A Novel mHealth Application Guided by an Optimization Algorithm for T1D Sensor-Augmented Insulin Injection Users
NCT04123054 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 84
Last updated 2024-05-16
Summary
The Artificial Pancreas lab at McGill University has developed an optimization algorithm for adults with Type 1 Diabetes (T1D) on Multiple Daily Injection (MDI) therapy with the adjunctive use of glucose sensor technology, collectively known as sensor-augmented MDI therapy. The algorithm is designed to estimate optimal basal-bolus parameters based on the patient's glucose, insulin and meal data over several days. The investigators hope that this algorithm will be better able to improve long-term glycemic targets by reducing HbA1c levels compared to sensor-augmented MDI therapy alone.
Conditions
- Diabetes Mellitus
- Diabetes Mellitus, Type 1
Interventions
- DEVICE
-
Mobile App
Participants will use the mobile app to log their daily basal dose and calculate their meal doses by entering their sensor glucose value (and amount of meal carbohydrates if applicable) using the built-in bolus calculator.
- DEVICE
-
Mobile App + Basal-Bolus Optimization Algorithm
Participants will use the mobile app to log their daily basal dose and calculate their meal doses by entering their sensor glucose value (and amount of meal carbohydrates if applicable) using the built-in bolus calculator. In addition, participants will receive weekly app notifications with personalized recommendations for insulin parameter adjustments made by the optimization algorithm.
Sponsors & Collaborators
- lead OTHER
Principal Investigators
-
Michael Tsoukas, MD · RI-MUHC
Study Design
- Allocation
- RANDOMIZED
- Purpose
- TREATMENT
- Masking
- NONE
- Model
- PARALLEL
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2020-03-05
- Primary Completion
- 2023-12-21
- Completion
- 2024-01-12
Countries
- Canada
Study Locations
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