A Novel mHealth Application Guided by an Optimization Algorithm for T1D Sensor-Augmented Insulin Injection Users

NCT ID: NCT04123054

Last Updated: 2024-05-16

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 84 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2020-03-05
• Study Completion Date: 2024-01-12

Brief Summary

The Artificial Pancreas lab at McGill University has developed an optimization algorithm for adults with Type 1 Diabetes (T1D) on Multiple Daily Injection (MDI) therapy with the adjunctive use of glucose sensor technology, collectively known as sensor-augmented MDI therapy. The algorithm is designed to estimate optimal basal-bolus parameters based on the patient's glucose, insulin and meal data over several days. The investigators hope that this algorithm will be better able to improve long-term glycemic targets by reducing HbA1c levels compared to sensor-augmented MDI therapy alone.

Detailed Description

The changes in eligibility criteria indicated below are from a previously approved amendment but were inadvertently omitted in the previous PRS update made in November of 2020. Therefore, this note serves to clarify the order of updates.

Inclusion: HbA1c ≥ 7.5% in the last 2 months (modification)

Exclusion:

• More than 1 slow-acting injection and unwilling to switch to once a day for the study (addition)
• Severe hypoglycemic episode within one month of admission (addition)

In the subsequent amendment, we modified the timeframe for the HbA1c inclusion criterion to obtain a more accurate representation of their current glucose control at the time of enrollment.

Conditions

Diabetes Mellitus; Diabetes Mellitus, Type 1

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Study Groups

Sensor-Augmented MDI + Mobile App (control)

Participants will continue their usual multiple daily injections (MDI) therapy along with the use of Freestyle Libre glucose sensors (Abbott Diabetes Care) and a mobile application that facilitates insulin dose calculations while collecting insulin and meal data.

Group Type: ACTIVE_COMPARATOR

Mobile App

Intervention Type: DEVICE

Participants will use the mobile app to log their daily basal dose and calculate their meal doses by entering their sensor glucose value (and amount of meal carbohydrates if applicable) using the built-in bolus calculator.

Sensor-Augmented MDI + Mobile App + Basal-Bolus Optimization Algorithm

Participants will undergo multiple daily injections (MDI) therapy along with the use of Freestyle Libre glucose sensors (Abbott Diabetes Care) and a mobile application that facilitates insulin dose calculations while collecting insulin and meal data. Every week, participants' insulin doses will be updated by the optimization algorithm's recommendations.

Group Type: EXPERIMENTAL

Mobile App + Basal-Bolus Optimization Algorithm

Intervention Type: DEVICE

Participants will use the mobile app to log their daily basal dose and calculate their meal doses by entering their sensor glucose value (and amount of meal carbohydrates if applicable) using the built-in bolus calculator. In addition, participants will receive weekly app notifications with personalized recommendations for insulin parameter adjustments made by the optimization algorithm.

Interventions

Mobile App

Participants will use the mobile app to log their daily basal dose and calculate their meal doses by entering their sensor glucose value (and amount of meal carbohydrates if applicable) using the built-in bolus calculator.

Intervention Type: DEVICE

Mobile App + Basal-Bolus Optimization Algorithm

Participants will use the mobile app to log their daily basal dose and calculate their meal doses by entering their sensor glucose value (and amount of meal carbohydrates if applicable) using the built-in bolus calculator. In addition, participants will receive weekly app notifications with personalized recommendations for insulin parameter adjustments made by the optimization algorithm.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

1. Males and females ≥ 18 years of age

2. Clinical diagnosis of type 1 diabetes for at least 12 months. The diagnosis of type 1 diabetes is based on the investigator's judgment; C peptide level and antibody determinations are not needed.

3. Undergoing multiple daily injection therapy.

4. Baseline HbA1c value ≥ 7.5% (up to 7 days before or after screening).

Exclusion Criteria

1. Serious medical illness likely to interfere with study participation or with the ability to complete the trial by the judgment of the investigator.

2. Failure to comply with the study protocol or with the team's recommendations.

3. Injection of isophane insulin (NPH) or any intermediate-acting insulin

4. More than 1 slow-acting injection and unwilling to switch to once a day for the study

5. Current or ≤ 1-month use of other antihyperglycemic agents (Sodium-Glucose Cotransporter 2 inhibitor (SGLT2), Glucagon-Like Peptide-1 (GLP-1), Metformin, Acarbose, etc.…).

6. Pregnancy

7. Severe hypoglycemic episode within one month of admission.

8. Severe diabetic ketoacidosis episode within one month of admission

9. Clinically significant nephropathy, neuropathy or retinopathy as judged by the investigator

10. Recent (<6 months) acute macrovascular event e.g. acute coronary syndrome or cardiac surgery

11. Other serious medical illness likely to interfere with study participation or with the ability to complete the trial by the judgment of the investigator.

• 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

Michael Tsoukas, MD

Role: PRINCIPAL_INVESTIGATOR

RI-MUHC

Locations

CIUSSS West-Central Montreal, Jewish General Hospital

Montreal, Quebec, Canada

McGill University Health Centre

Montreal, Quebec, Canada

Countries

Canada

References

Kobayati A, El Fathi A, Garfield N, Legault L, Jafar A, Yale JF, Tsoukas MA, Haidar A. A Bayesian decision support system for automated insulin doses in adults with type 1 diabetes on multiple daily injections: a randomized controlled trial. Nat Commun. 2025 Sep 29;16(1):8593. doi: 10.1038/s41467-025-63671-0.

Reference Type: DERIVED

PMID: 41022835 (View on PubMed)

Other Identifiers

2020-5887

Identifier Type: -

Identifier Source: org_study_id