Gait and balance assessments as early indicators of frailty in patients with known peripheral artery disease

Abstract

Background: Peripheral artery disease is associated with increased morbidity and mortality, and frailty syndrome may mediate the risk of these adverse health outcomes to predict intervention results. The aim of this study was to determine the association between motor performance impairments based on in-clinic gait and balance measurements with frailty at intermediate stages (pre-frailty) in peripheral artery disease patients.

Methods: Seventeen participants with peripheral artery disease (≥ 55 years) were recruited and frailty assessed using Fried criteria. Gait and balance were quantified using wearable sensor technologies in the clinical setting. Between-group differences in frailty were assessed using analysis of variance, and independent associations between gait and balance parameters with frailty were determined using logistic regression models.

Findings: Based on Fried index nine (53%), participants were pre-frail and eight (47%) were non-frail. Although no between-group differences in demographics or clinical parameters was observed, gait parameters were worse among pre-frail compared to non-frail participants. The highest effect sizes for between-group differences were observed in double support during habitual normal walking (effect size=1.86, p<0.01), speed variability during dual-task (effect size=1.26, p=0.03), and trunk sway during fast walking (effect size=1.43, p=0.02). No significant difference was observed in balance parameters (p>0.07). The regression model using gait parameters demonstrated a high sensitivity and specificity in predicting pre-frailty.

Interpretation: A short 25-step sensor-based in-clinic overground gait test objectively identified pre-frailty independent of age. Double support was the most sensitive parameter in identifying pre-frail aging adults.

Keywords: Balance postural control; Dual task; Frailty; Locomotion; Peripheral artery disease; Wearable sensor technology.

Copyright © 2015 Elsevier Ltd. All rights reserved.

Figures

Figure 1

Receiver operating characteristic (ROC) curves for predicting pre-frailty using demographic information and gait parameters within habitual normal walk condition. Similar results were obtained for dual-task and fast walk conditions. Area under curve (AUC) values are presented.