DECIDE-CV Using AI

Recruiting

• Conditions: Type 2 Diabetes

• Registration Number: NCT05482958
• Lead Sponsor: McGill University Health Centre/Research Institute of the McGill University Health Centre

Brief Summary

The purpose of this study is to identify digital biomarkers associated with type 2 diabetes mellitus (T2DM) by combining sensor data from a wrist-worn wearable and clinical data. This will be done by recruiting patients with and without diabetes within the cardio-metabolic clinics a the MUHC. Consented patients will be provided with a HOP Technologies (HOP) watch in this project across two observation periods. The Watch-HOP platform facilitates the development of predictive algorithms built with data collected in a clinical setting or at home in a passive (sensors) and active (self-assessments) way. Data from the Watch-Hop will be analyzed using machine learning strategies to determine associations with clinical measures of T2DM.

Detailed Description

The epidemic of type 2 diabetes mellitus (T2DM) continues to increase. Sensor technologies and artificial intelligence present us with an opportunity to identify patients suffering from T2DM and to optimize their treatment.

Specifically, our primary objective is to identify digital biomarkers associated with T2DM by combining sensor data from a wrist-worn wearable and clinical data.

Study Timeline

• Study First Submitted: 2022-07-26
• Study First Submitted QC: 2022-07-28
• Study Start: 2022-07-29
• Study First Posted: 2022-08-01
• Status Verified: 2023-08
• Last Update Submitted: 2023-08-03
• Last Update Posted: 2023-08-07
• Primary Completion: 2025-07-29
• Study Completion: 2025-07-29

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 126

Inclusion Criteria

1. Age > 18 years
2. Able to follow-up with study protocol schedule
3. Life expectancy > 1 year
4. Case group only a. HbA1c >= 6.5% or is diagnosed with T2DM

Exclusion Criteria

1. Age > 18 years
2. Able to follow-up with study protocol schedule
3. Life expectancy > 1 year
4. Case group only a. HbA1c >= 6.5% or is diagnosed with T2DM

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Presence or absence of T2DM	Cross sectional based on a single clinic visit with device worn for an estimated 24 hours	As defined by HbA1c \> 6.5 %, known history of T2DM, or on antihyperglycemic therapies
Glycemic control amongst people with established T2DM.	Cross sectional based on a single clinic visit with device worn for an estimated 24 hours	As defined by HbA1c %

Secondary Outcome Measures

Name	Time	Method
Glycemic control.	Cross sectional based on a single clinic visit with device worn for an estimated 24 hours	Whether the digital biomarker as identified by the wrist-worn device differs between participants who have T2DM with glycemic control while using antihyperglycemic medications versus participants who do not have T2DM with baseline HbA1c \< 6.5%. Glycemic control is defined as HbA1c \< 6.5%
Change in glycemic control.	On average the change will be evaluated over 3-6 months	Whether changes provided by the digital biomarker also correlate with changes in HbA1c after initiation of antihyperglycemic treatments in the same participant over time. Change in glycemic control as measured by HbA1c % with specific antihyperglycemic medication

Trial Locations

Locations (1)

McGill University health Center; 🇨🇦 Montreal, Quebec, Canada