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.
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 Type
OBSERVATIONAL
Enrollment
210
A multisensor smartwatch that includes neurophysiological sensors such as heart rate sensor to monitor the vitals of the participant.
McGill University health Center
Montreal, Quebec, Canada
Presence or absence of T2DM
As defined by HbA1c \> 6.5 %, known history of T2DM, or on antihyperglycemic therapies
Time frame: Cross sectional based on a single clinic visit with device worn for an estimated 24 hours
Glycemic control amongst people with established T2DM.
As defined by HbA1c %
Time frame: Cross sectional based on a single clinic visit with device worn for an estimated 24 hours
Glycemic control.
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%
Time frame: Cross sectional based on a single clinic visit with device worn for an estimated 24 hours
Change in glycemic control.
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
Time frame: On average the change will be evaluated over 3-6 months
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