A Wrist-Worn Sensor-Derived Frailty Index Based on an Upper-Extremity Functional Test in Predicting Functional Mobility in Older Adults

Gerontology. 2021;67(6):753-761. doi: 10.1159/000515078. Epub 2021 Apr 1.

Abstract

Introduction: Preoperative frailty is an independent risk factor for postoperative complications across surgical specialties. Functional mobility such as gait, timed up and go (TUG), and 5 times sit-to-stand (5-STS) are popular preoperative frailty measurements but are not suitable for patients with severe mobility impairment. A wrist-worn sensor-derived frailty index based on an upper-extremity functional test (20-s repetitive elbow flexion-extension task; UEFI) was developed previously; however, its association with functional mobility remained unexplored. We aimed to investigate the predictive power of the UEFI in predicting functional mobility.

Methods: We examined correlation between the UEFI and gait speed, TUG duration, and 5-STS duration in 100 older adults (≥ 65 years) using multivariate regression analysis. The UEFI was calculated using slowness, weakness, exhaustion, and flexibility of the sensor-based 20-s repetitive elbow flexion-extension task.

Results: The UEFI was a significant predictor for gait speed and TUG duration and 5-STS duration (all R ≥ 0.60; all p < 0.001) with the variance (adjusted R2) of 35-37% for the dependent variables. The multivariate regression analysis revealed significant associations between the UEFI and gait speed (β = -0.84; 95% confidence interval [95% CI] = [-1.19, -0.50]; p < 0.001) and TUG duration (β = 16.2; 95% CI = [9.59, 22.8]; p < 0.001) and 5-STS duration (β = 33.3; 95% CI = [23.6, 43.2]; p < 0.001), found after accounting for confounding variables (e.g., age and fear of falling scale).

Conclusions: Our findings suggest that the UEFI can be performed with a wrist-worn sensor and has been validated with other established measures of preoperative frailty. The UEFI can be applied in a wide variety of patients, regardless of mobility limitations, in an outpatient setting.

Keywords: Digital health; Frailty; Gait; Motor capacity; Risk of falling; Sit to stand; Timed up and go; Wearable sensors.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Accidental Falls
  • Aged
  • Fear
  • Frailty* / diagnosis
  • Geriatric Assessment
  • Humans
  • Wrist