An interventional study of Sensor augmented MDI therapy plus mobile application in Type 1 Diabetes, sponsored by McGill University. Completed at 1 site in Canada. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2023-11-09.
Sponsored by McGill University · Not applicable, Interventional, and Treatment
McGill artificial pancreas lab has developed a learning algorithm using a reinforcement learning approach to adjust basal and bolus recommendations for high-fat meals and exercise management for individuals with type 1 diabetes on multiple daily injections (MDI) therapy. The reinforcement learning algorithm is integrated with a mobile application that gathers insulin, meal information (carbs (if applicable) and high-fat content), mealtime glucose value, glucose trend at mealtime, and type and timing of postprandial exercise.
The objective of this study is to assess the feasibility of a reinforcement learning algorithm to adjust basal and bolus recommendations for high-fat meals and postprandial exercise management. The investigators hypothesize that the reinforcement learning algorithm will be safe, and participants will get the benefit of improved glucose outcomes and improved patient satisfaction from the start to the end of study.
Participants (aged ≥18) will undergo multiple daily injections (MDI) therapy for 4 months using a freestyle Libre glucose sensor (Abbott Diabetes Care) and a mobile data collection application integrated with the reinforcement learning algorithm.
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This study's enrollment of 15 is below the median of 80 across 8,367 interventional studies indexed under Diabetes Mellitus.
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Exclusion Criteria:
Participants with type 1 diabetes will undergo sensor-augmented MDI therapy for 4 months using a freestyle libre glucose sensor (Abbott Diabetes Care) and a mobile application integrated with the reinforcement learning algorithm.
Device: Sensor augmented MDI therapy plus mobile application
Participants will use the mobile application to calculate their basal dose and to calculate their meal bolus dose by entering their glucose value, carbs (if applicable), fat composition (high fat or not), and type and timing of postprandial exercises. Participants will receive their dosing parameters weekly upon adjustments made by the reinforcement learning algorithm. Participants will be contacted by telephone on Weeks 1, 3, 5, and 7 in case of any technical difficulties or questions. All participants will be asked to complete the: (i) Diabetes treatment satisfaction questionnaire (DTSQ) and hypoglycemia fear survey-II (HFS-II) at baseline, halfway through the intervention, and post-intervention. (ii) mHealth usability questionnaire (MAUQ) at post-intervention.
Comparison of 5 hours postprandial incremental area under the curve of glucose (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial percentage of time below 3.9 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial percentage of time between 3.9 and 10 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial percentage of time between 3.9 and 7.8 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial percentage of time below 3.3 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial percentage of time below 2.8 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial percentage of time above 7.8 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial percentage of time above 10 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial percentage of time above 13.9 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial percentage of time above 16.7 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial mean glucose level (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial standard deviation of glucose levels (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 5 hours postprandial coefficient of variance of glucose levels (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last month of intervention, approximately 4 months
Comparison of 24 hours incremental area under the curve of glucose levels (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours percentage of time below 3.9 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours percentage between 3.9 and 10 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours percentage between 3.9 and 7.8 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours percentage of time below 3.3 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours percentage of time below 2.8 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours percentage of time above 10 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours percentage of time above 13.9 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours percentage of time above 16.7 mmol/L (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours mean glucose level (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours standard deviation of glucose levels (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Comparison of 24 hours coefficient of variance of glucose levels (for high-fat meals and/or postprandial exercise) of the last month algorithm recommendations with the first month recommendations
Time frame: First and last week of intervention, approximately 4 months
Quality of life measure by Hypoglycemic Fear Survey - II: score is the average of 18 items and each item scores ranges 1 to 5 to select (average of higher scores equates to more distress)
Time frame: Pre-intervention, mid-way intervention, and post-intervention, approximately 4 months
Quality of life measure by Hypoglycemic Fear Survey - II: score is the average of 9 items and each item scores ranges 0 to 6 (average of higher scores equates to more satisfied with the treatment)
Time frame: Pre-intervention, mid-way intervention, and post-intervention, approximately 4 months
Mobile app usability questionnaire: score is the average of 16 items and each item scores ranges 0-6 (average of higher scores means higher usability)
Time frame: Post-intervention, approximately 4 months
Plan to share: Yes — The raw data (insulin delivery, glucose levels, individual participant data) could be shared by the corresponding author, ahmad.haidar@mcgill.ca, upon reasonable request for academic purposes, subject to Material Transfer Agreement and approval of McGill University Health Center's Research Ethics Board. All data shared will be deidentified. Study protocol is available with publication.
Supporting information: Study protocol, Icf
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