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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
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03859401
Enrollment
15
Registered
2019-03-01
Start date
2019-04-12
Completion date
2020-01-13
Last updated
2026-05-05

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hypoglycemia, Type 1 Diabetes Mellitus

Keywords

Artificial Pancreas, Continuous Glucose Monitor, Exercise, Exercise-Induced Hypoglycemia

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.

Interventions

DEVICEEnMPC (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.

DEVICErMPC (Naïve Model Predictive Control) AP Controller

This AP controller does not have the ability to anticipate exercise activity.

Sponsors

Marc Breton
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
TREATMENT
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
No

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.

Design outcomes

Primary

MeasureTime frameDescription
Number of Hypoglycemic Occurrences in Relation to Exercise Activity2 HoursNumber 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

MeasureTime frameDescription
Average CGM36 HoursAverage CGM value
Percent Time CGM Below 54 mg/dL36 HoursPercentage of time CGM was below 54 mg/dL
Percent Time CGM Below 70 mg/dL36 HoursPercentage of time CGM was below 70 mg/dL
Percent Time CGM Between 70 and 180 mg/dL36 HoursPercentage of time CGM was between 70 and 180 mg/dL
Percent Time CGM Between 70 and 140 mg/dL36 HoursPercentage of time CGM was between 70 and 140 mg/dL
Percent Time CGM Above 180 mg/dL36 HoursPercentage of time CGM was above 180 mg/dL
Percent Time CGM Above 250 mg/dL36 HoursPercentage of time CGM was above 250 mg/dL
CGM Coefficient of Variation36 HoursCoefficient of Variation of the CGM Values
CGM-based Low Blood Glucose Index36 HoursCGM-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.
CGM Standard Deviation36 HoursStandard Deviation of the CGM Values

Countries

United States

Contacts

PRINCIPAL_INVESTIGATORMarc Breton, PhD

University of Virginia

Baseline characteristics

Characteristic
Age, Continuous42.9 years
STANDARD_DEVIATION 10.9
HbA1c6.7 percentage of glycated hemoglobin
STANDARD_DEVIATION 0.3
Height164.1 cm
STANDARD_DEVIATION 11.3
Race (NIH/OMB)
American Indian or Alaska Native
0 Participants
Race (NIH/OMB)
Asian
0 Participants
Race (NIH/OMB)
Black or African American
0 Participants
Race (NIH/OMB)
More than one race
0 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
0 Participants
Race (NIH/OMB)
Unknown or Not Reported
0 Participants
Race (NIH/OMB)
White
7 Participants
Sex: Female, Male
Female
10 Participants
Sex: Female, Male
Male
1 Participants
Type 1 Diabetes Duration26.8 years
STANDARD_DEVIATION 13.6
Weight86.9 kg
STANDARD_DEVIATION 11.5

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
0 / 150 / 15
other
Total, other adverse events
1 / 150 / 15
serious
Total, serious adverse events
0 / 150 / 15

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: May 6, 2026