Literature DB >> 30124106

Can we trust self-reported walking distance when determining EDSS scores in patients with multiple sclerosis? The Danish MS hospitals rehabilitation study.

Anders Guldhammer Skjerbæk1, Finn Boesen1, Thor Petersen2, Peter Vestergaard Rasmussen2, Egon Stenager3, Michael Nørgaard1, Peter Feys4, Marie Louise Kjeldgaard-Jørgensen5, Lars Grøndahl Hvid5, Ulrik Dalgas5.   

Abstract

BACKGROUND: In multiple sclerosis (MS), the Expanded Disability Status Scale (EDSS) reflects disease severity. Although parts of the EDSS are dependent on actual walking distance, self-reported statements are often applied.
OBJECTIVES: The purpose of the present study was, therefore, to compare self-reported walking distance to actual walking distance to outline how this influences EDSS scoring.
METHODS: MS patients with EDSS 4.0-7.5 (n = 273) were included from the Danish MS hospitals rehabilitation study (n = 427). All patients subjectively classified their maximal walking distance according to one of seven categories (>500; 300-499; 200-299; 100-199; 20-99; 5-19; 0-4 m). Subsequently, actual maximal walking distance was assessed and EDSS was determined from both self-reported walking distance (EDSSself-report) and actual walking distance (EDSSactual).
RESULTS: In 145 patients (53%), self-reported walking distance was misclassified when compared to the actual walking distance. Misclassification was more frequent in patients using walking aids (64% vs. 44%, p < 0.05) and in patients with primary progressive MS (69%, p < 0.05). Misclassification of walking distance corresponded to incorrect EDSS scores (EDSSself-report vs EDSSactual) of ⩾0.5 point in 24%.
CONCLUSION: In MS patients with EDSS 4.0-7.5, 53% misclassified their walking distance yielding incorrect EDSS scores in 24%. Therefore, correct EDSS determination must be based on measurement of actual walking distance.

Entities:  

Keywords:  EDSS; Expanded Disability Status Scale; Outcome measurement; Walking; multiple sclerosis; primary progressive MS

Mesh:

Year:  2018        PMID: 30124106     DOI: 10.1177/1352458518795416

Source DB:  PubMed          Journal:  Mult Scler        ISSN: 1352-4585            Impact factor:   6.312


  4 in total

1.  The feasibility of assessing cognitive and motor function in multiple sclerosis patients using robotics.

Authors:  Leif Er Simmatis; Albert Y Jin; Sean W Taylor; Etienne J Bisson; Stephen H Scott; Moogeh Baharnoori
Journal:  Mult Scler J Exp Transl Clin       Date:  2020-10-15

2.  Comparison of Self-Reported vs Objective Measures of Long-Term Community Ambulation in Lower Limb Prosthesis Users.

Authors:  Bradeigh Godfrey; Christopher Duncan; Teri Rosenbaum-Chou
Journal:  Arch Rehabil Res Clin Transl       Date:  2022-07-28

3.  Early use of high-efficacy disease‑modifying therapies makes the difference in people with multiple sclerosis: an expert opinion.

Authors:  Massimo Filippi; Maria Pia Amato; Diego Centonze; Paolo Gallo; Claudio Gasperini; Matilde Inglese; Francesco Patti; Carlo Pozzilli; Paolo Preziosa; Maria Trojano
Journal:  J Neurol       Date:  2022-05-24       Impact factor: 6.682

4.  Disability assessment using Google Maps.

Authors:  Luigi Lavorgna; Pietro Iaffaldano; Gianmarco Abbadessa; Roberta Lanzillo; Sabrina Esposito; Domenico Ippolito; Maddalena Sparaco; Simone Cepparulo; Giacomo Lus; Rosa Viterbo; Marinella Clerico; Francesca Trojsi; Paolo Ragonese; Giovanna Borriello; Elisabetta Signoriello; Raffaele Palladino; Marcello Moccia; Francesco Brigo; Maria Troiano; Gioacchino Tedeschi; Simona Bonavita
Journal:  Neurol Sci       Date:  2021-06-17       Impact factor: 3.307

  4 in total

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