Clinical trial NCT02688218: Exercise Detection Study
Official title: Testing and Tuning a Multiparameter Exercise Detection Algorithm
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Type 1 Diabetes
Keywords: exercise
artificial pancreas
hypoglycemia
type 1 diabetes
Lead sponsor: Oregon Health and Science University
Sponsor class: OTHER
First posted: 2016-02-23
Enrollment: 30
Sex: ALL
Minimum age (years): 21
Maximum age (years): 45
Standard ages: ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: CROSSOVER
Primary purpose: DIAGNOSTIC

Brief summary: The risk of hypoglycemia in individuals with type 1 diabetes increases considerably during exercise. As a result, many patients with type 1 diabetes experience fear of and reluctance to pursue physical activity, in order to avoid the discomforting symptoms associated with hypoglycemia. The bi-hormonal artificial pancreas, a device used for automatic delivery of insulin and glucagon subcutaneously to subjects with type 1 diabetes, is paving the way to revolutionize the management of this disease. The investigator's group has recently completed a study of the bi-hormonal artificial pancreas system during exercise, suggesting reduced hypoglycemia around the exercise period. In order to prepare for a future home study, the ability to detect, grade, and classify physical activity so as to appropriately adjust system parameters is vital in helping to prevent exercise induced hypoglycemia in the home setting.

This study is designed to collect 3-axis accelerometry data and heart rate data during a variety of different home activities, as well as during formal exercise in both healthy subjects and subjects with type 1 diabetes. Additionally, the investigators will observe the change in glucose levels before and after exercise in subjects with type 1 diabetes.

Detailed description: The artificial pancreas, a device used for automatic delivery of insulin and glucagon subcutaneously to subjects with type 1 diabetes, is paving the way to revolutionize the management of this disease. Already, the benefit of improved glycemic control compared to current open-loop pump therapy has been demonstrated in several trials. The investigator's group has shown that artificial pancreas algorithm dual hormone system effectively manages blood glucose in a clinic setting and the investigators have specifically shown great progress using glucagon to reduce hypoglycemic episodes outside of exercise. The investigators most recent inpatient study, as yet unpublished, shows that adjusting insulin and glucagon delivery during closed loop treatment, after announcing exercise, effectively reduces mean time below a glucose level of 70 mg/dl when compared to closed loop control without adjustments. The investigators utilized initial open-loop data from this study to help devise dosing changes for the artificial pancreas algorithm.

In order to prepare for a future home study, the ability to detect, grade, and classify physical activity so as to appropriately adjust system parameters is vital in helping to prevent exercise induced hypoglycemia in the home setting. Currently, our closed-loop system transmits heart rate and accelerometry outputs from a Zephyrlife BioPatch monitoring device to a Nexus 5 smart phone master controller via Bluetooth. The algorithm then converts the heart rate and accelerometry data into modified estimated energy expenditure - accounting for age, weight, height, sex, resting and sitting heart rates - to determine if exercise is present. However, further data collection is needed to hone the specificity and sensitivity of the detection algorithm to account for a wide variety of subject characteristics and activities.

This study is designed to collect 3-axis accelerometry data and heart rate data during a variety of different home activities, as well as during formal exercise, which included aerobic exercise (on a calibrated treadmill) and resistance exercise (straight-leg raises or equivalent) in healthy subjects as well as subjects with type 1 diabetes. Optionally VO2 data from a portable VO2 mask will be obtained. The data collected will be used to further enhance our algorithm that, in future closed-loop studies, will detect exercise and automatically trigger algorithmic adjustments to reduce exercise-related hypoglycemia during and after exercise in individuals with type 1 diabetes.

Eligibility criteria: TYPE 1 DIABETIC SUBJECT CRITERIA

Inclusion criteria:

1. Male or female subjects 21 to 45 years of age with a diagnosis of T1D for at least 6 months on an insulin pump.
2. Physically active on a regular basis, i.e. at least 3 days of scheduled physical activity per week and willing to perform approximately 60 minutes of exercise (as determined by the investigator after reviewing the subjects activity level).
3. Willingness to follow all study procedures.
4. Willingness to sign informed consent and HIPAA documents.

Exclusion criteria:

a. Pregnancy or Lactation: i. For women of childbearing potential, there is a requirement for a negative urine pregnancy test. b. Any cardiovascular disease, defined as a clinically significant EKG abnormality at the time of screening or any history of: stroke, heart failure, myocardial infarction, angina pectoris, or coronary arterial bypass graft or angioplasty. Diagnosis of 2nd or 3rd degree heart block or any non-physiological arrhythmia judged by the investigator to be exclusionary. c. Renal insufficiency (GFR \< 60 ml/min, using the MDRD equation as report by the OHSU laboratory). d. Hematocrit of less than or equal to 34%. e. History of severe hypoglycemia during the past 12 months prior to screening visit or hypoglycemia unawareness as judged by the investigator. f. Adrenal insufficiency. g. Any active infection. h. Known or suspected abuse of alcohol, narcotics, or illicit drugs (except marijuana use).

i. Seizure disorder. j. Active foot ulceration. k. Severe peripheral arterial disease characterized by ischemic rest pain or severe claudication. l. Major surgical operation within 30 days prior to screening. m. Use of an investigational drug within 30 days prior to screening. n. Chronic usage of any immunosuppressive medication (such as cyclosporine, azathioprine, sirolimus, or tacrolimus). o. Bleeding disorder, treatment with warfarin, or platelet count below 50,000. p. Current administration of oral or parenteral corticosteroids. q. Any life threatening disease, including malignant neoplasms and medical history of malignant neoplasms within the past 5 years prior to screening (except basal and squamous cell skin cancer). r. Any concurrent illness, other than diabetes, that is not controlled by a stable therapeutic regimen. s. Beta blockers or non-dihydropyridine calcium channel blockers. t. A positive response to any of the questions from the Physical Activity Readiness Questionnaire, see Appendix A. u. Any chest discomfort with physical activity, including pain or pressure, or other types of discomfort. v. Any clinically significant disease or disorder which in the opinion of the Investigator may jeopardize the subject's safety or compliance with the protocol.

HEALTHY SUBJECT CRITERIA

Inclusion Criteria:

1. Male or female subjects 21 to 45 years of age.
2. Physically active on a regular basis, i.e. at least 3 days of scheduled physical activity per week and willing to perform approximately 60 minutes of exercise (as determined by the investigator after reviewing the subjects activity level).
3. Willingness to follow all study procedures.
4. Willingness to sign informed consent and HIPAA documents.

Exclusion criteria:

1. Pregnancy or Lactation: For women of childbearing potential, there is a requirement for a negative urine pregnancy test.
2. Any history or evidence of renal insufficiency, adrenal insufficiency, liver disease or anemia.
3. A history of cerebrovascular disease or coronary artery disease (or angina) regardless of the time since occurrence.
4. Congestive heart failure, New York Heart Association (NYHA) any class.
5. Diagnosis of 1st, 2nd or 3rd degree heart block or any arrhythmia judged by the investigator to be exclusionary.
6. Any condition which, in the opinion of the investigator, makes it difficult to engage in vigorous physical activity.
7. Any active infection.
8. Severe peripheral arterial disease characterized by ischemic rest pain or severe claudication.
9. Active alcohol abuse, substance abuse, or severe mental illness (as judged by the principal investigator).
10. Active malignancy, except basal cell or squamous cell skin cancers.
11. Major surgical operation within 30 days prior to screening.
12. Seizure disorder.
13. Bleeding disorder, or treatment with warfarin.
14. Use of any chronic medications.
15. Use of an investigational drug within 30 days prior to screening.
16. Any reason the principal investigator deems exclusionary.

Primary outcomes:
measure: Mean Change in Sensor Glucose in Subjects With Type 1 Diabetes
timeFrame: 4 hours
Secondary outcomes:
Other outcomes:
Locations:
city: Portland
country: United States
facility: Oregon Health and Science University
state: Oregon
Study officials:
affiliation: Oregon Health and Science University
name: Joseph El Youssef, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Castle JR, Engle JM, El Youssef J, Massoud RG, Yuen KC, Kagan R, Ward WK. Novel use of glucagon in a closed-loop system for prevention of hypoglycemia in type 1 diabetes. Diabetes Care. 2010 Jun;33(6):1282-7. doi: 10.2337/dc09-2254. Epub 2010 Mar 23.
citation: Jacobs PG, El Youssef J, Castle J, Bakhtiani P, Branigan D, Breen M, Bauer D, Preiser N, Leonard G, Stonex T, Ward WK. Automated control of an adaptive bihormonal, dual-sensor artificial pancreas and evaluation during inpatient studies. IEEE Trans Biomed Eng. 2014 Oct;61(10):2569-81. doi: 10.1109/TBME.2014.2323248. Epub 2014 May 13.
citation: Jacobs PG, El Youssef J, Castle JR, Engle JM, Branigan DL, Johnson P, Massoud R, Kamath A, Ward WK. Development of a fully automated closed loop artificial pancreas control system with dual pump delivery of insulin and glucagon. Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:397-400. doi: 10.1109/IEMBS.2011.6090127.
citation: Jacobs PG, Resalat N, El Youssef J, Reddy R, Branigan D, Preiser N, Condon J, Castle J. Incorporating an Exercise Detection, Grading, and Hormone Dosing Algorithm Into the Artificial Pancreas Using Accelerometry and Heart Rate. J Diabetes Sci Technol. 2015 Oct 5;9(6):1175-84. doi: 10.1177/1932296815609371.