search
Back to results

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

Primary Purpose

Type 1 Diabetes

Status
Recruiting
Phase
Not Applicable
Locations
Canada
Study Type
Interventional
Intervention
Sensor augmented MDI therapy plus mobile application
Sponsored by
McGill University
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional treatment trial for Type 1 Diabetes

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

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

Sites / Locations

  • Clinique Médicale HygeaRecruiting

Arms of the Study

Arm 1

Arm Type

Experimental

Arm Label

Sensor augmented MDI therapy plus mobile application with reinforcement learning algorithm

Arm Description

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.

Outcomes

Primary Outcome Measures

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
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

Secondary Outcome Measures

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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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)
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)

Full Information

First Posted
July 26, 2021
Last Updated
April 19, 2022
Sponsor
McGill University
search

1. Study Identification

Unique Protocol Identification Number
NCT05041621
Brief Title
A Learning Algorithm for MDI Individuals With Type 1 Diabetes to Adjust Recommendations for High Fat Meals and Exercise Management
Official Title
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
Study Type
Interventional

2. Study Status

Record Verification Date
April 2022
Overall Recruitment Status
Recruiting
Study Start Date
July 7, 2021 (Actual)
Primary Completion Date
December 2022 (Anticipated)
Study Completion Date
December 2022 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
McGill University

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No

5. Study Description

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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Type 1 Diabetes

7. Study Design

Primary Purpose
Treatment
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
15 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
Sensor augmented MDI therapy plus mobile application with reinforcement learning algorithm
Arm Type
Experimental
Arm Description
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.
Intervention Type
Device
Intervention Name(s)
Sensor augmented MDI therapy plus mobile application
Intervention Description
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.
Primary Outcome Measure Information:
Title
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
Title
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
Secondary Outcome Measure Information:
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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
Title
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

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria: Signed and dated informed consent form Females and males ≥ 18 years old Diagnosis of type 1 diabetes of ≥ 12 months based on the clinical investigator's judgement Undergoing MDI therapy 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: Current use of any non-insulin antihyperglycemic medication (SGLT2 inhibitors, GLP 1 receptor agonists, metformin…) Current use of glucocorticoid medication, except inhaled and/or at low stable doses Pregnancy Use of isophane insulin (NPH) or intermediate-acting insulin Significant clinical nephropathy, neuropathy, retinopathy as per the clinical investigator's judgement Acute macrovascular event (ex: acute coronary syndrome or cardiac surgery) within 6 months of admission Severe diabetes ketoacidosis and/or hypoglycemia within one month of admission Other severe medical illness that the clinical investigator considers may interfere with participation in or completion of the study An inability or unwillingness to comply with study procedures as per the clinical investigator's judgement
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Adnan Jafar, PhD Student
Phone
+1 4383456595
Email
adnan.jafar@mail.mcgill.ca
First Name & Middle Initial & Last Name or Official Title & Degree
Alessandra Kobayati, PhD Student
Phone
+1 5145010326
Email
alessandra.kobayati@mail.mcgill.ca
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Ahmad Haidar, PhD
Organizational Affiliation
McGill University Health Centre/Research Institute of the McGill University Health Centre
Official's Role
Study Chair
First Name & Middle Initial & Last Name & Degree
Michael Tsoukas, MD
Organizational Affiliation
McGill University Health Centre/Research Institute of the McGill University Health Centre
Official's Role
Principal Investigator
Facility Information:
Facility Name
Clinique Médicale Hygea
City
Montreal
State/Province
Quebec
ZIP/Postal Code
H4A 3T2
Country
Canada
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Michael Tsoukas
Phone
(514) 967 9503
Email
michael.tsoukas@mcgill.ca
First Name & Middle Initial & Last Name & Degree
Michael Tsoukas, MD
First Name & Middle Initial & Last Name & Degree
Ahmad Haidar, PhD
First Name & Middle Initial & Last Name & Degree
Jean François YALE, MD
First Name & Middle Initial & Last Name & Degree
Julia Von Oettingen, MD
First Name & Middle Initial & Last Name & Degree
Laurent Legault, ND
First Name & Middle Initial & Last Name & Degree
Natasha Garfield, MD

12. IPD Sharing Statement

Plan to Share IPD
Yes
IPD Sharing Plan Description
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.
IPD Sharing Time Frame
Raw data and consent form: Anytime upon reasonable request. Protocol: After publication
IPD Sharing Access Criteria
The requested data could be accessed from the corresponding author, ahmad.haidar@mcgill.ca, upon reasonable request for academic purposes. Protocol is available with publication

Learn more about this trial

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

We'll reach out to this number within 24 hrs