Efficacy of Closed-Loop Strategy With and Without a Learning Component in Children and Adolescents With Type 1 Diabetes at a Diabetes Camp
Condition: Diabetes; Type 1 Diabetes Mellitus
MeSH terms: Diabetes Mellitus; Diabetes Mellitus, Type 1
Study type: Interventional

Summary: 
      Our lab has developed an artificial pancreas system called the McGill Artificial Pancreas
      (MAP) for automating insulin delivery. Using patient's basal-bolus parameters (basal rates
      and ICRs), the artificial pancreas involves a control algorithm that modulates insulin
      infusion based on the sensor readings and meal information. However, because basal-bolus
      parameters are difficult to optimize, proper glycemic control is not always achieved.
      Therefore, we have developed a learning algorithm that estimates optimal basal-bolus
      parameters using data over several days. The algorithm examines daily glucose, insulin, and
      meal data to make changes in patients' basal rates and ICRs.

      The objective of this project is to test our artificial pancreas system with and without the
      learning algorithm using a randomized crossover design in between 31 and 67 children and
      adolescents at camp Carowanis. We hypothesize that adding a learning algorithm to the
      artificial pancreas will improve the performance of our artificial pancreas system by
      increasing the time spent in target glucose range (4mmol/L - 10mmol/L) compared with the
      artificial pancreas system alone.
    

Detailed description: 
      This is an open-label, randomized, two-way, cross-over study to compare the glucose control
      between closed-loop strategy with and without a learning module. Children and adolescent type
      1 diabetes patients at Camp Carowanis will be enrolled in the study, where they will undergo
      two randomly ordered interventions:

        1. Closed-loop therapy: participants will undergo a closed-loop therapy where insulin
           delivery is determined by the MAP system. The study parameters (basal rates and ICRs)
           will be determined by the camp's physicians on day 1 of camp. The research staff will
           update the pump's settings to reflect the physician's recommendations at the beginning
           of the closed-loop therapy, and each time the physicians update the study parameters.
           Camp physicians will review participants' sensor and insulin data daily, and if
           necessary, adjust participant basal rates and ICRs. The research staff members will
           likewise adjust the pump's basal rates and ICR settings as per physician's
           recommendations. The closed-loop therapy will last 2 days (48 hours).

        2. Closed-loop therapy with learning module: participants will undergo a closed-loop
           therapy where insulin delivery is determined by the MAP system. The study parameters
           (basal rates and ICRs) will be computed by the learning algorithm and updated daily. The
           learning algorithm runs on a computer of the research staff members and requires patient
           data to calculate the optimal basal rates and ICR. Each morning, the research staff
           members will upload patient data onto the computer, run the leaning algorithm, and
           update the pump parameters to reflect the recommendations computed by the learning
           algorithm. Camp physicians will be to review the algorithm's recommendations before they
           are entered into the patient's pump. The closed-loop therapy with the learning module
           will last 8 days (192 hours).
    

Intervention name(s): Artificial Pancreas
Intervention type(s): Device
Intervention description(s): The system is composed of 3 main components:
Insulin infusion pump to infuse insulin. The pump model used in the study is t:slim, Tandem Diabetes Care.
Continuous glucose monitor (CGM) to continuously measure glucose levels in the interstitial fluid. Glucose levels will be measured by Dexcom G5® CGM.
MAP application (iMAP) that computes insulin infusion based on the glucose values. The application also alarms the user when glucose sensor values are approaching the hypoglycemic or hyperglycemic range. The iMAP runs on an android smartphone.
Every 10 minutes, iMAP retrieves the glucose values from the Dexcom G5 CGM via Bluetooth. The application computes an optimal insulin infusion rate based on i) the current glucose reading, ii) the glucose trend (i.e. how quickly the glucose level is rising or falling) and iii) the open-loop basal rates (study parameters). The insulin recommendations are then sent wirelessly via Bluetooth to the insulin pump.
Intervention MeSH terms: Pancrelipase
Allocation: Randomized
Intervention model: Crossover Assignment
Intervention model description: This is an open-label, randomized, two-way, cross-over study.
Masking: Single (Participant)
Primary purpose: Treatment
Keywords: diabetes; type 1 diabetes; diabetes mellitus; pediatrics; diabetes camp