NCT03859401

Exercise-Induced Hypoglycemia Prevention in Adults With Type 1 Diabetes Using an Artificial Pancreas

Hypoglycemia Prevention During and After Moderate Exercise in Adults With Type 1 Diabetes Using an Artificial Pancreas With Exercise Behavior Recognition

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 18 (actual)
• Sponsor: Marc Breton · Academic / Other
• Sex: All
• Age: 18 Years – 65 Years
• Healthy volunteers: Not accepted

Summary

This is a randomized crossover trial with 1:1 randomization to the admission sequence of using the Control AP system (rMPC - Naïve Model Predictive Control) vs. Experimental AP system (EnMPC - Ensemble Model Predictive Control) over approximately 4 months. Eligible participants will proceed to the Data Collection Phase for approximately 28 days, during which they will participate in regimented exercise activities. If the participant collected adequate data during the Data Collection Phase, they will be randomized and undergo the study admissions in the assigned sequence. Each admission is approximately 36 hours in length and will consist of one afternoon of exercise and one without.

Detailed description

Exercise remains a challenge to AP systems; more specifically, by the time exercise is detected it is often too late to avoid hypoglycemia without the ingestion of rapid carbohydrates or the use of rescue injections, such as glucagon. To this avail, the investigators propose to add a novel Model Predictive Control module to the proven USS system. This module is designed to compute insulin doses every 5 minutes that are designed to "optimally" maintain glycaemia around a target of 120mg/dL. The optimality is defined mathematically as minimizing deviations from basal rate injections and the distance between current and future (up to 2h) glycaemia from a physiologically feasible trajectory back down (or up) to a pre-specified target. Furthermore, the novel control system, labelled Multi Stage MPC or Ensemble MPC, accounts for a preset number of exercise scenarios during the prediction horizon, these scenarios being derived from the user historical record; this setup allows the control system to anticipate expected exercise bouts up to 2h in advance while maintaining the condition for optimal glycemic control. By adding such module to a well validated system, the investigators expect an improvement in protection against hypoglycemia during and immediately after physical activity without increase in hyperglycemia. To demonstrate the feasibility of this approach, the novel anticipatory system will be compared to a naïve AP system during highly supervised hotel admissions with afternoon exercise. Participants will be asked to exercise regularly in the late afternoon during a month of data collection to generate the patterns to be anticipated.

Conditions

• Type 1 Diabetes Mellitus
• Hypoglycemia

Interventions

Type	Name	Description
DEVICE	EnMPC (Ensemble Model Predictive Control) AP Controller	This AP controller has the ability to anticipate exercise activity by use of trends seen during the Data Collection Period.
DEVICE	rMPC (Naïve Model Predictive Control) AP Controller	This AP controller does not have the ability to anticipate exercise activity.

Timeline

• Start date: 2019-04-12
• Primary completion: 2020-01-13
• Completion: 2020-01-13
• First posted: 2019-03-01
• Last updated: 2020-01-18

Locations

1 site across 1 country: United States

Regulatory

• FDA-regulated device study