The Evaluation of Artificial Intelligence in Lifestyle Management of Diabetic Patients in Community
NCT ID: NCT06118671
Last Updated: 2023-11-07
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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NOT_YET_RECRUITING
NA
460 participants
INTERVENTIONAL
2023-11-07
2024-11-07
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
OTHER
SINGLE
Study Groups
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Intervention group
giving personalized lifestyle intervention suggestions through AI
personalized lifestyle intervention by AI
The experimental group completed the basic information, diet structure, use of dietary supplements, living habits, and exercise according to the AI scale (AI scale can be entered through we-chat mini program search), and provided personalized lifestyle intervention plan according to the survey result.
Control group
giving routine lifestyle suggestions
No interventions assigned to this group
Interventions
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personalized lifestyle intervention by AI
The experimental group completed the basic information, diet structure, use of dietary supplements, living habits, and exercise according to the AI scale (AI scale can be entered through we-chat mini program search), and provided personalized lifestyle intervention plan according to the survey result.
Eligibility Criteria
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Inclusion Criteria
* 18-80 years old, gender is not limited
* Diagnosed diabetes (according to WHO1999 diagnostic criteria)
* Well compliance
Exclusion Criteria
* Poor blood glucose control (HbA1c\>11%)
* A history of malignant tumor
* Abnormal liver or renal function \[defined as alanine aminotransferase (ALT)\>2.5 times higher than normal range, or eGFR\<30 mL/min per 1.73 m2\]
* Poor blood pressure control \[systolic blood pressure (SBP)\>180mmHg, or diastolic blood pressure (DBP)\>110mmHg
* With severe heart disease, cardiac function worse than grade II, anemia (Hb\<9.0g/d1)
* Blood routine test indicates that the white blood cell count (WBC) \<3\*109/L
* Body Mass Index (BMI)\<18.5 or ≥35kg/m2
* Drug or alcohol abuse
* Accompanying mental disorder who can't collaborate
* Abnormal digestion and absorption function
* Other endocrine diseases
* Other chronic diseases needed long-term glucocorticoid treatment
* With severe infection, immune dysfunction
18 Years
80 Years
ALL
No
Sponsors
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Chongqing Medical University
OTHER
Responsible Party
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Qifu Li
Professor.
Principal Investigators
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Jinbo Hu, PhD
Role: STUDY_CHAIR
First Affiliated Hospital of Chongqing Medical University
Locations
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Jinbo Hu
Chongqing, Chongqing Municipality, China
Countries
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Central Contacts
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Facility Contacts
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References
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Dobson R, Whittaker R, Jiang Y, Maddison R, Shepherd M, McNamara C, Cutfield R, Khanolkar M, Murphy R. Effectiveness of text message based, diabetes self management support programme (SMS4BG): two arm, parallel randomised controlled trial. BMJ. 2018 May 17;361:k1959. doi: 10.1136/bmj.k1959.
Wu Y, Min H, Li M, Shi Y, Ma A, Han Y, Gan Y, Guo X, Sun X. Effect of Artificial Intelligence-based Health Education Accurately Linking System (AI-HEALS) for Type 2 diabetes self-management: protocol for a mixed-methods study. BMC Public Health. 2023 Jul 11;23(1):1325. doi: 10.1186/s12889-023-16066-z.
Toi PL, Anothaisintawee T, Chaikledkaew U, Briones JR, Reutrakul S, Thakkinstian A. Preventive Role of Diet Interventions and Dietary Factors in Type 2 Diabetes Mellitus: An Umbrella Review. Nutrients. 2020 Sep 6;12(9):2722. doi: 10.3390/nu12092722.
Viguiliouk E, Kendall CW, Kahleova H, Rahelic D, Salas-Salvado J, Choo VL, Mejia SB, Stewart SE, Leiter LA, Jenkins DJ, Sievenpiper JL. Effect of vegetarian dietary patterns on cardiometabolic risk factors in diabetes: A systematic review and meta-analysis of randomized controlled trials. Clin Nutr. 2019 Jun;38(3):1133-1145. doi: 10.1016/j.clnu.2018.05.032. Epub 2018 Jun 13.
Nundy S, Dick JJ, Chou CH, Nocon RS, Chin MH, Peek ME. Mobile phone diabetes project led to improved glycemic control and net savings for Chicago plan participants. Health Aff (Millwood). 2014 Feb;33(2):265-72. doi: 10.1377/hlthaff.2013.0589.
Arambepola C, Ricci-Cabello I, Manikavasagam P, Roberts N, French DP, Farmer A. The Impact of Automated Brief Messages Promoting Lifestyle Changes Delivered Via Mobile Devices to People with Type 2 Diabetes: A Systematic Literature Review and Meta-Analysis of Controlled Trials. J Med Internet Res. 2016 Apr 19;18(4):e86. doi: 10.2196/jmir.5425.
Sarkar U, Karter AJ, Liu JY, Adler NE, Nguyen R, Lopez A, Schillinger D. The literacy divide: health literacy and the use of an internet-based patient portal in an integrated health system-results from the diabetes study of northern California (DISTANCE). J Health Commun. 2010;15 Suppl 2(Suppl 2):183-96. doi: 10.1080/10810730.2010.499988.
Chiavaroli L, Lee D, Ahmed A, Cheung A, Khan TA, Blanco S, Mejia, Mirrahimi A, Jenkins DJA, Livesey G, Wolever TMS, Rahelic D, Kahleova H, Salas-Salvado J, Kendall CWC, Sievenpiper JL. Effect of low glycaemic index or load dietary patterns on glycaemic control and cardiometabolic risk factors in diabetes: systematic review and meta-analysis of randomised controlled trials. BMJ. 2021 Aug 4;374:n1651. doi: 10.1136/bmj.n1651.
Wagner EH, Sandhu N, Newton KM, McCulloch DK, Ramsey SD, Grothaus LC. Effect of improved glycemic control on health care costs and utilization. JAMA. 2001 Jan 10;285(2):182-9. doi: 10.1001/jama.285.2.182.
Other Identifiers
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BDT-CDR
Identifier Type: -
Identifier Source: org_study_id
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