Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Horizon2020 Introduction Wearable devices are gaining interest in the clinical assessment of physical behavior as a marker of disease severity. With the increased use, patient willingness and adherence will be increasingly important. As part of the SafeHeart study, examining the potential of physical behavior as an identifier of clinical deterioration in patients with an implantable cardioverter defibrillator (ICD), we present preliminary results on adherence to a wrist-worn wearable used for physical behavior assessment. Purpose Define the willingness to participate and long-term adherence to wearables in an ICD population. Methods This is a preliminary analysis of the ongoing multicenter, prospective, observational SafeHeart study. SafeHeart is aimed to construct a personalized prediction engine for ICD therapy using wearable-assessed physical behavior, remote ICD monitoring, electronic health records, and patient-reported data. The study will enroll 400 participants with an ICD with or without cardiac resynchronization therapy (CRT-D). In this preliminary analysis, wearable data was analyzed for the first 50 participants, where inclusion required a minimum of 1 month of follow up data. No data from the wearables were provided to the participants. The wrist-worn wearables were used continuously (day and night) for up to 12 months of follow-up. Adherence to the wearable was measured through patient-reported (subjective) adherence and wearable-measured (objective) adherence. Data were extracted from the wearables and non-wear time was detected via open source algorithms. A valid day was set to 22 hours of available wear time with 24-hour periods assessed from 3pm to 3pm for sleep metric capture. The willingness to participate and dropout rates were calculated for the same first 50 patients of the study. Results A total of 50 ICD participants were included in this study. The mean age was 65.1 years, 82 % male, with a mean follow up of 7 weeks, generating 326 patient weeks of data. Regarding patient-reported adherence, participants reported 81.4% full adherence and 18.6 % of participants reported very brief non-wear due to e.g. sauna or surgery. Of those reporting non-wear, 62.5% described one episode only of non-wear lasting 15-75 minutes. Regarding objectively measured adherence from wearable data, full adherence was shown in 91.7% of days. The mean number of valid days per participant was 41.3. Recruitment rates showed a willingness to participate of 50% (50/100) out of eligible subjects invited. No participants were lost to follow Conclusion Results show high adherence and reasonable willingness to participate without wearable adherence dropping over time. Comparison of objectively measured and patient-reported adherence showed similar values.
Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Horizon Introduction There is a growing interest in the use of accelerometers and sensors embedded in implantable cardioverter-defibrillators (ICDs) for monitoring patient activity. Despite evidence regarding the potential clinical value of device-measured activity (D-PA), the validity of these measurements has not yet been established. Objective To assess the validity of device-measured activity against a research-grade, widely validated wearable accelerometer. Methods This is a subanalysis of the ongoing multicenter, prospective SafeHeart study. Raw accelerometry data was continuously sampled at 50Hz from a wrist-worn accelerometer (GENEActiv) during 12 months. Days with at least 22 hours of wear time were used to create summary measures of time in activity, daily active volume and total slow walking steps. These measures were compared to D-PA harmonised as percentage of active time per day, from four different ICD vendors’ remote transmission data, using linear mixed effect models. Results Wearable and device-measured activity data in 51 ICD patients rendered 1228 days (mean 24 days ±19) with both wearable and device-measured activity data. There were significant differences between wearable and device-measured accelerometery in the average time active per day (Table 1). For two vendors significant associations between D-PA, daily active volume, and total slow walking steps were observed. Also, associations between D-PA and daily active time and moderate vigorous physical activity were found in a third vendor. For the fourth vendor no association between any wearable activity metric and D-PA was found. Inter-patient differences accounted for 73.1% of the total variance in D-PA. Conclusion Results demonstrate substantial differences in device-measured activity measurements compared to research-grade activity data. This has implications for the utility and generalizability of D-PA as clinical parameter.
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