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Prediction of Walking and Arm Recovery after Stroke: A Critical Review

1
Discipline of Physiotherapy, Graduate School of Health, University of Technology Sydney, Ultimo, NSW 2007, Australia
2
Neuroscience Research Australia (NeuRA), Randwick, NSW 2031, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Sheila Schindler-Ivens
Brain Sci. 2016, 6(4), 53; https://doi.org/10.3390/brainsci6040053
Received: 31 August 2016 / Revised: 27 October 2016 / Accepted: 28 October 2016 / Published: 2 November 2016
(This article belongs to the Special Issue Functional Recovery after Stroke)
Clinicians often base their predictions of walking and arm recovery on multiple predictors. Multivariate prediction models may assist clinicians to make accurate predictions. Several reviews have been published on the prediction of motor recovery after stroke, but none have critically appraised development and validation studies of models for predicting walking and arm recovery. In this review, we highlight some common methodological limitations of models that have been developed and validated. Notable models include the proportional recovery model and the PREP algorithm. We also identify five other models based on clinical predictors that might be ready for further validation. It has been suggested that neurophysiological and neuroimaging data may be used to predict arm recovery. Current evidence suggests, but does not show conclusively, that the addition of neurophysiological and neuroimaging data to models containing clinical predictors yields clinically important increases in predictive accuracy. View Full-Text
Keywords: prediction; prognosis; recovery; walking; arm function; stroke prediction; prognosis; recovery; walking; arm function; stroke
MDPI and ACS Style

Kwah, L.K.; Herbert, R.D. Prediction of Walking and Arm Recovery after Stroke: A Critical Review. Brain Sci. 2016, 6, 53.

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