Key result
In patients with systolic heart failure, demographic and clinical data including age, functional class, and ejection fraction predicted 81% of the variation in daily steps measured by a step counter.
Why the study?
Physical activity decreases cardiovascular mortality and morbidity, but whether demographic and clinical data of patients with heart failure can predict walking activity monitored by a step counter was unknown.
RCT (n=65)
Demographic and clinical factors, including age, NYHA class, and ejection fraction, can strongly predict daily walking activity in patients with systolic heart failure using a step counter.
Answers are grounded in this paper and cite their sources.
Routine clinical data predict most daily step variation in systolic HF; confirms limited incremental value of step counters beyond standard variables.
BACKGROUND Physical activity has been shown to decrease cardiovascular mortality and morbidity. Walking, a simple physical activity which is an integral part of daily life, is a feasible and safe activity for patients with heart failure (HF). A step counter, measuring daily walking activity, might be a motivational factor for increased activity. OBJECTIVE The aim of this study was to examine the association between walking activity and demographical and clinical data of patients with HF, and whether these associations could be used as predictors of walking activity. METHODS A total of 65 patients with HF from the Future Patient Telerehabilitation (FPT) program were included in this study. The patients monitored their daily activity using a Fitbit step counter for 1 year. This monitoring allowed for continuous and safe data transmission of self-monitored activity data. RESULTS A higher walking activity was associated with younger age, lower New York Heart Association (NYHA) classification, and higher ejection fraction (EF). There was a statistically significant correlation between the number of daily steps and NYHA classification at baseline (P=.01), between the increase in daily steps and EF at baseline (P<.001), and between the increase in daily steps and improvement in EF (P=.005). The patients’ demographic, clinical, and activity data could predict 81% of the variation in daily steps. CONCLUSIONS This study demonstrated an association between demographic, clinical, and activity data for patients with HF that could predict daily steps. A step counter can thus be a useful tool to help patients monitor their own physical activity. CLINICALTRIAL ClinicalTrials.gov NCT03388918; https://clinicaltrials.gov/ct2/show/NCT03388918 INTERNATIONAL REGISTERED REPORT RR2-10.2196/14517
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Gade et al. (2020) conducted an RCT in Systolic Heart Failure (n=65). Fitbit step counter was evaluated on Variation in daily steps. In patients with systolic heart failure, demographic and clinical data including age, functional class, and ejection fraction predicted 81% of the variation in daily steps measured by a step counter.
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