Insulin Titration System Based on Deep Learning

NCT05409391 | Completed DMC

• 1 other identifier: ZSE-202205
• Study Type: interventional
• Target: 16
• Locations: 1 country
• Sites: 1

Brief Summary

This is an open-labeled, one-arm intervention trial to access the effect and safety of the Insulin Titration System Based on Deep Learning in patients with Type 2 Diabetes Mellitus.

Conditions

Diabetes Mellitus Type 2 - Insulin-Treated

Outcome Measures

Primary Outcomes (1)

• mean daily blood glucose concentration

  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 Outcomes (4)

• glucose concentration in target range (TIR) of 3.9-10.0 mmol/L

  5 days

• glucose concentration above range (10.1-13.9 mmol/L or >13.9 mmol/L)

  5 days

• glucose concentration below range (3.0-3.8 mmol/L or <3.0 mmol/L)

  5 days

• glycemic variability

  5 days

Study Arms (1)

AI

EXPERIMENTAL

Insulin Titration System Based on Deep Learning

Device: Insulin Titration System

Interventions

Insulin Titration System DEVICE

A noval insulin titration system, which is based on deep learning

AI

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• type 2 diabetes
• age of 18-75 years
• HbA1c between 7.0% and 11.0%.

You may not qualify if:

• 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

Sponsors & Collaborators

• Shanghai Zhongshan Hospital: lead

Study Sites (1)

Department of Endocrinology, Zhongshan Hospital Fudan University

Shanghai, China

Location

Related Publications (1)

• Wang G, Liu X, Ying Z, Yang G, Chen Z, Liu Z, Zhang M, Yan H, Lu Y, Gao Y, Xue K, Li X, Chen Y. Optimized glycemic control of type 2 diabetes with reinforcement learning: a proof-of-concept trial. Nat Med. 2023 Oct;29(10):2633-2642. doi: 10.1038/s41591-023-02552-9. Epub 2023 Sep 14.

  PMID: 37710000 DERIVED

Study Officials

• Xiaoying Li

  Shanghai Zhongshan Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: June 1, 2022
• First Posted: June 8, 2022
• Study Start: June 15, 2022
• Primary Completion: October 6, 2022
• Study Completion: October 6, 2022
• Last Updated: June 7, 2023

Record last verified: 2023-06

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)