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A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
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Wearable Device-Measured Physical Activity for Predicting Hospitalization-Associated Disability in Older Patients

Yosuke Yoshida1,2, Satoshi Okayama1,3, Daisuke Fujihara1

  • 1Department of Rehabilitation, Nara Prefectural Seiwa Medical Center Nara Japan.

Circulation Reports
|January 16, 2026
PubMed
Summary

Hospitalization-associated disability (HAD) in older heart failure (HF) patients can be predicted by wearable device data. Lower light-intensity physical activity (LPA) levels indicate a higher risk of developing HAD.

Keywords:
FrailtyHeart failureHospitalization-associated disabilityOlder agePhysical activity

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Area of Science:

  • Gerontology
  • Cardiology
  • Rehabilitation Medicine

Background:

  • Hospitalization-associated disability (HAD) negatively impacts post-discharge outcomes in elderly heart failure (HF) patients.
  • Identifying predictors of HAD is crucial for improving patient care and recovery.
  • Wearable technology offers a novel approach to monitoring physical activity in this population.

Purpose of the Study:

  • To determine if physical activity, measured by wearable devices, can predict hospitalization-associated disability (HAD) in older adults with heart failure (HF).

Main Methods:

  • Retrospective analysis of 104 elderly HF patients undergoing cardiac rehabilitation.
  • Physical activity was monitored for 3 days using wearable devices, categorized into sedentary behavior, light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA).
  • Receiver operating characteristic (ROC) curve analysis was used to identify predictive cut-off points for LPA.

Main Results:

  • HAD was present in 29.8% of the study participants.
  • Patients with HAD exhibited significantly shorter durations of LPA compared to those without HAD (45.7 min/day vs. 121.2 min/day).
  • An LPA threshold of 68 min/day demonstrated high sensitivity (87.1%) and specificity (80.8%) in predicting HAD (AUC=0.888).

Conclusions:

  • Wearable device-measured physical activity, specifically LPA, shows promise as a predictive tool for HAD in older HF patients.
  • This non-invasive method can aid in early risk stratification and intervention planning.
  • Further research can validate these findings and integrate wearable data into clinical practice for HF management.