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Impacts of Glucose Forecasting

NCT04217369 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 90

Last updated 2020-01-03

No results posted yet for this study

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.

Conditions

  • Diabetes Mellitus, Type 1
  • Diabetes Mellitus, Type 2

Interventions

DEVICE

Diabits Predictions

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.

Sponsors & Collaborators

  • Bio Conscious Technologies Ltd

    lead INDUSTRY

Study Design

Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-05-04
Primary Completion
2020-12-01
Completion
2020-12-01

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04217369 on ClinicalTrials.gov