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Gait rehabilitation after stroke: review of the evidence of predictors, clinical outcomes and timing for interventions

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Abstract

The recovery of walking capacity is one of the main aims in stroke rehabilitation. Being able to predict if and when a patient is going to walk after stroke is of major interest in terms of management of the patients and their family’s expectations and in terms of discharge destination and timing previsions. This article reviews the recent literature regarding the predictive factors for gait recovery and the best recommendations in terms of gait rehabilitation in stroke patients. Trunk control and lower limb motor control (e.g. hip extensor muscle force) seem to be the best predictors of gait recovery as shown by the TWIST algorithm, which is a simple tool that can be applied in clinical practice at 1 week post-stroke. In terms of walking performance, the 6-min walking test is the best predictor of community ambulation. Various techniques are available for gait rehabilitation, including treadmill training with or without body weight support, robotic-assisted therapy, virtual reality, circuit class training and self-rehabilitation programmes. These techniques should be applied at specific timing during post-stroke rehabilitation, according to patient’s functional status.

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Authors and Affiliations

  1. Service de Médecine Physique et Réadaptation, Cliniques universitaires Saint-Luc, Avenue Hippocrate 10, 1200, Brussels, Belgium

    Clara Selves, Gaëtan Stoquart & Thierry Lejeune

  2. Secteur des Sciences de la Santé, Institut de Recherche Expérimentale et Clinique (IREC), Neuro Musculo Skeletal Lab (NMSK), Université catholique de Louvain, Avenue Mounier 53, 1200, Brussels, Belgium

    Clara Selves, Gaëtan Stoquart & Thierry Lejeune

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  1. Clara Selves
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  2. Gaëtan Stoquart
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  3. Thierry Lejeune
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Correspondence to Clara Selves.

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Selves, C., Stoquart, G. & Lejeune, T. Gait rehabilitation after stroke: review of the evidence of predictors, clinical outcomes and timing for interventions. Acta Neurol Belg 120, 783–790 (2020). https://doi.org/10.1007/s13760-020-01320-7

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