OBJECTIVES: The present study was conducted to investigate and validate the accelerometry data (PA%) of the CRT device with an external activity monitor (Actigraph GT3X+). We were also curious to learn whether the result of the 6MWT test could be estimated using PA% from Home Monitoring. Moreover, we wished to clarify the possibility of using this information for sensing the changes in the condition of heart failure patients with remote control.

METHODS: This study was a longitudinal design. The patients wore the Actigraph for a week, and the Home Monitoring data collection covered a year. We used descriptive statistics, Spearman’s rank correlation analysis, and linear regression, and Bland-Altman plots in the study. The patients wore the Actigraph for a week (29.09.2018-10.10.2019), and the Home Monitoring data collection covered a year (01.07.2018-01.07.2019). A total of 42 CRT patients from the Heart Clinic of the University of Pécs were enrolled.

RESULTS: The analysis of the 6MWT and the PA% data revealed a correlation with a linear regression (F= 6.126; p= 0.018). With this regression equation, the assessing distance of the 6MWT could be estimated. The Bland-Altman plots also showed that there was a correlation between the mean and the difference, with higher means resulting in larger (negative) differences (R2=0.109; F=4.665; p=0.037; Beta=-0.362; p=0.037) between the Actigraph GT3X+ and the built-in device activity data. The PA% result is applicable in estimating the walking distance of 6MWT. We suggest using this equation to estimate patients’ health status/ physical activity monitoring, as it could be a predictor of the worsening health status.

CONCLUSIONS: Based on the statistical analysis we found a negative correlation in mean differences between the accelerometer PA% and the built-in device’s PA% supporting the fact that the physical activity was slightly overestimated by the built-in PA%.