Advertisement

Deterioration of specific aspects of gait during the instrumented 6-min walk test among people with multiple sclerosis

  • S. Shema-Shiratzky
  • E. Gazit
  • R. Sun
  • K. Regev
  • A. Karni
  • J. J. Sosnoff
  • T. Herman
  • A. Mirelman
  • Jeffrey M. HausdorffEmail author
Original Communication

Abstract

Prolonged walking is typically impaired among people with multiple sclerosis (pwMS), however, it is unclear what the contributing factors are or how to evaluate this deterioration. We aimed to determine which gait features become worse during sustained walking and to examine the clinical correlates of gait fatigability in pwMS. Fifty-eight pwMS performed the 6-min walk test while wearing body-fixed sensors. Multiple gait domains (e.g., pace, rhythm, variability, asymmetry and complexity) were compared across each minute of the test and between mild- and moderate-disability patient groups. Associations between the decline in gait performance (i.e., gait fatigability) and patient-reported gait disability, fatigue and falls were also determined. Cadence, stride time variability, stride regularity, step regularity and gait complexity significantly deteriorated during the test. In contrast, somewhat surprisingly, gait speed and swing time asymmetry did not change. As expected, subjects with moderate disability (n = 24) walked more poorly in most gait domains compared to the mild-disability group (n = 34). Interestingly, a group × fatigue interaction effect was observed for cadence and gait complexity; these measures decreased over time in the moderate-disability group, but not in the mild group. Gait fatigability rate was significantly correlated with physical fatigue, gait disability, and fall history. These findings suggest that sustained walking affects specific aspects of gait, which can be used as markers for fatigability in MS. This effect on gait depends on the degree of disability, and may increase fall risk in pwMS. To more fully understand and monitor correlates that reflect everyday walking in pwMS, multiple domains of gait should be quantified.

Keywords

Multiple sclerosis Gait Fatigability Fatigue Fall risk Walking disability Wearables Body-fixed-sensor Accelerometer 

Notes

Acknowledgments

We thank the study participants for their time and contribution to this research. This work was supported in part by a Grant for the National Multiple Sclerosis Society (RG-1507-05433).

Compliance with ethical standards

Conflicts of interest

All authors declare that they have no conflict of interest.

Ethical approval

This study was conducted in accordance with the standards and approved by local human study committees, and has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. All subjects provided informed written consent prior to their inclusion in the study.

Reference

  1. 1.
    Motl RW (2013) Ambulation and multiple sclerosis. Phys Med Rehabil Clin N Am 24:325–336CrossRefGoogle Scholar
  2. 2.
    Bouchard V, Duquette P, Mayo NE (2017) Path to illness intrusiveness: what symptoms affect the life of people living with multiple sclerosis? Arch Phys Med Rehabil 98:1357–1365CrossRefGoogle Scholar
  3. 3.
    Barin L, Salmen A, Disanto G, Babacic H, Calabrese P, Chan A, Kamm CP, Kesselring J, Kuhle J, Gobbi C, Pot C, Puhan MA, von Wyl V (2018) The disease burden of multiple sclerosis from the individual and population perspective: which symptoms matter most? Mult Scler Relat Disord 25:112–121CrossRefGoogle Scholar
  4. 4.
    Stellmann JP, Neuhaus A, Gotze N, Briken S, Lederer C, Schimpl M, Heesen C, Daumer M (2015) Ecological validity of walking capacity tests in multiple sclerosis. PLoS ONE 10:e0123822CrossRefGoogle Scholar
  5. 5.
    Motl RW, Pilutti L, Sandroff BM, Dlugonski D, Sosnoff JJ, Pula JH (2013) Accelerometry as a measure of walking behavior in multiple sclerosis. Acta Neurol Scand 127:384–390CrossRefGoogle Scholar
  6. 6.
    Kieseier BC, Pozzilli C (2012) Assessing walking disability in multiple sclerosis. Mult Scler 18:914–924CrossRefGoogle Scholar
  7. 7.
    Goldman MD, Marrie RA, Cohen JA (2008) Evaluation of the six-minute walk in multiple sclerosis subjects and healthy controls. Mult Scler 14:383–390CrossRefGoogle Scholar
  8. 8.
    Butland RJ, Pang J, Gross ER, Woodcock AA, Geddes DM (1982) Two-, six-, and 12-minute walking tests in respiratory disease. Br Med J (Clin Res Ed) 284:1607–1608CrossRefGoogle Scholar
  9. 9.
    Sandroff BM, Pilutti LA, Motl RW (2015) Does the six-minute walk test measure walking performance or physical fitness in persons with multiple sclerosis? NeuroRehabilitation 37:149–155CrossRefGoogle Scholar
  10. 10.
    Pilutti LA, Dlugonski D, Sandroff BM, Suh Y, Pula JH, Sosnoff JJ, Motl RW (2013) Gait and six-minute walk performance in persons with multiple sclerosis. J Neurol Sci 334:72–76CrossRefGoogle Scholar
  11. 11.
    Burschka JM, Keune PM, Menge U, Hofstadt-van OU, Oschmann P, Hoos O (2012) An exploration of impaired walking dynamics and fatigue in multiple sclerosis. BMC Neurol 12:161CrossRefGoogle Scholar
  12. 12.
    Kluger BM, Krupp LB, Enoka RM (2013) Fatigue and fatigability in neurologic illnesses: proposal for a unified taxonomy. Neurology 80:409–416CrossRefGoogle Scholar
  13. 13.
    Lord S, Galna B, Rochester L (2013) Moving forward on gait measurement: toward a more refined approach. Mov Disord 28:1534–1543CrossRefGoogle Scholar
  14. 14.
    van der Linden ML, Andreopoulou G, Scopes J, Hooper JE, Mercer TH (2018) Ankle kinematics and temporal gait characteristics over the duration of a 6-minute walk test in people with multiple sclerosis who experience foot Drop. Rehabil Res Pract 2018:1260852Google Scholar
  15. 15.
    Socie MJ, Motl RW, Sosnoff JJ (2014) Examination of spatiotemporal gait parameters during the 6-min walk in individuals with multiple sclerosis. Int J Rehabil Res 37:311–316CrossRefGoogle Scholar
  16. 16.
    Engelhard MM, Dandu SR, Patek SD, Lach JC, Goldman MD (2016) Quantifying six-minute walk induced gait deterioration with inertial sensors in multiple sclerosis subjects. Gait Posture 49:340–345CrossRefGoogle Scholar
  17. 17.
    Motl RW, Suh Y, Balantrapu S, Sandroff BM, Sosnoff JJ, Pula J, Goldman MD, Fernhall B (2012) Evidence for the different physiological significance of the 6- and 2-minute walk tests in multiple sclerosis. BMC Neurol 12:6CrossRefGoogle Scholar
  18. 18.
    Qureshi A, Brandt-Pearce M, Goldman MD (2016) Relationship between gait variables and domains of neurologic dysfunction in multiple sclerosis using six-minute walk test. Conf Proc IEEE Eng Med Biol Soc 2016:4959–4962Google Scholar
  19. 19.
    ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories (2002) ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med 166: 111–117Google Scholar
  20. 20.
    Kos D, Kerckhofs E, Carrea I, Verza R, Ramos M, Jansa J (2005) Evaluation of the modified fatigue impact scale in four different European countries. Mult Scler 11:76–80CrossRefGoogle Scholar
  21. 21.
    Hobart JC, Riazi A, Lamping DL, Fitzpatrick R, Thompson AJ (2003) Measuring the impact of MS on walking ability: the 12-Item MS Walking Scale (MSWS-12). Neurology 60:31–36CrossRefGoogle Scholar
  22. 22.
    Hausdorff JM, Rios DA, Edelberg HK (2001) Gait variability and fall risk in community-living older adults: a 1-year prospective study. Arch Phys Med Rehabil 82:1050–1056CrossRefGoogle Scholar
  23. 23.
    Herman T, Weiss A, Brozgol M, Giladi N, Hausdorff JM (2014) Gait and balance in Parkinson's disease subtypes: objective measures and classification considerations. J Neurol 261:2401–2410CrossRefGoogle Scholar
  24. 24.
    Weiss A, Brozgol M, Dorfman M, Herman T, Shema S, Giladi N, Hausdorff JM (2013) Does the evaluation of gait quality during daily life provide insight into fall risk? A novel approach using 3-day accelerometer recordings. Neurorehabil Neural Repair 27:742–752CrossRefGoogle Scholar
  25. 25.
    Weiss A, Herman T, Giladi N, Hausdorff JM (2014) Objective assessment of fall risk in Parkinson's disease using a body-fixed sensor worn for 3 days. PLoS ONE 9:e96675CrossRefGoogle Scholar
  26. 26.
    Kalron A (2016) Gait variability across the disability spectrum in people with multiple sclerosis. J Neurol Sci 361:1–6CrossRefGoogle Scholar
  27. 27.
    Moe-Nilssen R, Helbostad JL (2004) Estimation of gait cycle characteristics by trunk accelerometry. J Biomech 37:121–126CrossRefGoogle Scholar
  28. 28.
    Moe-Nilssen R, Aaslund MK, Hodt-Billington C, Helbostad JL (2010) Gait variability measures may represent different constructs. Gait Posture 32:98–101CrossRefGoogle Scholar
  29. 29.
    Kobayashi H, Kakihana W, Kimura T (2014) Combined effects of age and gender on gait symmetry and regularity assessed by autocorrelation of trunk acceleration. J Neuroeng Rehabil 11:109CrossRefGoogle Scholar
  30. 30.
    Kobsar D, Olson C, Paranjape R, Hadjistavropoulos T, Barden JM (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 39:553–557CrossRefGoogle Scholar
  31. 31.
    Yogev G, Plotnik M, Peretz C, Giladi N, Hausdorff JM (2007) Gait asymmetry in patients with Parkinson's disease and elderly fallers: when does the bilateral coordination of gait require attention? Exp Brain Res 177:336–346CrossRefGoogle Scholar
  32. 32.
    Costa M, Peng CK, Goldberger AL, Hausdorff JM (2003) Multiscale entropy analysis of human gait dynamics. Phys A 330:53–60CrossRefGoogle Scholar
  33. 33.
    Ihlen EAF, Weiss A, Bourke A, Helbostad JL, Hausdorff JM (2016) The complexity of daily life walking in older adult community-dwelling fallers and non-fallers. J Biomech 49:1420–1428CrossRefGoogle Scholar
  34. 34.
    Bautmans I, Jansen B, Van KB, Mets T (2011) Reliability and clinical correlates of 3D-accelerometry based gait analysis outcomes according to age and fall-risk. Gait Posture 33:366–372CrossRefGoogle Scholar
  35. 35.
    Mazumder R, Murchison C, Bourdette D, Cameron M (2014) Falls in people with multiple sclerosis compared with falls in healthy controls. PLoS ONEne 9:e107620CrossRefGoogle Scholar
  36. 36.
    Block VA, Pitsch E, Tahir P, Cree BA, Allen DD, Gelfand JM (2016) Remote physical activity monitoring in neurological disease: a systematic review. PLoS ONE 11:e0154335CrossRefGoogle Scholar
  37. 37.
    Tochigi Y, Segal NA, Vaseenon T, Brown TD (2012) Entropy analysis of tri-axial leg acceleration signal waveforms for measurement of decrease of physiological variability in human gait. J Orthop Res 30:897–904CrossRefGoogle Scholar
  38. 38.
    Warlop T, Detrembleur C, Stoquart G, Lejeune T, Jeanjean A (2018) Gait complexity and regularity are differently modulated by treadmill walking in Parkinson's disease and healthy population. Front Physiol 9:68CrossRefGoogle Scholar
  39. 39.
    Loy BD, Taylor RL, Fling BW, Horak FB (2017) Relationship between perceived fatigue and performance fatigability in people with multiple sclerosis: a systematic review and meta-analysis. J Psychosom Res 100:1–7CrossRefGoogle Scholar
  40. 40.
    Motl RW, Cohen JA, Benedict R, Phillips G, LaRocca N, Hudson LD, Rudick R (2017) Validity of the timed 25-foot walk as an ambulatory performance outcome measure for multiple sclerosis. Mult Scler 23:704–710CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Center for the Study of Movement, Cognition and MobilityTel Aviv Sourasky Medical CenterTel AvivIsrael
  2. 2.Motor Control Research Laboratory, Department of Kinesiology and Community HealthUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  3. 3.Neuroimmunology and Multiple Sclerosis Unit of the Department of NeurologyTel Aviv Sourasky Medical CenterTel AvivIsrael
  4. 4.Sagol School of NeuroscienceTel Aviv UniversityTel AvivIsrael
  5. 5.Department of Neurology, Sackler Faculty of MedicineTel Aviv UniversityTel AvivIsrael
  6. 6.Department of Physiotherapy, Sackler Faculty of MedicineTel Aviv UniversityTel AvivIsrael
  7. 7.Rush Alzheimer’s Disease Center and Department of Orthopaedic SurgeryRush University Medical CenterChicagoUSA

Personalised recommendations