Diabetes Mellitus, Type 1NCT04217369
Impacts of Glucose Forecasting
A study testing Diabits Predictions in people with Diabetes Mellitus, Type 1 and Diabetes Mellitus, Type 2, run by Bio Conscious Technologies Ltd.
Trial summary
This is a study of individuals with type I or type II diabetes. It is meant to test the effect of using the Diabits app on a participant's blood glucose control. The Diabits app is a diabetes management app which integrates with your continuous glucose monitor (CGM) and presents not only your current blood glucose… Read more about this study
- Who is it for?
- Ages 18 to 75 years
- Conditions the study is for
- Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2
- What is being tested?
- Diabits Predictions
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 90 participants
- Where
- No sites listed yet
- Study dates
- 4 May 2020to 1 Dec 2020
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- An individual with type I or type II diabetes treated with > 1 insulin injections
- Currently using a smartphone compatible with the Diabits app
- Are willing to, or already wear a CGM which is compatible with the Diabits app
- Willing and able to provide informed consent, to have their data collected, and to complete questionnaires that are included as part of the protocol.
- HbA1c between 7.5 - 10 % ( 86 - 58 mmol/mol)
Who cannot join
- Patients who are pregnant or are planning to become pregnant during the duration of the study.
- Patients with major psychiatric illness or severe end-stage diabetes complications.
- Patients who use sensor-augmented pumps with automated features such as hybrid closed loop or predictive insulin suspension. This includes those who use non-commercial software such as DIY closed loop.
- Patients with prior use of the Diabits app
About this study
Official title: Impacts of Estimated Future Glucose Values on Health
This is a study of individuals with type I or type II diabetes. It is meant to test the effect of using the Diabits app on a participant's blood glucose control. The Diabits app is a diabetes management app which integrates with your continuous glucose monitor (CGM) and presents not only your current blood glucose trend, but also an estimate of your blood glucose values up to 60 minutes into the future. The Diabits app has been available in the USA and Canada for the past two years and was validated for predictive accuracy at BC Children's Hospital in Canada in 2017 with a predicted accuracy of 94.9%. Diabits app users in North America have shown some improvements in their individual time in range (TIR) and HbA1c values. This study aims to validate those results in a clinical setting. The study will randomise a total of 90 participants into using the Diabits app with or without the glucose forecasting enabled to help determine if the glucose forecasting (or predictions) can help participants make better treatment decisions and improve not only measurements of glucose such as time in range and HbA1c, but also reduce anxiety and improve quality of life with diabetes.
Read the detailed description
This study focuses on the impact of the Diabits app, a smartphone application which assists a person with diabetes to better manage their blood glucose. The Diabits app connects to a user's continuous glucose monitor (CGM) such as an Abbott Freestyle Libre, and predicts what the user's blood glucose will be over the next 60 minutes, updating every 5 minutes. The Diabits app displays that prediction to the user so that the user may make proactive decisions about insulin and food, with the goal of achieving more stable blood glucose control.
The study will evaluate the impact which having access to blood glucose predictions has on a user's time in range (TIR). The hypothesis is that having access to blood glucose predictions will improve the user's ability to stay within their target blood glucose range by 5% within a given 24 hour period. This is a randomized controlled trial. A control group with Abbott Freestyle Libre CGMs will be recruited, and given a version of the Diabits app which does not display any blood glucose forecasts. A treatment group, also with Abbott Freestyle Libres, will be given the Diabits app with glucose forecasts enabled. Both groups will be asked to use the app as their primary diabetes management tool for the duration of the study.
The study will run for 3 months. At the beginning of the study the 90 participants will be separated evenly into two groups. A blood test will be done to measure HbA1c and each participant will complete a number of surveys. At the end of the study the same activities will occur. Following conclusion, results will be evaluated to determine what differences develop between the control and treatment groups.
- Being tested
- Diabits Predictions
- Medical subject headings
- Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Diabits PredictionsDevice
Participants will be able to view predictions of future blood glucose. These predictions will indicate where the participant's blood glucose will travel over the next hour given that the participant's state does not change. Based on this, the participant is expected, but not required to make decisions about their activity, food, and insulin, in order to maintain blood glucose in a healthy range. The intervention does not require a specific method of glucose management, or event that a participant takes any action after viewing a prediction, the intervention is simply to display the prediction.
| Study group | Role | What they receive |
|---|---|---|
| Control | No intervention | A control arm. The participant will be given a version of the Diabits app without predictions of blood glucose enabled. They will then use the Diabits app as if they were using their usual companion app to manage their diabetes for the duration of the study. |
| Intervention | Experimental | The intervention arm. The participants in this arm will be provided with a version of the Diabits app which provides predictions of where their blood glucose will be one hour into the future, based on historic data and user inputs. The participant will then manage their blood glucose using these predictions for the duration of the study. Receives: Device: Diabits Predictions |
What is being measured
The primary outcome is the main question the study is designed to answer.
Time in Range
The proportion of time in a single day in which a given participant's blood glucose is within a predetermined target blood glucose range.
Measured: One day
Secondary outcomes (5)
BGL variability (SD) BGL variability (SD)
The standard deviation from the mean of the participant's blood glucose
Measured: 1 day
BGL Variability (ADRR)
Average Daily Risk Range, a measure of variability which assesses two weeks of data to identify risk of out-of-range events.
Measured: 14 days
Time below range
A proportion of time where the participant's blood glucose is below 3.9 mmol/L, and is below 3.0 mmol/L, respectively
Measured: 1 day
Change is HbA1c
A calculated metric which is an analogue to a laboratory HbA1c measure, to assess the likelihood of measurable changes in HbA1c
Measured: 14 days
Laboratory HbA1c
A blood test which measures hemoglobin A1c, an indicator of long term tissue damage
Measured: 90 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Jan 2020
- Study start4 May 2020 (estimated)
- Primary completion1 Dec 2020 (estimated)
- Study completion1 Dec 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabetes Mellitus, Type 1Studies 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
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Participants will be assigned randomly at the time of recruitment into two groups: a treatment group and a control group. Both groups will be given the app, but the control group will not have predictions enabled.
- Masking
- None (open label)
- Enrolment
- 90 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Bio Conscious Technologies Ltd
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04217369
- Sponsor's protocol ID
- 2019
- Status last verified
- Jan 2020
- First submitted
- 26 Dec 2019
- Last updated
- 3 Jan 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: IPD will not be made available.
Study at a glance
From the registry record, last updated by the sponsor on 3 Jan 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Impacts of Estimated Future Glucose Values on Health
- ClinicalTrials.gov ID
- NCT04217369
- Acronym / sponsor ID
- 2019
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 90 participants (estimated)
- Lead sponsor
- Bio Conscious Technologies LtdIndustry (pharma, biotech, devices)
- Study start
- 4 May 2020 (estimated)
- Primary completion
- 1 Dec 2020 (estimated)
- Study completion
- 1 Dec 2020 (estimated)
- First posted
- 3 Jan 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This is a study of individuals with type I or type II diabetes. It is meant to test the effect of using the Diabits app on a participant's blood glucose control. The Diabits app is a diabetes management app which integrates with your continuous glucose monitor (CGM) and presents not only your current blood glucose trend, but also an estimate of your blood glucose values up to 60 minutes into the future. The Diabits app has been available in the USA and Canada for the past two years and was validated for predictive accuracy at BC Children's Hospital in Canada in 2017 with a predicted accuracy of 94.9%. Diabits app users in North America have shown some improvements in their individual time in range (TIR) and HbA1c values. This study aims to validate those results in a clinical setting. The study will randomise a total of 90 participants into using the Diabits app with or without the glucose forecasting enabled to help determine if the glucose forecasting (or predictions) can help participants make better treatment decisions and improve not only measurements of glucose such as time in range and HbA1c, but also reduce anxiety and improve quality of life with diabetes.
Detailed description
This study focuses on the impact of the Diabits app, a smartphone application which assists a person with diabetes to better manage their blood glucose. The Diabits app connects to a user's continuous glucose monitor (CGM) such as an Abbott Freestyle Libre, and predicts what the user's blood glucose will be over the next 60 minutes, updating every 5 minutes. The Diabits app displays that prediction to the user so that the user may make proactive decisions about insulin and food, with the goal of achieving more stable blood glucose control.
The study will evaluate the impact which having access to blood glucose predictions has on a user's time in range (TIR). The hypothesis is that having access to blood glucose predictions will improve the user's ability to stay within their target blood glucose range by 5% within a given 24 hour period. This is a randomized controlled trial. A control group with Abbott Freestyle Libre CGMs will be recruited, and given a version of the Diabits app which does not display any blood glucose forecasts. A treatment group, also with Abbott Freestyle Libres, will be given the Diabits app with glucose forecasts enabled. Both groups will be asked to use the app as their primary diabetes management tool for the duration of the study.
The study will run for 3 months. At the beginning of the study the 90 participants will be separated evenly into two groups. A blood test will be done to measure HbA1c and each participant will complete a number of surveys. At the end of the study the same activities will occur. Following conclusion, results will be evaluated to determine what differences develop between the control and treatment groups.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Participants will be assigned randomly at the time of recruitment into two groups: a treatment group and a control group. Both groups will be given the app, but the control group will not have predictions enabled.
| Arm | Type | Receives |
|---|---|---|
| Control | No intervention | –A control arm. The participant will be given a version of the Diabits app without predictions of blood glucose enabled. They will then use the Diabits app as if they were using their usual companion app to manage their diabetes for the duration of the study. |
| Intervention | Experimental | Device: Diabits PredictionsThe intervention arm. The participants in this arm will be provided with a version of the Diabits app which provides predictions of where their blood glucose will be one hour into the future, based on historic data and user inputs. The participant will then manage their blood glucose using these predictions for the duration of the study. |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- An individual with type I or type II diabetes treated with > 1 insulin injections
- Currently using a smartphone compatible with the Diabits app
- Are willing to, or already wear a CGM which is compatible with the Diabits app
- Willing and able to provide informed consent, to have their data collected, and to complete questionnaires that are included as part of the protocol.
- HbA1c between 7.5 - 10 % ( 86 - 58 mmol/mol)
Key exclusion criteria (4 listed)
- Patients who are pregnant or are planning to become pregnant during the duration of the study.
- Patients with major psychiatric illness or severe end-stage diabetes complications.
- Patients who use sensor-augmented pumps with automated features such as hybrid closed loop or predictive insulin suspension. This includes those who use non-commercial software such as DIY closed loop.
- Patients with prior use of the Diabits app
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 |
|---|---|---|
| Diabits PredictionsParticipants will be able to view predictions of future blood glucose. These predictions will indicate where the participant's blood glucose will travel over the next hour given that the participant's state does not change. Based on this, the participant is expected, but not required to make decisions about their activity, food, and insulin, in order to maintain blood glucose in a healthy range. The intervention does not require a specific method of glucose management, or event that a participant takes any action after viewing a prediction, the intervention is simply to display the prediction. | Device | Intervention |
Primary outcome
Time in Range
Time frame: One day
The proportion of time in a single day in which a given participant's blood glucose is within a predetermined target blood glucose range.
5 secondary outcomes
BGL variability (SD) BGL variability (SD)
Time frame: 1 day
BGL Variability (ADRR)
Time frame: 14 days
Time below range
Time frame: 1 day
Change is HbA1c
Time frame: 14 days
Laboratory HbA1c
Time frame: 90 days
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Jan 2020.
- Individual participant dataSharing planned: No. IPD will not be made available.
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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.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
A study testing Diabits Predictions in people with Diabetes Mellitus, Type 1 and Diabetes Mellitus, Type 2, run by Bio Conscious Technologies Ltd.
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 5 inclusion and 4 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: status not confirmed, as of the sponsor's last update on 3 Jan 2020. Status can change between updates, so confirm with the study contact before making plans.
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?
Results are not available in the source record.
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?
Time in Range (time frame: One day). 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 3 Jan 2020.