Influences of frailty syndrome on open-loop and closed-loop postural control strategy.

BACKGROUND As the population of older adults quickly increases, the incidence of frailty syndrome, a reduction in physiological reserve across multiple physiological systems, likewise increases. To date, impaired balance has been associated with frailty; however, the underlying frailty-related postural balance mechanisms remain unclear. OBJECTIVE The aim of the current study was to use open-loop (OL; postural muscles) and closed-loop (CL; postural muscles plus sensory feedback) mechanisms to explore differences in postural balance mechanisms between nonfrail (n = 44), prefrail (n = 59) and frail individuals (n = 19). METHODS One hundred and twenty-two older adults (age ≥65 years) without major mobility disorders were recruited, and frailty was measured using Fried's criteria. Each participant performed two 15-second trials of Romberg balance assessment, once with their eyes open and once with their eyes closed. Body-worn sensors were used to estimate center of gravity (COG) plots. Body-sway (traditional stabilogram analysis) and OLCL (stabilogram diffusion analysis) parameters were derived using COG plots and compared between groups using ANOVA. Frailty and prefrailty were estimated using a multiple variable logistic regression while controlling for age, body mass index, body-sway and OLCL parameters. RESULTS Between-group differences in the parameters of interest were more pronounced during the eyes-closed condition, for which OL duration was approximately 33 and 22% shorter, respectively, in the frail and prefrail groups when compared to nonfrail controls (mean = 1.9 ± 1.1 s, p = 0.01). The average rate of sway during the OL was 164 and 66% higher, respectively, in frail and prefrail when compared to nonfrail subjects (0.03 ± 0.02 cm(2)/s, p < 0.001). RESULTS also suggest that OLCL parameters can predict frail and prefrail categories when compared to nonfrail controls. Using this method, frailty was identified with a sensitivity and specificity of 97 and 88% (as compared to nonfrail), and prefrailty with 82 and 92%, respectively. CONCLUSIONS This study suggested an innovative method to differentiate between frailty status using sensory dependency characteristics of postural control. RESULTS suggest that postural muscle deconditioning may compromise balance in frail elders, leading to dependency on somatosensory feedback to compensate for errors and stabilize the system.