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

NCT ID: NCT05041621

Last Updated: 2023-11-09

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 15 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2021-07-07
• Study Completion Date: 2023-02-21

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.

Conditions

Type 1 Diabetes

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Study Groups

Sensor augmented MDI therapy plus mobile application with reinforcement learning algorithm

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.

Group Type: EXPERIMENTAL

Sensor augmented MDI therapy plus mobile application

Intervention Type: DEVICE

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.

Interventions

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.

Intervention Type: DEVICE

Eligibility Criteria

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

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

McGill University

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Ahmad Haidar, PhD

Role: STUDY_CHAIR

McGill University Health Centre/Research Institute of the McGill University Health Centre

Michael Tsoukas, MD

Role: PRINCIPAL_INVESTIGATOR

McGill University Health Centre/Research Institute of the McGill University Health Centre

Locations

Clinique Médicale Hygea

Montreal, Quebec, Canada

Countries

Canada

Other Identifiers

2021-47375

Identifier Type: -

Identifier Source: org_study_id