Accelerometer-measured physical activity in patients with heart failure and reduced ejection fraction: Determinants and relationship with patient-reported health status

Background

Accelerometer-measured physical activity is an increasingly used endpoint in heart failure (HF) trials. We investigated the determinants of accelerometer-measured physical activity and the relationship with patient-reported health status.

Methods

Post-hoc analysis of the Empire HF trial, including outpatients with HF with reduced ejection fraction (HFrEF). Physical activity was quantified as average accelerometer counts per minute (CPM) with higher values representing higher activity. We investigated associations between activity level and clinical variables, including age, sex, and body mass index, as well as patient-reported health status assessed by Kansas City Cardiomyopathy Questionnaire (KCCQ).

Results

Complete data were available in 180 (95%) patients (86% male, mean age 65 year). Baseline median physical activity level was 1,318 CPM (Q1-Q3 1,111-1,585). Age and anemia were independently associated with activity level (β-coefficients: −10 CPM per year age increase [95% CI −16 to −5.1], P = .00015, and −126 CPM for anemia [95% CI −9.1 to −244], P = .035). Significant independent associations were observed between activity level and all KCCQ summary scores (β-coefficient point estimates of 3.7, 4.6, and 4.9 CPM, all P < .02). For 12-week changes in KCCQ-summary scores, only the KCCQ-CSS was associated with activity level; mean increase of 17.5 CPM [95% CI 1.5 to 34.0], P = 0.032, per 5-point increase in KCCQ-CSS. Associations were not modified by treatment allocation (interaction P-values > .05).

Conclusions

In patients with HFrEF, older age and anemia were independently associated with lower activity. Moreover, physical activity only weakly increased with better health status, suggesting that changes in physical activity reflect improvements in patients’ health status to a limited degree. This highlights the need to better understand the endpoint with regards to all other health parameters to ease interpretation in future HF trials.