Prediction of Walking and Arm Recovery after Stroke: A Critical Review
AbstractClinicians 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
Share & Cite This Article
Kwah, L.K.; Herbert, R.D. Prediction of Walking and Arm Recovery after Stroke: A Critical Review. Brain Sci. 2016, 6, 53.
Kwah LK, Herbert RD. Prediction of Walking and Arm Recovery after Stroke: A Critical Review. Brain Sciences. 2016; 6(4):53.Chicago/Turabian Style
Kwah, Li K.; Herbert, Robert D. 2016. "Prediction of Walking and Arm Recovery after Stroke: A Critical Review." Brain Sci. 6, no. 4: 53.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.