for diabetes
2.Individuals deemed inappropriate for participation by the attending physician
660
| 1st name | Masaru |
| Middle name | |
| Last name | Kitazawa |
Graduate School of Medical and Dental Sciences, Niigata University
Department of Haematology, Endocrinology and Metabolism
9518510
754 Asahimachidori Ichibancho, Chuo-ku, Niigata City, Niigata, Japan
0253689026
m-kitazawa.med@niigata-u.ac.jp
| 1st name | Masaru |
| Middle name | |
| Last name | Kitazawa |
Graduate School of Medical and Dental Sciences, Niigata University
Department of Haematology, Endocrinology and Metabolism
9518510
754 Asahimachidori Ichibancho, Chuo-ku, Niigata City, Niigata, Japan
0253689026
m-kitazawa.med@niigata-u.ac.jp
Niigata University
Japan Agency for Medical Research and Development (AMED)
Japanese Governmental office
Niigata University Research Ethics Committee for Studies Involving Human Subjects
754 Asahimachidori Ichibancho, Chuo-ku, Niigata City, Niigata, Japan
025-227-2625
ethics@adm.niigata-u.ac.jp
NO
| 2026 | Year | 02 | Month | 13 | Day |
Unpublished
Preinitiation
| 2026 | Year | 02 | Month | 04 | Day |
| 2026 | Year | 02 | Month | 13 | Day |
| 2028 | Year | 02 | Month | 28 | Day |
| 2026 | Year | 02 | Month | 04 | Day |
| 2026 | Year | 02 | Month | 04 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000069291