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

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.

Study Overview

• Status: Completed
• Conditions: Hypoglycemia; Type 1 Diabetes Mellitus
• Intervention / Treatment: Device: EnMPC (Ensemble Model Predictive Control) AP Controller; Device: rMPC (Naïve Model Predictive Control) AP Controller

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.

• Study Type: Interventional
• Enrollment (Actual): 15
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Virginia
    • Charlottesville, Virginia, United States, 22908
      • University of Virginia

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 65 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• 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.

Exclusion Criteria:

• 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 Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Control - Experimental Admissions; 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.	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.
Experimental: Experimental - Control Admissions; 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.	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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of Hypoglycemic Occurrences in Relation to Exercise Activity	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.	2 Hours

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
CGM Coefficient of Variation	Coefficient of Variation of the CGM Values	36 Hours
Average CGM	Average CGM value	36 Hours
Percent Time CGM Below 54 mg/dL	Percentage of time CGM was below 54 mg/dL	36 Hours
Percent Time CGM Below 70 mg/dL	Percentage of time CGM was below 70 mg/dL	36 Hours
Percent Time CGM Between 70 and 180 mg/dL	Percentage of time CGM was between 70 and 180 mg/dL	36 Hours
Percent Time CGM Between 70 and 140 mg/dL	Percentage of time CGM was between 70 and 140 mg/dL	36 Hours
Percent Time CGM Above 180 mg/dL	Percentage of time CGM was above 180 mg/dL	36 Hours
Percent Time CGM Above 250 mg/dL	Percentage of time CGM was above 250 mg/dL	36 Hours
CGM-based Low Blood Glucose Index	CGM-based Low Blood Glucose Index (LBGI) which is a metric used to quantify the risk of hypoglycemia (low blood sugar) based on self-monitored blood glucose (SMBG) data. LBGI is based on a nonlinear transformation of blood glucose values that corrects for the asymmetry of the glucose scale. This transformation maps glucose values into a risk space (minimum risk = 0), where higher values correspond to higher risk. Values <1 suggest low risk of hypoglycemia.	36 Hours
CGM Standard Deviation	Standard Deviation of the CGM Values	36 Hours

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of Hypoglycemic Episodes	Number of Hypoglycemic Episodes as defined by contiguous CGM below 70 mg/dL	36 Hours
Total Amount of Insulin Used	Total Amount of Insulin Used, units	36 Hours

Collaborators and Investigators

• Sponsor: Marc Breton
• Investigators: Principal Investigator: Marc Breton, PhD, University of Virginia

Publications and helpful links

General Publications

• Garcia-Tirado J, Brown SA, Laichuthai N, Colmegna P, Koravi CLK, Ozaslan B, Corbett JP, Barnett CL, Pajewski M, Oliveri MC, Myers H, Breton MD. Anticipation of Historical Exercise Patterns by a Novel Artificial Pancreas System Reduces Hypoglycemia During and After Moderate-Intensity Physical Activity in People with Type 1 Diabetes. Diabetes Technol Ther. 2021 Apr;23(4):277-285. doi: 10.1089/dia.2020.0516. Epub 2020 Dec 1.

Helpful Links

• Related Info

Study record dates

Study Major Dates

• Study Start (Actual): April 12, 2019
• Primary Completion (Actual): January 13, 2020
• Study Completion (Actual): January 13, 2020

Study Registration Dates

• First Submitted: February 27, 2019
• First Submitted That Met QC Criteria: February 27, 2019
• First Posted (Actual): March 1, 2019

Study Record Updates

• Last Update Posted (Actual): May 5, 2026
• Last Update Submitted That Met QC Criteria: April 14, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: Exercise; Continuous Glucose Monitor; Artificial Pancreas; Exercise-Induced Hypoglycemia
• Additional Relevant MeSH Terms: Endocrine System Diseases; Metabolic Diseases; Autoimmune Diseases; Immune System Diseases; Glucose Metabolism Disorders; Diabetes Mellitus; Behavior; Nutritional and Metabolic Diseases; Hypoglycemia; Diabetes Mellitus, Type 1; Motor Activity
• Other Study ID Numbers: 180039

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Will follow the NIH Data Sharing Policy and Implementation Guidance on sharing research resources for research purposes to qualified individuals in the scientific community.
• IPD Sharing Time Frame: Data will be made available after the publication of the manuscript.
• IPD Sharing Access Criteria: The Data Sharing Agreements will be formulated by the study team
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; ICF

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes