Insulin Titration System Based on Deep Learning
Study to Assess the Efficacy and Safety of Insulin Titration System Based on Deep Learning on Glucose Control in Type 2 Diabetes Mellitus Patients
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Xiaoying Li
- Phone Number: +862164041990
- Email: li.xiaoying@zs-hospital.sh.cn
Study Contact Backup
- Name: Ying Chen
- Email: chen.ying4@zs-hospital.sh.cn
Study Locations
-
-
-
Shanghai, China
- Department of Endocrinology, Zhongshan Hospital Fudan University
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- type 2 diabetes
- age of 18-75 years
- HbA1c between 7.0% and 11.0%.
Exclusion Criteria:
- subjects with acute complications of diabetes, such as ketoacidosis or hyperglycemic hyperosmolar state;
- BMI ≥ 45kg/m2;
- women who are pregnant or breast-feeding;
- subjects with severe cardiac, hepatic, renal diseases; subjects with any psychiatric or psychological diseases;
- subjects with severe edema, infections or peripheral circulation disorders, receiving surgery during hospitalization;
- subjects who could not comply with the protocol
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: AI
Insulin Titration System Based on Deep Learning
|
A noval insulin titration system, which is based on deep learning
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
mean daily blood glucose concentration
Time Frame: 5 days
|
For each patient, capillary glucose concentration was measured at 7 time points of fasting, after breakfast, before and after lunch, before and after dinner, and before bedtime a day using Glucometer (Glupad, Sinomedisite, China).
Capillary glucose measurements were performed by the nurse staff according to standard procedures with a point-of-care testing device, which is integrated into the HIS system.
The primary outcome is the difference in glycemia control as measured by mean daily blood glucose concentration during the intervention period.
|
5 days
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
glucose concentration in target range (TIR) of 3.9-10.0 mmol/L
Time Frame: 5 days
|
TIR measured by CGM and Capillary glucose measurements, respectively
|
5 days
|
|
glucose concentration above range (10.1-13.9 mmol/L or >13.9 mmol/L)
Time Frame: 5 days
|
TAR measured by CGM and Capillary glucose measurements, respectively
|
5 days
|
|
glucose concentration below range (3.0-3.8 mmol/L or <3.0 mmol/L)
Time Frame: 5 days
|
TBR measured by CGM and Capillary glucose measurements, respectively
|
5 days
|
|
glycemic variability
Time Frame: 5 days
|
glycemic variability measured by CGM and Capillary glucose measurements, respectively
|
5 days
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Xiaoying Li, Shanghai Zhongshan Hospital
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- ZSE-202205
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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