Type 1 DiabetesNCT05041621
A Learning Algorithm for MDI Individuals With Type 1 Diabetes to Adjust Recommendations for High Fat Meals and Exercise Management
A study testing Sensor augmented MDI therapy plus mobile application in people with Type 1 Diabetes, run by McGill University at 1 site in Canada.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Type 1 Diabetes
- What is being tested?
- Sensor augmented MDI therapy plus mobile application
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 15 participants
- Where
- 1 siteCanada
- Study dates
- 7 Jul 2021to 21 Feb 2023
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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
Show all 9Show fewer
- 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
Trial locations and contacts
1 site in 1 country.
About this study
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
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.
Read the 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
- Being tested
- Sensor augmented MDI therapy plus mobile application
- Medical subject headings
- Diabetes Mellitus, Type 1
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Sensor augmented MDI therapy plus mobile applicationDevice
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.
| Study group | Role | What they receive |
|---|---|---|
| Sensor augmented MDI therapy plus mobile application with reinforcement learning algorithm | Experimental | 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. Receives: Device: Sensor augmented MDI therapy plus mobile application |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: 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
Measured: First and last month of intervention, approximately 4 months
Secondary outcomes (26)
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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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
Measured: 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)
Measured: 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)
Measured: 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)
Measured: Post-intervention, approximately 4 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Sep 2021
- Study start7 Jul 2021
- Primary completion21 Feb 2023
- Study completion21 Feb 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Type 1 DiabetesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 15 participants (actual)
Sponsor and investigators
- Lead sponsor
- McGill University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Ahmad Haidar, PhD, Study chair, McGill University Health Centre/Research Institute of the McGill University Health CentreMichael Tsoukas, MD, Principal investigator, McGill University Health Centre/Research Institute of the McGill University Health Centre
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05041621
- Sponsor's protocol ID
- 2021-47375
- Status last verified
- Nov 2023
- First submitted
- 26 Jul 2021
- Last updated
- 9 Nov 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- 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.
Study at a glance
From the registry record, last updated by the sponsor on 9 Nov 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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
- ClinicalTrials.gov ID
- NCT05041621
- Acronym / sponsor ID
- 2021-47375
- Conditions
- Type 1 Diabetes
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 15 participants (actual)
- Lead sponsor
- McGill UniversityUniversity, hospital or other
- Study start
- 7 Jul 2021 (actual)
- Primary completion
- 21 Feb 2023 (actual)
- Study completion
- 21 Feb 2023 (actual)
- First posted
- 13 Sep 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Sensor augmented MDI therapy plus mobile application with reinforcement learning algorithm | Experimental | Device: Sensor augmented MDI therapy plus mobile applicationParticipants 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- 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
Key exclusion criteria (9 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Sensor augmented MDI therapy plus mobile applicationParticipants 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. | Device | Sensor augmented MDI therapy plus mobile application with reinforcement learning algorithm |
Primary outcome
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
26 secondary outcomes
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
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Nov 2023.
- Individual participant dataSharing planned: 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Ahmad Haidar, PhD study chair
McGill University Health Centre/Research Institute of the McGill University Health Centre
Michael Tsoukas, MD principal investigator
McGill University Health Centre/Research Institute of the McGill University Health Centre
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Sensor augmented MDI therapy plus mobile application in people with Type 1 Diabetes, run by McGill University at 1 site in Canada.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 9 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 9 Nov 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Canada. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 9 Nov 2023.