The Dresden Protocol for Multidimensional Walking Assessment (DMWA) in Clinical Practice

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

Walking impairments represent one of the most debilitating symptom areas for people with multiple sclerosis (MS). It is important to detect even slightest walking impairments in order to start and optimize necessary interventions in time to counteract further progression of the disability. For this reason, a regular monitoring through gait analysis is highly necessary. At advanced stages of MS with significant walking impairment, this assessment is also necessary to optimize symptomatic treatment, choose the most suitable walking aid and plan individualized rehabilitation. In clinical practice, walking impairment is only assessed at higher levels of the disease using e.g., the Expanded Disability Status Scale (EDSS). In contrast to the EDSS, standardized functional tests such as walking speed, walking endurance and balance as well as walking quality and gait-related patient-reported outcomes allow a more holistic and sensitive assessment of walking impairment. In recent years, the MS Center Dresden has established a standardized monitoring procedure for the routine multidimensional assessment of gait and balance disorders. In the following protocol, we present the techniques and procedures for the analysis of gait and balance of people with MS at the MS Center Dresden. Patients are assessed with a multidimensional gait analysis at least once a year. This enables long-term monitoring of walking impairment, which allows early active intervention regarding further progression of disease and improves the current standard clinical practice.

Details

Original languageEnglish
Pages (from-to)582046
JournalFrontiers in neuroscience
Volume14
Publication statusPublished - 2020
Peer-reviewedYes

External IDs

PubMedCentral PMC7649388
Scopus 85095705363
ORCID /0000-0003-2465-4909/work/142236918
ORCID /0000-0001-8799-8202/work/171553353

Keywords