Skip to main content

Walking function in clinical monitoring of multiple sclerosis by telemedicine

Abstract

Walking limitation is a key component of disability in patients with multiple sclerosis (MS), but the information on daily walking activity and disability over time is limited. To determine, (1) the agreement between the standard measurements of MS-related disability [expanded disability status scale (EDSS), functional systems (FS) and ambulation index (AI)] obtained by conventional and remote evaluation using a multimedia platform; (2) the usefulness of monitoring 6-min walk test (6MWT) and average daily walking activity (aDWA) to better characterize patients disability. Twenty-five patients (EDSS score 1.0–6.5) were evaluated every 3 months for the first year, and aDWA repeated at year 2. Remote visits included the recording of a video with self-performed neurological examination and specific multimedia questionnaires. aDWA was measured by a triaxial accelerometer. All but two patients completed the study. Modest agreement between conventional and multimedia EDSS was found for EDSS ≤ 4.0 (kappa = 0.2) and good for EDSS ≥ 4.5 (kappa = 0.6). For the overall sample, pyramidal, cerebellar and brainstem FS showed the greatest agreement (kappa = 0.7). SR-AI showed a modest agreement for EDSS ≤ 4.0 and good for EDSS ≥ 4.5 (kappa = 0.3 and 0.6, respectively). There was a strong correlation between conventional and 6MWT measured by accelerometer (r = 0.76). The aDWA correlated strongly with the EDSS (r = −0.86) and a cut-off point of 3279.3 steps/day discriminated patients with ambulatory impairment. There was a significant decline in aDWA over 2 years in patients with ambulatory impairment that were not observed by standard measurements of disability. MS clinical monitoring by telemedicine is feasible, but the observed lower agreement in less disabled patients emphasizes the need to optimize the assessment methodology. Accelerometers capture changes that may indicate deterioration over time.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

References

  1. Porter B, Thompson A (2012) Connecting to the future––the promise of telecare. Mult Scler 18:384–386. doi:10.1177/1352458512441273

    Article  PubMed  Google Scholar 

  2. Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an Expanded Disability Status Scale (EDSS). Neurology 33:1444–1452

    CAS  Article  PubMed  Google Scholar 

  3. Meyer-Moock S, Feng YS, Maeurer M, Dippel FW, Kohlmann T (2014) Systematic literature review and validity evaluation of the Expanded Disability Status Scale (EDSS) and the multiple sclerosis functional composite (MSFC) in patients with multiple sclerosis. BMC Neurol 14:58. doi:10.1186/1471-2377-14-58

    PubMed Central  Article  PubMed  Google Scholar 

  4. Polman CH, Rudick RA (2010) The multiple sclerosis functional composite: a clinically meaningful measure of disability. Neurology 74(Suppl 3):S8–S15. doi:10.1212/WNL.0b013e3181dbb571

    Article  PubMed  Google Scholar 

  5. Larocca NG (2011) Impact of walking impairment in multiple sclerosis: perspectives of patients and care partners. Patient 4:189–201. doi:10.2165/11591150-000000000-00000

    Article  PubMed  Google Scholar 

  6. Motl RW, Snook EM, Agiovlasitis S (2011) Does an accelerometer accurately measure steps taken under controlled conditions in adults with mild multiple sclerosis? Disabil Health J 4:52–57. doi:10.1016/j.dhjo.2010.02.003

    Article  PubMed  Google Scholar 

  7. Motl RW, Pilutti LA, Learmonth YC, Goldman MD, Brown T (2013) Clinical importance of steps taken per day among persons with multiple sclerosis. PLoS One 8:e73247. doi:10.1371/journal.pone.0073247

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  8. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, Fujihara K, Havrdova E, Hutchinson M, Kappos L, Lublin FD, Montalban X, O’Connor P, Sandberg-Wollheim M, Thompson AJ, Waubant E, Weinshenker B, Wolinsky JS (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69:292–302. doi:10.1002/ana.22366

    PubMed Central  Article  PubMed  Google Scholar 

  9. Fischer JS, Rudick RA, Cutter GR, Reingold SC (1999) The multiple sclerosis functional composite measure (MSFC): an integrated approach to MS clinical outcome assessment. National MS Society Clinical Outcomes Assessment Task Force. Mult Scler 5:244–250

    CAS  Article  PubMed  Google Scholar 

  10. Goldman MD, Marrie RA, Cohen JA (2008) Evaluation of the 6-min walk in multiple sclerosis subjects and healthy controls. Mult Scler 14:383–390

    Article  PubMed  Google Scholar 

  11. Kappos L (2011) Neurostatus training. http://www.neurostatus.net/training/index.php. Accessed 26 June 2012

  12. Fernández O, Fernández V, Baumstarck-Barrau K, Muñoz L, Gonzalez Alvarez Mdel M, Arrabal JC, León A, Alonso A, López-Madrona JC, Bustamante R, Luque G, Guerrero M, di Cantogno EV, Auquier P, MusiQoL study group of Spain (2011) Validation of the spanish version of the Multiple Sclerosis International Quality of Life (Musiqol) questionnaire. BMC Neurol 11:127. doi:10.1186/1471-2377-11-127

    PubMed Central  Article  PubMed  Google Scholar 

  13. Lechner-Scott J, Kappos L, Hofman M, Polman CH, Ronner H, Montalban X, Tintore M, Frontoni M, Buttinelli C, Amato MP, Bartolozzi ML, Versavel M, Dahlke F, Kapp JF, Gibberd R (2003) Can the Expanded Disability Status Scale be assessed by telephone? Mult Scler 9:154–159

    CAS  Article  PubMed  Google Scholar 

  14. EuroQol Group (1990) EuroQol—a new facility for the measurement of health-related quality of life. Health Policy 16:199–208

    Article  Google Scholar 

  15. Oldfield RC (1971) The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9:97–113

    CAS  Article  PubMed  Google Scholar 

  16. 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 127:384–390. doi:10.1111/ane.12036

    CAS  Article  PubMed  Google Scholar 

  17. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174

    CAS  Article  PubMed  Google Scholar 

  18. Dancey C, Reidy J (2004) Statistics without maths for psychology: using SPSS for windows, 5th edn. Prentice Hall, London, pp 168–212

    Google Scholar 

  19. Goodkin DE (1991) EDSS reliability. Neurology 41:332

    CAS  Article  PubMed  Google Scholar 

  20. Rudick RA, Polman CH, Cohen JA, Walton MK, Miller AE, Confavreux C, Lublin FD, Hutchinson M, O’Connor PW, Schwid SR, Balcer LJ, Lynn F, Panzara MA, Sandrock AW (2009) Assessing disability progression with the multiple sclerosis functional composite. Mult Scler 15:984–997. doi:10.1177/1352458509106212

    CAS  Article  PubMed  Google Scholar 

  21. Amato MP, Fratiglioni L, Groppi C, Siracusa G, Amaducci L (1988) Interrater reliability in assessing functional systems and disability on the Kurtzke Scale in multiple sclerosis. Arch Neurol 45:746–748

    CAS  Article  PubMed  Google Scholar 

  22. Francis DA, Bain P, Swan AV, Hughes RA (1991) An assessment of disability rating scales used in multiple sclerosis. Arch Neurol 48:299–301

    CAS  Article  PubMed  Google Scholar 

  23. Verdier-Taillefer MH, Zuber M, Lyon-Caen O, Clanet M, Gout O, Louis C, Alpérovitch A (1991) Observer disagreement in rating neurologic impairment in multiple sclerosis: facts and consequences. Eur Neurol 31:117–119

    CAS  Article  PubMed  Google Scholar 

  24. Noseworthy JH, Vandervoort MK, Wong CJ, Ebers GC (1990) Interrater variability with the Expanded Disability Status Scale (EDSS) and functional systems (FS) in a multiple sclerosis clinical trial. The Canadian Cooperation MS Study Group. Neurology 40:971–975

    CAS  Article  PubMed  Google Scholar 

  25. Sharrack B, Hughes RA, Soudain S, Dunn G (1999) The psychometric properties of clinical rating scales used in multiple sclerosis. Brain 122(Pt 1):141–159

    Article  PubMed  Google Scholar 

  26. Hobart J, Freeman J, Thompson A (2000) Kurtzke Scales revisited: the application of psychometric methods to clinical intuition. Brain 123(Pt 5):1027–1040

    Article  PubMed  Google Scholar 

  27. Sharrack B, Hughes RA (1997) Reliability of distance estimation by doctors and patients: cross sectional study. BMJ 315:1652–1654

    PubMed Central  CAS  Article  PubMed  Google Scholar 

  28. Gijbels D, Alders G, Van Hoof E, Charlier C, Roelants M, Broekmans T, Eijnde BO, Feys P (2010) Predicting habitual walking performance in multiple sclerosis: relevance of capacity and self-report measures. Mult Scler 16:618–626. doi:10.1177/1352458510361357

    Article  PubMed  Google Scholar 

  29. Motl RW, Dlugonski D, Suh Y, Weikert M, Fernhall B, Goldman M (2010) Accelerometry and its association with objective markers of walking limitations in ambulatory adults with multiple sclerosis. Arch Phys Med Rehabil 91:1942–1947. doi:10.1016/j.apmr.2010.08.011

    PubMed Central  Article  PubMed  Google Scholar 

  30. Dlugonski D, Pilutti LA, Sandroff BM, Suh Y, Balantrapu S, Motl RW (2013) Steps per day among persons with multiple sclerosis: variation by demographic, clinical, and device characteristics. Arch Phys Med Rehabil 94:1534–1539. doi:10.1016/j.apmr.2012.12.014

    Article  PubMed  Google Scholar 

  31. Shammas L, Zentek T, von Haaren B, Schlesinger S, Hey S, Rashid A (2014) Home-based system for physical activity monitoring in patients with multiple sclerosis (Pilot study). Biomed Eng Online 13:10. doi:10.1186/1475-925X-13-10

    PubMed Central  Article  PubMed  Google Scholar 

  32. Learmonth YC, Dlugonski DD, Pilutti LA, Sandroff BM, Motl RW (2013) The reliability, precision and clinically meaningful change of walking assessments in multiple sclerosis. Mult Scler 19:1784–1791. doi:10.1177/1352458513483890

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

Núria Solà-Valls received an award from Hospital Clínic of Barcelona in 2012 (Emili Letang award). The authors thank the “Associació Esclerosi Múltiple Illa de Menorca” for their contribution in the study, Montserrat Artola for her excellent technical support and Erika Lampert for her help in English and linguistic corrections. We also want to express our gratitude to all patients who freely accepted to participate in this study.

Conflicts of interest

Núria Sola-Valls, Yolanda Blanco, Maria Sepúlveda, Sara Llufriu, Elena H Martínez-Lapiscina, Delon La Puma and Francesc Graus declare that there is no conflict of interest. Pablo Villoslada has received consultation fees from Roche, Novartis, Neurotech Pharma and is founder and hold stocks of Bionure Farma. Albert Saiz has received compensation for consulting services and speaking from Bayer-Schering, Merck-Serono, Biogen-Idec, Sanofi-Aventis, Teva Pharmaceutical Industries Ltd and Novartis.

Ethical standards

All participants provided their written informed consent prior to their inclusion in the study. This clinical study was approved by the ethical committee of the Hospital Clinic of Barcelona and therefore performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yolanda Blanco.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Sola-Valls, N., Blanco, Y., Sepúlveda, M. et al. Walking function in clinical monitoring of multiple sclerosis by telemedicine. J Neurol 262, 1706–1713 (2015). https://doi.org/10.1007/s00415-015-7764-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00415-015-7764-x

Keywords

  • Multiple sclerosis
  • Telemedicine
  • Disability progression
  • Accelerometer
  • Daily walking activity