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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.
The objective of this exploratory study is to test the efficacy of this optimization algorithm with sensor-augmented MDI therapy in improving long-term glucose control, using a randomized parallel study over three months. The optimization algorithm may lead to the automation of physician-adjusted basal rate and Insulin to Carb Ratio (ICR) adjustments.
84 adults with type 1 diabetes will be enrolled in the study, where they will randomly undergo one of two interventions:
1. Sensor-Augmented MDI Therapy: Participants will undergo their usual MDI therapy along with a Freestyle Libre glucose sensor (Abbott Diabetes Care), and a data collection mobile application that collects insulin and meal data.
2. Sensor-Augmented MDI Therapy with the Optimization Algorithm: Participants will undergo MDI therapy with a Freestyle Libre glucose sensor (Abbott Diabetes Care) and a data collection mobile application that collects insulin and meal data. Every week, participants will have their insulin doses adjusted by the optimization algorithm's recommendations.
MDI (multiple daily injections) with Optimization Algorithm
McGill University Health Centre
Not yet recruiting
Published on BioPortfolio: 2019-10-17T11:03:51-0400
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