AI Health Assistant and Type 2 Diabetes

September 12, 2022 updated by: Liping Gu, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Application of AI Health Assistant in Out of Hospital Management of Patients With Type 2 Diabetes

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.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

  1. 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.
  2. 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.

Study Type

Interventional

Enrollment (Anticipated)

196

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 65 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

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.)

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: AI health assistant
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.
Device: AI health assistant
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.
No Intervention: Routine treatment group
Perform routine management and follow-up without using AI health assistant

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
HbA1c compliance rate
Time Frame: 6 months
Compliance rate of HbA1c < 7%
6 months
Blood pressure compliance rate
Time Frame: 6 months
Proportion of patients with blood pressure < 130 / 80mmHg
6 months
Compliance rate of total cholesterol
Time Frame: 6 months
Proportion of patients with total cholesterol < 4.5mmol/l
6 months
Compliance rate of BMI (Body Mass Index)
Time Frame: 6 months
Proportion of patients with BMI < 24 kg/m2
6 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Incidence of hypoglycemia
Time Frame: 6 months
Number of attacks with blood glucose less than 3.8mmol/l
6 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Investigators

  • Study Chair: Yufan Wang, doctor, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Anticipated)

October 1, 2022

Primary Completion (Anticipated)

September 30, 2024

Study Completion (Anticipated)

September 30, 2024

Study Registration Dates

First Submitted

September 4, 2022

First Submitted That Met QC Criteria

September 12, 2022

First Posted (Actual)

September 14, 2022

Study Record Updates

Last Update Posted (Actual)

September 14, 2022

Last Update Submitted That Met QC Criteria

September 12, 2022

Last Verified

September 1, 2022

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 21Y11904800

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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