Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-22T23:28:50.808Z Has data issue: false hasContentIssue false
  • English
  • Français

The relationship between gait dynamics and future cognitive decline: a prospective pilot study in geriatric patients

Published online by Cambridge University Press:  10 December 2017

Lisette H. J. Kikkert ,
Nicolas Vuillerme ,
Jos P. van Campen ,
Bregje A. Appels ,
Tibor Hortobágyi  and
Claudine J. C. Lamoth
Lisette H. J. Kikkert*
Affiliation:
University of Groningen, University Medical Centre Groningen, Center for Human Movement Sciences, Groningen, The Netherlands Université Grenoble Alpes, EA AGEIS, Grenoble, France Department of Geriatric Medicine, MC Slotervaart Hospital, Amsterdam, The Netherlands
Nicolas Vuillerme
Affiliation:
Université Grenoble Alpes, EA AGEIS, Grenoble, France Institut Universitaire de France, Paris, France
Jos P. van Campen
Affiliation:
Department of Geriatric Medicine, MC Slotervaart Hospital, Amsterdam, The Netherlands
Bregje A. Appels
Affiliation:
Department of Medical Psychology and Hospital Psychiatry, MC Slotervaart Hospital, Amsterdam, The Netherlands
Tibor Hortobágyi
Affiliation:
University of Groningen, University Medical Centre Groningen, Center for Human Movement Sciences, Groningen, The Netherlands
Claudine J. C. Lamoth
Affiliation:
University of Groningen, University Medical Centre Groningen, Center for Human Movement Sciences, Groningen, The Netherlands
*
Correspondence should be addressed to: Lisette H. J. Kikkert, University of Groningen, University Medical Centre Groningen, Center for Human Movement Sciences, Ant Deusinglaan 1, 9713 AV Groningen, The Netherlands. Phone: +31(0)50 363 2710. Email: l.h.j.kikkert@umcg.nl.
Get access

Abstract

Background:

Walking ability recently emerged as a sub-clinical marker of cognitive decline. Hence, the relationship between baseline gait and future cognitive decline was examined in geriatric patients. Because a “loss of complexity” (LOC) is a key phenomenon of the aging process that exhibits in multiple systems, we propose the idea that age- and cognition-related LOC may also become manifested in gait function. The LOC theory suggests that even healthy aging is associated with a (neuro)physiological breakdown of system elements that causes a decline in variability and an overall LOC. We used coordination dynamics as a conceptual framework and hypothesized that a LOC is reflected in dynamic gait outcomes (e.g. gait regularity, complexity, stability) and that such outcomes could increase the specificity of the gait-cognition link.

Methods:

19 geriatric patients (age 80.0±5.8) were followed for 14.4±6.6 months. An iPod collected three-dimensional (3D) trunk accelerations while patients walked for 3 minutes. Cognition was evaluated with the Mini-Mental State Examination (MMSE) and the Seven-Minute screen (7MS) test. The Reliable Change Index (RCI) quantified the magnitude of cognitive change. Spearman's Rho coefficients (ρ) indexed correlations between baseline gait and future cognitive change.

Results:

Seven patients showed reliable cognitive decline (“Cognitive Decline” group), and 12 patients remained cognitively stable (“Cognitive Stable” group) over time. Future cognitive decline was correlated with a more regular (ρ = 0.579*) and predictable (ρ = 0.486*) gait pattern, but not with gait speed.

Conclusions:

The increase in gait regularity and predictability possibly reflects a LOC due to age- and cognition-related (neuro)physiological decline. Because dynamic versus traditional gait outcomes (i.e. gait speed and (variability of) stride time) were more strongly correlated with future cognitive decline, the use of wearable sensors in predicting and monitoring cognitive and physical health in vulnerable geriatric patients can be considered promising. However, our results are preliminary and do require replication in larger cohorts.

Keywords

geriatric patientsfrailtycognitive impairmentgait analysisnon-linear dynamicspredictionloss of complexity
Type
Original Research Article
Information
International Psychogeriatrics , Volume 30 , Issue 9: Issue Theme: Quality of Care for Frail Older Adults , September 2018 , pp. 1301 - 1309
Copyright
Copyright © International Psychogeriatric Association 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allali, G. et al. (2016). Gait phenotype from mild cognitive impairment to moderate dementia: results from the GOOD initiative. European Journal of Neurology, 23, 527–541. doi: 10.1111/ene.12882.Google Scholar
Beauchet, O. et al. (2016). Poor gait performance and prediction of dementia: results from a meta-analysis. Journal of the American Medical Directors Association, 17, 482–490. doi: 10.1016/j.jamda.2015.12.092.Google Scholar
Brach, J. S., Perera, S., Van Swearingen, J. M., Hile, E. S., Wert, D. M. and Studenski, S. A. (2011). Challenging gait conditions predict 1-year decline in gait speed in older adults with apparently normal gait. Physical Therapy, 91, 1857–1864. doi: 10.2522/ptj.20100387.Google Scholar
Cignetti, F., Decker, L. M. and Stergiou, N. (2012). Sensitivity of the Wolf's and Rosenstein's algorithms to evaluate local dynamic stability from small gait data sets. Annals of Biomedical Engineering, 40, 1122–1130. doi: 10.1007/s10439-011-0474-3.Google Scholar
Costa, M., Peng, C. -L., Goldberger, A. and Hausdorff, J. M. (2003). Multiscale entropy analysis of human gait dynamics. Physica A: Statistical Mechanics and its Applications, 330, 53–60. doi: https://doi.org/10.1016/j.physa.2003.08.022.Google Scholar
de Groot, M. H., van Campen, J. P., Kosse, N. M., de Vries, O. J., Beijnen, J. H. and Lamoth, C. J. (2016). The association of medication-use and frailty-related factors with gait performance in older patients. PloS One, 11, e0149888. doi: 10.1371/journal.pone.0149888.Google Scholar
de Groot, M. H., van der Jagt-Willems, H. C., van Campen, J. P., Lems, W. F., Beijnen, J. H. and Lamoth, C. J. (2014). A flexed posture in elderly patients is associated with impairments in postural control during walking. Gait & Posture, 39, 767–772. doi: 10.1016/j.gaitpost.2013.10.015.Google Scholar
Holtzer, R., Epstein, N., Mahoney, J. R., Izzetoglu, M. and Blumen, H. M. (2014). Neuroimaging of mobility in aging: a targeted review. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 69, 1375–1388. doi: 10.1093/gerona/glu052.Google Scholar
Hooghiemstra, A. M. et al. (2017). Gait speed and grip strength reflect cognitive impairment and are modestly related to incident cognitive decline in memory clinic patients with subjective cognitive decline and mild cognitive impairment: findings from the 4C study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 72, 846–854. doi: 10.1093/gerona/glx003.Google Scholar
Inouye, S. K., Studenski, S., Tinetti, M. E. and Kuchel, G. A. (2007). Geriatric syndromes: clinical, research, and policy implications of a core geriatric concept. Journal of the American Geriatrics Society, 55, 780–791. doi: JGS1156 [pii].Google Scholar
Jacobson, N. S. and Truax, P. (1991). Clinical significance: a statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59, 12–19.Google Scholar
Kang, H. G. et al. (2009). Frailty and the degradation of complex balance dynamics during a dual-task protocol. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 64, 1304–1311. doi: 10.1093/gerona/glp113.Google Scholar
Kikkert, L. H. J. et al. (2017). Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic. PloS One, 12, e0178615. doi: 10.1371/journal.pone.0178615.Google Scholar
Kikkert, L. H., Vuillerme, N., van Campen, J. P., Hortobagyi, T. and Lamoth, C. J. (2016). Walking ability to predict future cognitive decline in old adults: a scoping review. Ageing Research Reviews, 27, 1–14. doi: S1568-1637(16)30009-5 [pii].Google Scholar
Kobsar, D., Olson, C., Paranjape, R., Hadjistavropoulos, T. and Barden, J. M. (2014). Evaluation of age-related differences in the stride-to-stride fluctuations, regularity and symmetry of gait using a waist-mounted tri-axial accelerometer. Gait & Posture, 39, 553–557. doi: 10.1016/j.gaitpost.2013.09.008.Google Scholar
Kosse, N. M., Caljouw, S., Vervoort, D., Vuillerme, N. and Lamoth, C. J. (2015). Validity and reliability of gait and postural control analysis using the tri-axial accelerometer of the ipod touch. Annals of Biomedical Engineering, 43, 1935–1946. doi: 10.1007/s10439-014-1232-0.Google Scholar
Lamoth, C. J., Beek, P. J. and Meijer, O. G. (2002). Pelvis-thorax coordination in the transverse plane during gait. Gait & Posture, 16, 101–114. doi: S0966636201001461 [pii].Google Scholar
Lamoth, C. J., van Deudekom, F. J., van Campen, J. P., Appels, B. A., de Vries, O. J. and Pijnappels, M. (2011). Gait stability and variability measures show effects of impaired cognition and dual tasking in frail people. Journal of Neuroengineering and Rehabilitation, 8, 2-0003-8-2. doi: 10.1186/1743-0003-8-2.Google Scholar
Lang, P. O., Michel, J. P. and Zekry, D. (2009). Frailty syndrome: a transitional state in a dynamic process. Gerontology, 55, 539–549. doi: 10.1159/000211949.Google Scholar
Lipsitz, L. A. (2002). Dynamics of stability: the physiologic basis of functional health and frailty. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 57, B115–125.Google Scholar
Lipsitz, L. A. and Goldberger, A. L. (1992). Loss of ‘complexity’ and aging: potential applications of fractals and chaos theory to senescence. JAMA, 267, 1806–1809. doi: 10.1001/jama.1992.03480130122036 [doi].Google Scholar
Manor, B. et al. (2010). Physiological complexity and system adaptability: evidence from postural control dynamics of older adults. Journal of Applied Physiology (Bethesda, Md.: 1985), 109, 1786–1791. doi: 10.1152/japplphysiol.00390.2010.Google Scholar
Montero-Odasso, M. et al. (2014). The motor signature of mild cognitive impairment: results from the gait and brain study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 69, 1415–1421. doi: 10.1093/gerona/glu155.Google Scholar
Qualls, C. et al. (2017). Reversible states of physical and/or cognitive dysfunction: a 9-Year longitudinal study. The Journal of Nutrition, Health & Aging, 21, 271–275. doi: 10.1007/s12603-017-0878-3 [doi].Google Scholar
Rispens, S. M., Pijnappels, M., van Schooten, K. S., Beek, P. J., Daffertshofer, A. and van Dieen, J. H. (2014). Consistency of gait characteristics as determined from acceleration data collected at different trunk locations. Gait & Posture, 40, 187–192. doi: 10.1016/j.gaitpost.2014.03.182.Google Scholar
Riva, F., Toebes, M. J., Pijnappels, M., Stagni, R. and van Dieen, J. H. (2013). Estimating fall risk with inertial sensors using gait stability measures that do not require step detection. Gait & Posture, 38, 170–174. doi: 10.1016/j.gaitpost.2013.05.002.Google Scholar
Savica, R. et al. (2017). Comparison of gait parameters for predicting cognitive decline: the mayo clinic study of aging. Journal of Alzheimer's Disease: JAD, 55, 559–567. doi: JAD160697 [pii].Google Scholar
Sleimen-Malkoun, R., Temprado, J. J. and Hong, S. L. (2014). Aging induced loss of complexity and dedifferentiation: consequences for coordination dynamics within and between brain, muscular and behavioral levels. Frontiers in Aging Neuroscience, 6, 140. doi: 10.3389/fnagi.2014.00140.Google Scholar
Studenski, S. et al. (2011). Gait speed and survival in older adults. JAMA, 305, 50–58. doi: 10.1001/jama.2010.1923.Google Scholar
van Schooten, K. S., Pijnappels, M., Rispens, S. M., Elders, P. J., Lips, P. and van Dieen, J. H. (2015). Ambulatory fall-risk assessment: amount and quality of daily-life gait predict falls in older adults. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 70, 608–615. doi: 10.1093/gerona/glu225.Google Scholar
Verghese, J., Wang, C., Lipton, R. B. and Holtzer, R. (2013). Motoric cognitive risk syndrome and the risk of dementia. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 68, 412–418.Google Scholar