Exercise-Induced Hypoglycemia Prevention in Adults With Type 1 Diabetes Using an Artificial Pancreas
- Conditions
- HypoglycemiaType 1 Diabetes Mellitus
- Interventions
- Device: EnMPC (Ensemble Model Predictive Control) AP ControllerDevice: rMPC (Naïve Model Predictive Control) AP Controller
- Registration Number
- NCT03859401
- Lead Sponsor
- Marc Breton
- Brief 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.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 18
- Age ≥18 and ≤65 years
- Clinical diagnosis of Type 1 Diabetes for at least one year
- Currently using an insulin pump for at least 6 months
- Uses insulin parameters such as carbohydrate ratio and correction factors consistently on their insulin pump in order to dose insulin for meals or corrections
- Access to internet and willingness to upload data during the study
- Willingness to be physically active for at least 30 minutes per day at least 4 times per week
- Willingness to perform the required exercise regimen during Data Collection Period
- Willingness to not perform regular exercise outside of the study-regimented exercise window
- For females, not currently pregnant or breastfeeding. If a female is of child-bearing potential and sexually active, she must agree to use a form of contraception to prevent pregnancy while participating in the study.
- An understanding and willingness to follow the protocol and sign informed consent.
- History of diabetic ketoacidosis (DKA) in the 12 months prior to enrollment.
- Severe hypoglycemia resulting in seizure or loss of consciousness in the 12 months prior to enrollment.
- Pregnancy or intent to become pregnant during the trial.
- Currently being treated for a seizure disorder
- Coronary artery disease or heart failure, unless written clearance is received from a cardiologist or primary care provider and documentation of a negative stress test within the year
- History of cardiac arrhythmia (except for benign premature atrial contractions and benign premature ventricular contractions which are permitted)
- Clinically significant electrocardiogram (ECG) at time of Screening, as interpreted by the study medical physician.
- Use of non-insulin glucose-lowering agent (including GLP-1 agonists, pramlintide, DPP-4 inhibitors, SGLT-2 inhibitors, biguanides, sulfonylureas and naturaceuticals) with the exception of participants who have been on a stable dose of Metformin for at least 3 months.
- A known medical condition that in the judgment of the investigator might interfere with the completion of the protocol such as the following examples:
- Inpatient psychiatric treatment in the past 6 months
- Presence of a known adrenal disorder
- Abnormal liver function test results (Transaminase >2 times the upper limit of normal); testing required for subjects taking medications known to affect liver function or with diseases known to affect liver function
- Uncontrolled thyroid disease
- Use of an automated insulin delivery mechanism that is not FDA approved during the data collection phase
- Use of an automated insulin delivery mechanism that is not downloadable by the subject or study team
- Inability to be physically active for at least 30 minutes per day for at least 4 times per week
- Current enrollment in another clinical trial, unless approved by the investigators of both studies or if clinical trial is a non-interventional registry trial.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- CROSSOVER
- Arm && Interventions
Group Intervention Description Control - Experimental Admissions EnMPC (Ensemble Model Predictive Control) AP Controller Subjects will be randomized following the Data Collection Phase in a 1:1 ratio. Subjects in the Control-Experimental Arm will undergo the Control Admission first, utilizing an artificial pancreas (AP) controller that does not anticipate exercise (rMPC - naïve model predictive control), followed by the Experimental Admission, which will utilize an AP controller that has the ability to anticipate exercise (EnMPC - ensemble model predictive control). During the 36-hour admissions, subjects will begin using the study AP system (control or experimental) on Day 1 around midday with a scheduled exercise activity in the evening. Day 2 will consist of minimal activity and subjects will be discharged in the evening on Day 2. Experimental - Control Admissions EnMPC (Ensemble Model Predictive Control) AP Controller Subjects will be randomized following the Data Collection Phase in a 1:1 ratio. Subjects in the Experimental-Control Arm will undergo the Experimental Admission first, utilizing an artificial pancreas (AP) controller that has the ability to anticipate exercise (EnMPC), followed by the Control Admission, which will utilize an AP controller that does not have the ability to anticipate exercise (rMPC). During the 36-hour admissions, subjects will begin using the study AP system (control or experimental) on Day 1 around midday with a scheduled exercise activity in the evening. Day 2 will consist of minimal activity and subjects will be discharged in the evening on Day 2. Control - Experimental Admissions rMPC (Naïve Model Predictive Control) AP Controller Subjects will be randomized following the Data Collection Phase in a 1:1 ratio. Subjects in the Control-Experimental Arm will undergo the Control Admission first, utilizing an artificial pancreas (AP) controller that does not anticipate exercise (rMPC - naïve model predictive control), followed by the Experimental Admission, which will utilize an AP controller that has the ability to anticipate exercise (EnMPC - ensemble model predictive control). During the 36-hour admissions, subjects will begin using the study AP system (control or experimental) on Day 1 around midday with a scheduled exercise activity in the evening. Day 2 will consist of minimal activity and subjects will be discharged in the evening on Day 2. Experimental - Control Admissions rMPC (Naïve Model Predictive Control) AP Controller Subjects will be randomized following the Data Collection Phase in a 1:1 ratio. Subjects in the Experimental-Control Arm will undergo the Experimental Admission first, utilizing an artificial pancreas (AP) controller that has the ability to anticipate exercise (EnMPC), followed by the Control Admission, which will utilize an AP controller that does not have the ability to anticipate exercise (rMPC). During the 36-hour admissions, subjects will begin using the study AP system (control or experimental) on Day 1 around midday with a scheduled exercise activity in the evening. Day 2 will consist of minimal activity and subjects will be discharged in the evening on Day 2.
- Primary Outcome Measures
Name Time Method Number of hypoglycemic occurrences in relation to exercise activity 2 Hours Number of hypoglycemic occurrences immediately before, during, and immediately after exercise (\~5-7pm) as defined by more than one consecutive CGM values below 70 mg/dL or hypoglycemic treatment per glycemic guidelines.
- Secondary Outcome Measures
Name Time Method Percent CGM below 50 mg/dL 36 Hours Percent CGM below 50 mg/dL
Percent CGM below 54 mg/dL 36 Hours Percent CGM below 54 mg/dL
Percent CGM below 60 mg/dL 36 Hours Percent CGM below 60 mg/dL
Percent CGM below 70 mg/dL 36 Hours Percent CGM below 70 mg/dL
Average CGM 36 Hours Average CGM
CGM-based High Blood Glucose Index 36 Hours CGM-based High Blood Glucose Index
Percent CGM above 180 mg/dL 36 Hours Percent CGM above 180 mg/dL
Percent CGM above 250 mg/dL 36 Hours Percent CGM above 250 mg/dL
Percent CGM between 70 and 180 mg/dL 36 Hours Percent CGM between 70 and 180 mg/dL
Percent CGM above 300 mg/dL 36 Hours Percent CGM above 300 mg/dL
CGM Coefficient of Variation 36 Hours Coefficient of Variation of the CGM Values
CGM-based Low Blood Glucose Index 36 Hours CGM-based Low Blood Glucose Index
Trial Locations
- Locations (1)
University of Virginia
🇺🇸Charlottesville, Virginia, United States