Aims: Patients with heart failure often display a distinct pattern of walking characterized by short step-length and frequent short pauses. In the current study we sought to explore if qualitative aspects of movement have any additive value to established factors to predict all-cause mortality in patients with advanced heart failure.
Methods and results: 60 patients with advanced heart failure (NYHA III, peak VO2 <20 ml/kg and LVEF <35%) underwent symptom-limited CPX, echocardiography and routine chemistry. Physical activity was assessed using an accelerometer worn attached to the waist during waking hours for 7 consecutive days. The heart-failure survival score (HFSS) was calculated for each patient. All accelerometer-derived variables were analyzed with regard to all-cause mortality and added to a baseline model utilizing HFSS scores. HFSS score was significantly associated with the incidence of death (P<0.001; c-index 0.71; CI, 0.67-0.73). The addition of peak skewness to the HFSS model significantly improved the predictive ability with an increase in c-index to 0.74 (CI, 0.69-0.78), likelihood ratio P<0.02, establishing skewness as a predictor of increased event rates when accounting for baseline risk.
Conclusion: The feature skewness, a measure of asymmetry in the intensity level of periods of high physical activity, was identified to be predictive of all-cause mortality independent of the established prognostic model-HFSS and peak VO2. The findings from the present study emphasize the use of accelerometer analysis in clinical practice to make more accurate prognoses in addition to extract features of physical activity relevant to functional classification.