Insulin Titration System Based on Deep Learning
- Conditions
- Diabetes Mellitus Type 2 - Insulin-Treated
- Interventions
- Device: Insulin Titration System
- Registration Number
- NCT05409391
- Lead Sponsor
- Shanghai Zhongshan Hospital
- 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.
- Detailed Description
The study enrolls 13 patients with Type 2 Diabetes in Zhongshan Hospital who are on treatment with insulin. After screening for the inclusion and exclusion criteria, eligible patients will receive insulin dosage titration set by the Insulin Titration System Based on Deep Learning in the intervention trial. The goal of insulin therapy was to achieve preprandial capillary blood glucose between 5.6-7.8 mmol/L and postprandial capillary glucose less than 10.0mmol/L. All patients are studied for 5 consecutive days or untill hospital discharge. 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. And continuous glucose monitoring (CGM) was performed using flash glucose monitoring (Abbott Freestyle Libre, USA) placed on the upper left arm. This study will be conducted in the Department of Endocrinology, Zhongshan Hospital,Fudan University.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 16
- type 2 diabetes
- age of 18-75 years
- HbA1c between 7.0% and 11.0%.
- 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 & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description AI Insulin Titration System Insulin Titration System Based on Deep Learning
- Primary Outcome Measures
Name Time Method mean daily blood glucose concentration 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.
- Secondary Outcome Measures
Name Time Method glycemic variability 5 days glycemic variability measured by CGM and Capillary glucose measurements, respectively
glucose concentration below range (3.0-3.8 mmol/L or <3.0 mmol/L) 5 days TBR measured by CGM and Capillary glucose measurements, respectively
glucose concentration in target range (TIR) of 3.9-10.0 mmol/L 5 days TIR measured by CGM and Capillary glucose measurements, respectively
glucose concentration above range (10.1-13.9 mmol/L or >13.9 mmol/L) 5 days TAR measured by CGM and Capillary glucose measurements, respectively
Trial Locations
- Locations (1)
Department of Endocrinology, Zhongshan Hospital Fudan University
🇨🇳Shanghai, China