Type 1 DiabetesNCT04154904
Context Aware Data Gathering Study
A study testing Exercise in people with Type 1 Diabetes, run by Oregon Health and Science University at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 65 years
- Conditions the study is for
- Type 1 Diabetes
- What is being tested?
- Exercise
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 30 participants
- Where
- 1 siteUnited States
- Study dates
- 11 Aug 2020to 3 Jan 2022
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 65 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- 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.
- 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.
- 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.
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- 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.
- Current administration of oral or parenteral corticosteroids.
- 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).
- Beta blockers or non-dihydropyridine calcium channel blockers.
- Current use of any medication intended to lower glucose other than insulin (ex. use of liraglutide).
- A positive response to any of the questions from the Physical Activity Readiness Questionnaire with one exception: subject will not be excluded if he/she takes a single blood pressure medication that doesn't impact heart rate and blood pressure is controlled on the medication (blood pressure is less than 140/90 mmHg).
- Any chest discomfort with physical activity, including pain or pressure, or other types of discomfort.
- Any clinically significant disease or disorder which in the opinion of the Investigator may jeopardize the subject's safety or compliance with the protocol.
Trial locations and contacts
1 site in 1 country.
United States1 site
Oregon Health and Science University
Portland, Oregon, 97239
About this study
Official title: Development of a Context-aware Glucose Prediction Algorithm in Patients With Type 1 Diabetes
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.
Read the detailed description
Subjects will be on study for 28 days. Sensor glucose, activity, exercise, insulin, indoor and outdoor contextual patterns and meal data will be collected during this time. Subjects will wear the Dexcom G6 CGM system and a physical activity monitor for the entire 28 days. Subjects will continue to use their own insulin pump. Subjects will be asked to also wear a MotioWear indoor/outdoor context-aware tracking tag and to install the MotioWear beacons within their home. Subjects will be randomized to complete either aerobic, high intensity interval training, or resistance exercise videos twice weekly at home during weeks 1 and 2 and once during weeks 3 and 4. Subjects will also ingest a self-selected meal prior to these prescribed exercise sessions. Subjects will eat a high carbohydrate dinner once each week on the same day at the same approximate time of day (but not on the exercise days).
Subjects will use the T1 DEXI mobile app created by OHSU to capture meal and exercise data along with photos of meals the day of exercise and the day after. While at home, subjects will check CBG before and after exercise, for symptoms of hypoglycemia, and for Dexcom G6 alarms for sensor <70 mg/dL and >250 mg/dL.
- Conditions
- Type 1 Diabetes
- Being tested
- Exercise
- Keywords
- automated insulin delivery systems, Context patterns
- Medical subject headings
- Diabetes Mellitus, Type 1
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
ExerciseOther
Subjects will be randomized to complete either aerobic, high intensity interval training, or resistance exercise videos twice weekly at home.
| Study group | Role | What they receive |
|---|---|---|
| Aerobic exercise | Experimental | Not described Receives: Other: Exercise |
| Resistance exercise | Experimental | Not described Receives: Other: Exercise |
| High intensity interval exercise | Experimental | Not described Receives: Other: Exercise |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: 28 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Nov 2019
- Study start11 Aug 2020
- Primary completion23 Dec 2021
- Study completion3 Jan 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Other trials for Type 1 DiabetesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 30 participants (actual)
Sponsor and investigators
- Lead sponsor
- Oregon Health and Science University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Jessica Castle, Oregon Health and Science University
- Investigators
- Jessica Castle, MD, Principal investigator, Oregon Health and Science University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04154904
- Sponsor's protocol ID
- 20248
- Other IDs
- 1R01DK122583-01
- Status last verified
- Jul 2023
- First submitted
- 5 Nov 2019
- Last updated
- 1 Aug 2023
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 1 Aug 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of a Context-aware Glucose Prediction Algorithm in Patients With Type 1 Diabetes
- ClinicalTrials.gov ID
- NCT04154904
- Acronym / sponsor ID
- 20248
- Conditions
- Type 1 Diabetes
- Keywords
- automated insulin delivery systems, Context patterns
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 30 participants (actual)
- Lead sponsor
- Oregon Health and Science UniversityUniversity, hospital or other
- Collaborators
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
- Study start
- 11 Aug 2020 (actual)
- Primary completion
- 23 Dec 2021 (actual)
- Study completion
- 3 Jan 2022 (actual)
- First posted
- 7 Nov 2019 (actual)
- Results
- Posted 12 Jul 2023
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Subjects will be on study for 28 days. Sensor glucose, activity, exercise, insulin, indoor and outdoor contextual patterns and meal data will be collected during this time. Subjects will wear the Dexcom G6 CGM system and a physical activity monitor for the entire 28 days. Subjects will continue to use their own insulin pump. Subjects will be asked to also wear a MotioWear indoor/outdoor context-aware tracking tag and to install the MotioWear beacons within their home. Subjects will be randomized to complete either aerobic, high intensity interval training, or resistance exercise videos twice weekly at home during weeks 1 and 2 and once during weeks 3 and 4. Subjects will also ingest a self-selected meal prior to these prescribed exercise sessions. Subjects will eat a high carbohydrate dinner once each week on the same day at the same approximate time of day (but not on the exercise days).
Subjects will use the T1 DEXI mobile app created by OHSU to capture meal and exercise data along with photos of meals the day of exercise and the day after. While at home, subjects will check CBG before and after exercise, for symptoms of hypoglycemia, and for Dexcom G6 alarms for sensor <70 mg/dL and >250 mg/dL.
Study design
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Aerobic exercise | Experimental | Other: Exercise |
| Resistance exercise | Experimental | Other: Exercise |
| High intensity interval exercise | Experimental | Other: Exercise |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (7 listed)
- 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.
Key exclusion criteria (23 listed)
- 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.
- 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.
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| ExerciseSubjects will be randomized to complete either aerobic, high intensity interval training, or resistance exercise videos twice weekly at home. | Other | Aerobic exercise, High intensity interval exercise, Resistance exercise |
Primary outcome
Comparison of the Mean Absolute Relative Difference When Including Patterns in Hypoglycemia Prediction.
Time frame: 28 days
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.
Comparison of the Mean Relative Difference When Including Patterns in Hypoglycemia Prediction.
Time frame: 28 days
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.
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 1 Aug 2023.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Jessica Castle, MD principal investigator
Oregon Health and Science University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Exercise in people with Type 1 Diabetes, run by Oregon Health and Science University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 23 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 1 Aug 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 12 Jul 2023). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Comparison of the Mean Absolute Relative Difference When Including Patterns in Hypoglycemia Prediction. (time frame: 28 days). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 1 Aug 2023.