Clinical trial NCT04217369: Impacts of Glucose Forecasting
Official title: Impacts of Estimated Future Glucose Values on Health
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Diabetes Mellitus, Type 1
Diabetes Mellitus, Type 2
Lead sponsor: Bio Conscious Technologies Ltd
Sponsor class: INDUSTRY
First posted: 2020-01-03
Enrollment: 90
Sex: ALL
Minimum age (years): 18
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention 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.
Primary purpose: SUPPORTIVE_CARE

Brief 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 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.

Eligibility criteria: Inclusion Criteria:

* 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)

Exclusion Criteria:

* 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

Primary outcomes:
measure: Time in Range
timeFrame: One day
Secondary outcomes:
measure: BGL variability (SD) BGL variability (SD)
timeFrame: 1 day
measure: BGL Variability (ADRR)
timeFrame: 14 days
measure: Time below range
timeFrame: 1 day
measure: Change is HbA1c
timeFrame: 14 days
measure: Laboratory HbA1c
timeFrame: 90 days
Other outcomes:
Locations:
Study officials:
References: