Skip to content

A Learning Algorithm for MDI Individuals With Type 1 Diabetes to Adjust Recommendations for High Fat Meals and Exercise Management

A Single Arm Pilot Study to Assess the Feasibility of a Learning Algorithm to Automatically Adjust Basal and Bolus Recommendations for High Fat Meals and Exercise Management for Individuals With Type 1 Diabetes on MDI Therapy

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05041621
Enrollment
15
Registered
2021-09-13
Start date
2021-07-07
Completion date
2023-02-21
Last updated
2023-11-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Type 1 Diabetes

Brief summary

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.

Detailed description

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.

Interventions

DEVICESensor 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.

Sponsors

McGill University
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
TREATMENT
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

1. Signed and dated informed consent form 2. Females and males ≥ 18 years old 3. Diagnosis of type 1 diabetes of ≥ 12 months based on the clinical investigator's judgement 4. Undergoing MDI therapy 5. A self-reported diet that consists of at least 3 high-fat meals per week or participation in exercise for at least 30 minutes, two times per week

Exclusion criteria

1. Current use of any non-insulin antihyperglycemic medication (SGLT2 inhibitors, GLP 1 receptor agonists, metformin…) 2. Current use of glucocorticoid medication, except inhaled and/or at low stable doses 3. Pregnancy 4. Use of isophane insulin (NPH) or intermediate-acting insulin 5. Significant clinical nephropathy, neuropathy, retinopathy as per the clinical investigator's judgement 6. Acute macrovascular event (ex: acute coronary syndrome or cardiac surgery) within 6 months of admission 7. Severe diabetes ketoacidosis and/or hypoglycemia within one month of admission 8. Other severe medical illness that the clinical investigator considers may interfere with participation in or completion of the study 9. An inability or unwillingness to comply with study procedures as per the clinical investigator's judgement

Design outcomes

Primary

MeasureTime frame
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 recommendationsFirst 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 recommendationsFirst and last month of intervention, approximately 4 months

Secondary

MeasureTime frame
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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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 recommendationsFirst 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)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)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)Post-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 recommendationsFirst and last week 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 recommendationsFirst and last month of intervention, approximately 4 months

Countries

Canada

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 6, 2026