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AI Health Assistant and Type 2 Diabetes

Primary Purpose

Health Behavior, Type2 Diabetes Mellitus

Status
Not yet recruiting
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
AI health assistant
Sponsored by
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional treatment trial for Health Behavior focused on measuring Type 2 Diabetes, AI health assistant, Off hospital management

Eligibility Criteria

18 Years - 65 Years (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria:

The diagnostic criteria of T2DM patients are the diagnostic criteria of the 2017 China guidelines for the prevention and treatment of type 2 diabetes HbA1c 7.5-13% Age: 18-65y BMI 18.5-30kg/m2 The course of disease is less than 5 years Have good cognitive ability and can correctly use health assistants

Exclusion Criteria:

Acute complications of diabetes (diabetes ketosis, etc.) Diabetes complicating pregnancy or preparing for pregnancy HbA1c < 7.5% or > 13% Age < 18y or age > 65y Pre pregnancy BMI < 18.5 or > 30kg / m2 Severe liver and kidney dysfunction (ALT greater than 2.5 times the upper limit of normal, EGFR less than 45 ml / min / 1.73m2) Using drugs that may affect blood glucose are being used (including steroids, hydroxyprogesterone hexanoate, anti AIDS drugs, etc.)

Sites / Locations

    Arms of the Study

    Arm 1

    Arm 2

    Arm Type

    Experimental

    No Intervention

    Arm Label

    AI health assistant

    Routine treatment group

    Arm Description

    An AI health assistant suitable for diabetes patients has been developed. It has the functions of automatically uploading blood pressure, blood glucose data, intelligent reminder, automatic analysis of reports inside and outside the hospital, intelligent question and answer, etc. it is simple to operate, highly interactive, and maximizes the management level of diabetes patients outside the hospital.

    Perform routine management and follow-up without using AI health assistant

    Outcomes

    Primary Outcome Measures

    HbA1c compliance rate
    Compliance rate of HbA1c < 7%
    Blood pressure compliance rate
    Proportion of patients with blood pressure < 130 / 80mmHg
    Compliance rate of total cholesterol
    Proportion of patients with total cholesterol < 4.5mmol/l
    Compliance rate of BMI (Body Mass Index)
    Proportion of patients with BMI < 24 kg/m2

    Secondary Outcome Measures

    Incidence of hypoglycemia
    Number of attacks with blood glucose less than 3.8mmol/l

    Full Information

    First Posted
    September 4, 2022
    Last Updated
    September 12, 2022
    Sponsor
    Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
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    1. Study Identification

    Unique Protocol Identification Number
    NCT05539066
    Brief Title
    AI Health Assistant and Type 2 Diabetes
    Official Title
    Application of AI Health Assistant in Out of Hospital Management of Patients With Type 2 Diabetes
    Study Type
    Interventional

    2. Study Status

    Record Verification Date
    September 2022
    Overall Recruitment Status
    Not yet recruiting
    Study Start Date
    October 1, 2022 (Anticipated)
    Primary Completion Date
    September 30, 2024 (Anticipated)
    Study Completion Date
    September 30, 2024 (Anticipated)

    3. Sponsor/Collaborators

    Responsible Party, by Official Title
    Principal Investigator
    Name of the Sponsor
    Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

    4. Oversight

    Studies a U.S. FDA-regulated Drug Product
    No
    Studies a U.S. FDA-regulated Device Product
    No
    Data Monitoring Committee
    Yes

    5. Study Description

    Brief Summary
    The developed health assistant has the functions of intelligent analysis of health data inside and outside the hospital, health reminder, etc. The advantages of AI health assistant management group compared with conventional management group in terms of comprehensive compliance rate, metabolic index level, hypoglycemia incidence rate was further studied.
    Detailed Description
    The investigators have developed an AI health assistant suitable for diabetes patients, which has the functions of automatically uploading blood pressure, blood glucose data, intelligent reminder, automatic analysis of reports inside and outside the hospital, intelligent question and answer, etc. it is simple to operate, highly interactive, and maximizes the management level of diabetes patients outside the hospital. Through AI personal health assistant, 196 diabetes patients were managed to further improving the comprehensive compliance rate of metabolic indicators such as blood glucose and blood pressure of diabetes patients, improving the patients' self-management ability.

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Health Behavior, Type2 Diabetes Mellitus
    Keywords
    Type 2 Diabetes, AI health assistant, Off hospital management

    7. Study Design

    Primary Purpose
    Treatment
    Study Phase
    Not Applicable
    Interventional Study Model
    Parallel Assignment
    Masking
    None (Open Label)
    Allocation
    Randomized
    Enrollment
    196 (Anticipated)

    8. Arms, Groups, and Interventions

    Arm Title
    AI health assistant
    Arm Type
    Experimental
    Arm Description
    An AI health assistant suitable for diabetes patients has been developed. It has the functions of automatically uploading blood pressure, blood glucose data, intelligent reminder, automatic analysis of reports inside and outside the hospital, intelligent question and answer, etc. it is simple to operate, highly interactive, and maximizes the management level of diabetes patients outside the hospital.
    Arm Title
    Routine treatment group
    Arm Type
    No Intervention
    Arm Description
    Perform routine management and follow-up without using AI health assistant
    Intervention Type
    Device
    Intervention Name(s)
    AI health assistant
    Intervention Description
    To study the advantages of AI health assistant management group compared with conventional management group in terms of comprehensive compliance rate, metabolic index level, hypoglycemia incidence rate, and mastery of diabetes related knowledge.
    Primary Outcome Measure Information:
    Title
    HbA1c compliance rate
    Description
    Compliance rate of HbA1c < 7%
    Time Frame
    6 months
    Title
    Blood pressure compliance rate
    Description
    Proportion of patients with blood pressure < 130 / 80mmHg
    Time Frame
    6 months
    Title
    Compliance rate of total cholesterol
    Description
    Proportion of patients with total cholesterol < 4.5mmol/l
    Time Frame
    6 months
    Title
    Compliance rate of BMI (Body Mass Index)
    Description
    Proportion of patients with BMI < 24 kg/m2
    Time Frame
    6 months
    Secondary Outcome Measure Information:
    Title
    Incidence of hypoglycemia
    Description
    Number of attacks with blood glucose less than 3.8mmol/l
    Time Frame
    6 months

    10. Eligibility

    Sex
    All
    Minimum Age & Unit of Time
    18 Years
    Maximum Age & Unit of Time
    65 Years
    Accepts Healthy Volunteers
    No
    Eligibility Criteria
    Inclusion Criteria: The diagnostic criteria of T2DM patients are the diagnostic criteria of the 2017 China guidelines for the prevention and treatment of type 2 diabetes HbA1c 7.5-13% Age: 18-65y BMI 18.5-30kg/m2 The course of disease is less than 5 years Have good cognitive ability and can correctly use health assistants Exclusion Criteria: Acute complications of diabetes (diabetes ketosis, etc.) Diabetes complicating pregnancy or preparing for pregnancy HbA1c < 7.5% or > 13% Age < 18y or age > 65y Pre pregnancy BMI < 18.5 or > 30kg / m2 Severe liver and kidney dysfunction (ALT greater than 2.5 times the upper limit of normal, EGFR less than 45 ml / min / 1.73m2) Using drugs that may affect blood glucose are being used (including steroids, hydroxyprogesterone hexanoate, anti AIDS drugs, etc.)
    Central Contact Person:
    First Name & Middle Initial & Last Name or Official Title & Degree
    Liping Gu, doctor
    Phone
    +86（021）63240090
    Email
    guliping1980@126.com
    Overall Study Officials:
    First Name & Middle Initial & Last Name & Degree
    Yufan Wang, doctor
    Organizational Affiliation
    Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
    Official's Role
    Study Chair

    12. IPD Sharing Statement

    Plan to Share IPD
    No

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    AI Health Assistant and Type 2 Diabetes

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