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Abstract: PO1167

Feasibility Study of Wrist-Based Wearable Activity Trackers in Hemodialysis Patients

Session Information

Category: Dialysis

  • 701 Dialysis: Hemodialysis and Frequent Dialysis

Authors

  • Thwin, Ohnmar, Renal Research Institute, New York, New York, United States
  • Han, Maggie, Renal Research Institute, New York, New York, United States
  • Preciado, Priscila, Renal Research Institute, New York, New York, United States
  • Tao, Xia, Renal Research Institute, New York, New York, United States
  • Tapia, Mirell, Renal Research Institute, New York, New York, United States
  • Rivera Fuentes, Lemuel, Renal Research Institute, New York, New York, United States
  • Hakim, Mohamad I., Renal Research Institute, New York, New York, United States
  • Patel, Amrish U., Renal Research Institute, New York, New York, United States
  • Grobe, Nadja, Renal Research Institute, New York, New York, United States
  • Thijssen, Stephan, Renal Research Institute, New York, New York, United States
  • Kotanko, Peter, Renal Research Institute, New York, New York, United States
Background

Wearable activity trackers allow physicians to access patient’s physical activity (PA) outside the dialysis clinic. Hemodialysis (HD) population have an increased cardiovascular mortality and they are less active than their healthy counterparts. We aim to assess the feasibility of use of a wearable trackers in a HD population.

Methods

HD patients from 4 NYC clinics were enrolled in the study starting from June 2018 , followed up to 1 year. Patients ≥18 years on maintenance HD, able to walk, owning a smartphone, tablet or PC were included. Each patient received a wrist-based monitoring device (Fitbit Charge 2) to wear for a year. They were trained how to use and sync data . A stepwise intervention was created. After 3 in-person visits are completed, patients were deemed non-adherent and withdrawn. Events such as device failure or broken band were not counted as an in-person visit. We used Kaplan-Meier analysis to study time to withdrawal for non-adherence and predictors of time to withdrawal were assessed by univariate Cox Regression. The end of the observation period was May 8, 2020.

Results

118 patients were studied. Patients were 54±12 years old with a HD vintage of 5.2±5.1 years, 37% lived alone, 59% unemployed, 57% were African American, and 42% had an education level of some college or higher. Seventeen patients were withdrawn due to non-adherence. Mean and median time to withdrawal were 280 days (95%CI 260-301) and 359 days (95%CI 324-365). The probability of retention is shown in Fig.1. There was no association found between age, gender, race, living status, and education and time to withdraw due to non-adherence.

Conclusion

Only a small number of patients were withdrawn due to non-adherence, and the average time to withdraw was 9 months. We believe that the use of a wrist-based wearable device for remote patient monitoring, at least up to one year, is feasible in the HD population.

Funding

  • Private Foundation Support