Context Aware Data Gathering Study

NCT04154904 | Completed Results

• 2 other identifiers: 202481R01DK122583-01
• Study Type: interventional
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

Automated Insulin Delivery (AID) systems have now become an important standard-of-care for people with T1D and have demonstrated a reduction, but not elimination, of hypoglycemia during long-term studies. One limitation of current AID systems is that they have no knowledge about the context or environment that a person is currently experiencing. Contextual patterns can potentially improve the performance of an AID by recognizing environments or patterns of living that are related to changes in glucose. The team at OHSU is developing a context-aware glucose prediction algorithm that will capture context data from the patient both indoors and outdoors. This context data will be provided to the algorithm to allow for detecting contextual patterns that might relate to high or low glucose. The goal of this study will be the creation of a data set that will include contextual patterns along with glucose, insulin and physiological data.

Conditions

Type 1 Diabetes

Keywords

automated insulin delivery systems; Context patterns

Outcome Measures

Primary Outcomes (2)

• Comparison of the Mean Absolute Relative Difference When Including Patterns in Hypoglycemia Prediction.

  We used our recently published long short term memory neural network (LSTM) to predict sensor glucose 30-minutes in advance across the entire 4-week study duration when glucose was \< 70 mg/dL. We then used the context-aware pattern recognition algorithm to predict when hypoglycemia would occur 30-minutes in the future, and if hypoglycemia was predicted, we included a bias correction that is specific to the hypogylcemia region of glucose measurements. The outcome measure shows the reduction of MARD when the LSTM is corrected using the pattern-based bias correction algorithm. MARD is calculated by subtracting the new sensor glucose - reference value dividing by the reference value. A negative value means that the MARD was reduced. The LSTM is being compared with Dexcom G6 CGM values to determine the MARD. Physiologically relevant thresholds are less than 55 mg/dl, less than 70 mg/dl, above 180 mg/dl and above 250 mg/dl. The Dexcom G6 target range is 70-180 mg/dl.

  28 days

• Comparison of the Mean Relative Difference When Including Patterns in Hypoglycemia Prediction.

  We used our recently published long short term memory neural network (LSTM) to predict glucose 30-minutes in advance across the entire 4-week study duration when glucose was \< 70 mg/dL. We then used the context-aware pattern recognition algorithm to predict when hypoglycemia would occur 30-minutes in the future, and if hypoglycemia was predicted, we included a bias correction that is specific to the hypogylcemia region of glucose measurements. The outcome measure shows the reduction of mean relative difference (MRD) when the LSTM is corrected using the pattern-based bias correction algorithm. MARD is calculated by subtracting the new sensor glucose - reference value dividing by the reference value. A negative value means that the MARD was reduced. The LSTM is being compared with Dexcom G6 CGM values to determine the MARD. Physiologically relevant thresholds are less than 55 mg/dl, less than 70 mg/dl, above 180 mg/dl and above 250 mg/dl. The Dexcom G6 target range is 70-180 mg/dl.

  28 days

Study Arms (3)

Aerobic exercise

EXPERIMENTAL

Other: Exercise

Resistance exercise

EXPERIMENTAL

Other: Exercise

High intensity interval exercise

EXPERIMENTAL

Other: Exercise

Interventions

Exercise OTHER

Subjects will be randomized to complete either aerobic, high intensity interval training, or resistance exercise videos twice weekly at home.

Aerobic exercise; High intensity interval exercise; Resistance exercise

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Diagnosis of type 1 diabetes mellitus for at least 1 year.
• Male or female subjects 18 to 65 years of age.
• Physically willing and able to perform 30 min of exercise (as determined by the investigator after reviewing the subject's activity level).
• Current use of an insulin pump for at least 3 months.
• A1C \<10.5% at the time of screening.
• Willingness to follow all study procedures, including attending all clinic visits.
• Willingness to sign informed consent and HIPAA documents.

You may not qualify if:

• Female of childbearing potential who is pregnant or intending to become pregnant or breast-feeding, or is not using adequate contraceptive methods. Acceptable contraception includes birth control pill / patch / vaginal ring, Depo-Provera, Norplant, an IUD, the double barrier method (the woman uses a diaphragm and spermicide and the man uses a condom), or abstinence.
• Renal insufficiency (GFR \< 60 ml/min, using the MDRD equation as reported by the OHSU laboratory).
• Liver failure, cirrhosis, or any other liver disease that compromises liver function as determined by the investigator.
• Hematocrit of less than 36% for men, less than 32% for women.
• History of severe hypoglycemia during the past 12 months prior to screening visit or hypoglycemia unawareness as judged by the investigator. Subjects will complete a hypoglycemia awareness questionnaire. Subjects will be excluded for four or more R responses.
• Adrenal insufficiency.
• Any active infection.
• Known or suspected abuse of alcohol, narcotics, or illicit drugs.
• Seizure disorder.
• Active foot ulceration.
• Peripheral arterial disease.
• Major surgical operation within 30 days prior to screening.
• Use of an investigational drug within 30 days prior to screening.
• Chronic usage of any immunosuppressive medication (such as cyclosporine, azathioprine, sirolimus, or tacrolimus).
• Bleeding disorder or platelet count below 50,000.

Sponsors & Collaborators

• Oregon Health and Science University: lead
• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): collaborator

Study Sites (1)

Oregon Health and Science University

Portland, Oregon, 97239, United States

Location

MeSH Terms

Conditions

Diabetes Mellitus, Type 1

Interventions

Exercise

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Autoimmune Diseases; Immune System Diseases

Intervention Hierarchy (Ancestors)

Motor Activity; Movement; Musculoskeletal Physiological Phenomena; Musculoskeletal and Neural Physiological Phenomena

Limitations and Caveats

Technical problems with pump downloads after the study lead to unreliable or uninterpretable data.

Results Point of Contact

• Title: Jessica Castle
• Organization: Oregon Health and Science University

castleje@ohsu.edu

1503-494-7072

Study Officials

• Jessica Castle, MD

  Oregon Health and Science University

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: Yes

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: BASIC SCIENCE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: November 5, 2019
• First Posted: November 7, 2019
• Study Start: August 11, 2020
• Primary Completion: December 23, 2021
• Study Completion: January 3, 2022
• Last Updated: August 1, 2023
• Results First Posted: July 12, 2023

Record last verified: 2023-07

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)