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A Digital Health Framework to Assess Glycemia and Physical Activity in Kidney Transplant Candidates: A Pilot Study
Carina M Flaherty1, Christopher Sanchez1, Celina Liu1
1Division of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY.
Background:
Kidney transplant recipients are at risk for adverse health outcomes. Digital health tools such as wearable accelerometers and continuous glucose monitors (CGMs) can provide detailed, noninvasive tracking of health behaviors and measures, such as physical activity, sleep, and glucose levels, that may offer insights into future health concerns, such as posttransplant diabetes mellitus, cognitive health, and transplant rejection. However, there is limited evidence on the feasibility and acceptability of these devices in kidney transplant candidates older than 50 y.
Methods:
This observational cross-sectional pilot study aimed to examine the feasibility of 2 digital health tools: an accelerometer and a continuous glucose monitor. Participants were eligible for the study if they were living donor kidney transplant candidates, aged 50 y or older, had no known cognitive impairments, and could provide informed consent. Participants were asked to wear a CGM and an accelerometer for up to 14 d before their kidney transplant surgery. Device feasibility was quantified by (1) the total time the devices were worn, and (2) the validated System Usability Scale survey administered after the devices were returned.
Results:
20 participants enrolled in the study (mean age 64 ± 9 y, 25% women, 40% with type 2 diabetes). The median number of days of accelerometer and CGM wear were 7 (interquartile range, 6-10) d and 7 (interquartile range, 7-10) d, respectively. Ninety percent of participants reported a favorable opinion of both devices. Participants wore the CGM 100% of the time and the accelerometer 90% of the time, indicating high adherence.
Conclusions:
The use of digital devices was acceptable among kidney transplant candidates aged older than 50 y, paving the way for larger studies to identify early digital biomarkers of health outcomes in this high-risk population.
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