Abstract 4369009: Near-Maximal Movement Captured by Accelerometry Offers Superior Mortality Risk Prediction Than Aggregate Movement in Heart Failure

A Abhinav Sharma G George Perlman (Research Institute of the McGill University Health Centre, Montréal, Quebec, Canada) O Orhun Kose (Research Institute of the McGill University Health Centre, Montréal, Quebec, Canada) C Carlos Octavio Perez Mendoza (Research Institute of the McGill University Health Centre, Montréal, Quebec, Canada) E Elite Possik

Abstract

Background: There is a growing interest in understanding the impact of tested therapies on real-world functional outcomes as measured by wearable accelerometers (ACC) in heart failure (HF). However, there is a need to validate clinically meaningful ACC biomarkers as trials have shown limited efficacy in improving aggregate ACC measures such as daily steps to date. Here, we examine the association between an established aggregate ACC measure and a novel biomarker of near-maximal movement with the risk of all-cause and cardiovascular (CV) mortality in patients with HF. Research Question: How do measures of aggregate vs. near-maximal volitional movement captured via accelerometry compare in their prediction of mortality risk in patients with heart failure? Methods: Participants in the 2011–2012 and 2013–2014 waves of NHANES wore the Actigraph GT3X+ on their wrist for 7 days and were followed up to confirm mortality status and cause of death (ICD-10) in 2019. The sum of vector magnitudes (SVM) was calculated as the mean vector magnitude of acceleration for every 5 minutes. SVM values were ranked numerically and the 90 th percentile value was captured for each participant as a novel biomarker (i.e., SVM-90) of near-maximal movement. The aggregate ACC metric Monitor-independent movement summary (MIMS) was downloaded from the NHANES website. Cox proportional hazards models were employed to evaluate the relationship between SVM-90 and MIMS values above or below the cohort median and time to all-cause or CV mortality. Results: 291 participants with self-reported HF (50.9% female, mean (SD) age 66.8 (12.6), mean 5.4 years of follow-up) were included. Participants with SVM-90 below the median were older than their counterparts (age 70.6 (10.9) vs. 63.0 (13.1), p<0.001) while other demographics did not differ between groups. In models adjusted for MIMS above or below the median, the high SVM-90 group presented reduced risk of all-cause (HR 0.56 (0.38-0.84), p=0.00444, Fig.1A) and CV mortality (HR 0.43 (0.23-0.79), p=0.00676, Fig.1B) compared to the low SVM-90 group, while MIMS was not associated with risk of either outcome (all-cause: HR 0.72 (0.49-1.06), p=0.0959; CV: HR 0.81 (0.45-1.45), p=0.478). Conclusion: Here we provide evidence that a measure of near-maximal movement captured by ACC offers superior mortality prediction in HF compared to aggregate movement. ACC provides objective and patient-centric biomarkers that may serve as outcomes in HF trials.

Article Details

Journal Circulation
Volume / Issue Vol. 152, Issue Suppl_3
Published November 04, 2025
ISSN 0009-7322
Publisher Lippincott Williams & Wilkins

Journal Info

Circulation

Lippincott Williams & Wilkins

ISSN: 0009-7322 Health Sciences

Authors (5)

A

Abhinav Sharma

G

George Perlman

Research Institute of the McGill University Health Centre, Montréal, Quebec, Canada

O

Orhun Kose

Research Institute of the McGill University Health Centre, Montréal, Quebec, Canada

C

Carlos Octavio Perez Mendoza

Research Institute of the McGill University Health Centre, Montréal, Quebec, Canada

E

Elite Possik