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DECIDE-CV Using AI

Type 2 Diabetes

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.

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Conditions de participation

  • Sexe:

    ALL

  • Âges admissibles:

    18 and up

Critères de participation

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

Lieu de l'étude

McGill University health Center
McGill University health Center
Montreal, Quebec
Canada

Contactez l'équipe d'étude

Primary Contact

Abhinav Sharma, MD

[email protected]
514 934-1934
Étude parrainée par
McGill University Health Centre/Research Institute of the McGill University Health Centre
Participants recherchés
Plus d'informations
ID de l'étude: NCT05482958