Abstract: PO0918
Feasibility Study of Wrist-Based Wearable Activity Tracker in Hemodialysis Patients
Session Information
- Leveraging Technology and Innovation to Predict Events and Improve Dialysis Delivery
November 04, 2021 | Location: On-Demand, Virtual Only
Abstract Time: 10:00 AM - 12:00 PM
Category: Dialysis
- 701 Dialysis: Hemodialysis and Frequent Dialysis
Authors
- Han, Maggie, Renal Research Institute, New York, New York, United States
- Thwin, Ohnmar, Renal Research Institute, New York, New York, United States
- Tao, Xia, Renal Research Institute, New York, New York, United States
- Rivera Fuentes, Lemuel, 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
- Preciado, Priscila, Renal Research Institute, New York, New York, United States
- Tapia Silva, Leticia Mirell, Renal Research Institute, New York, New York, United States
- Hakim, Mohamad I., 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
Increased physical activity (PA) is associated with reduced risk of cardiovascular disease which is prevalent in hemodialysis (HD) patients. Wearable activity trackers (WAT) allow remote monitoring of PA. We aim to explore the feasibility of using a WAT for 1 year in HD patients.
Methods
HD patients from 4 NYC clinics were enrolled on a rolling basis starting June 2018 and followed for up to 1 year. Ambulatory patients ≥18 years, on maintenance HD, and owning a mobile device were included. Each patient was provided with and taught how to use the Fitbit Charge 2. A stepwise intervention plan was used to assess feasibility (Figure 1). We used Kaplan-Meier analysis to determine mean and median time to withdrawal for non-compliance (TW) and predictors of TW were assessed by univariate Cox Regression.
Results
119 patients were enrolled into the study. Patients were 54±12 years old, 59% African American, 37% lived alone, and 54% had an education level of college and above. 16% of patients were withdrawn for non-compliance. Mean and standard deviation TW was 175 ± 103 days. Median and interquartile range of TW was 133 and 181 days (98 to 280 days), respectively. The probability of not being withdrawn for non-compliance is shown in Figure 2. Age, gender, race, living status, and education were not associated with non-compliance.
Conclusion
A small portion of patients were continuously non-compliant with wearing/syncing their Fitbit devices in our study. Based on a low risk (<20%) of being withdrawn for non-compliance, we determined that it is feasible to use a wrist-based wearable device in HD patients for up to a year. However, prolonged use of these devices may require additional counseling to patients.
Funding
- Commercial Support –