A statistical approach to discriminate between non-fallers, rare fallers and frequent fallers in older adults based on posturographic data. (February 2016) - Maranesi, E.; Merlo, A.; Fioretti, S.; Zemp, D.D.; Campanini, I.; Quadri, P.
Abstract: Background: Identification of future non-fallers, infrequent and frequent fallers among older people would permit focusing the delivery of prevention programs on selected individuals. Posturographic parameters have been proven to differentiate between non-fallers and frequent fallers, but not between the first group and infrequent fallers. Methods: In this study, postural stability with eyes open and closed on both a firm and a compliant surface and while performing a cognitive task was assessed in a consecutive sample of 130 cognitively able elderly, mean age 77(7)years, categorized as non-fallers (N = 67), infrequent fallers (one/two falls, N = 45) and frequent fallers (more than two falls, N = 18) according to their last year fall history. Principal Component Analysis was used to select the most significant features from a set of 17posturographic parameters. Next, variables derived from principal component analysis were used to test, in each task, group differences between the three groups. Findings: One parameter based on a combination of a set of Centre of Pressure anterior-posterior variables obtained from the eyes-open on a compliant surface task was statistically different among all groups, thus distinguishing infrequent fallers from both non-fallers ( P  < 0.05) and frequent fallers ( P  < 0.05). Interpretation: For the first time, a method based on posturographic data to retrospectively discriminate infrequent fallers was obtained. The joint use of both the eyes-open on a compliant surface condition and this new parameter could be used, in a future study, to improve the performance of protocols and to verify the ability of this method to identify new-fallers in elderly without cognitive impairment. Highlights: Principal component analysis is used to select features from postural parameters Association between fall history and values of new parameters is analyzed 130 elderly non-fallers, infrequent fallers and frequent fallers are analyzed Eyes open compliant surface results optimal task to identify non/infrequent fallers