An update on predicting motor recovery after stroke

What the fuck good does prediction of non-recovery do? Do you tell your patients you have nothing that will get them 100% recovered? Or will you be like my doctor and know nothing and tell nothing about stroke?

 

An update on predicting motor recovery after stroke

 

Author links open overlay panelC.M.Stinear^ab

¹

W.D.Byblow^bc1S.H.Ward^c

^a

Clinical Neuroscience Laboratory, Department of Medicine, University of Auckland, Private Bag, 92019 Auckland, New Zealand

^b

Centre for Brain Research, University of Auckland, Private Bag, 92019 Auckland, New Zealand

^c

Movement Neuroscience Laboratory, Department of Sport and Exercise Science, University of Auckland, Private Bag, 92019 Auckland, New Zealand

Received 9 August 2014, Accepted 9 August 2014, Available online 27 August 2014.

https://doi.org/10.1016/j.rehab.2014.08.006Get rights and content

Under a Creative Commons license

open access

Abstract

Being able to predict an individual's potential for recovery of motor function after stroke may facilitate the use of more effective targeted rehabilitation strategies, and management of patient expectations and goals. This review summarises developments since 2010 of approaches based on clinical, neurophysiological and neuroimaging measures for predicting individual patients’ potential for upper limb recovery. Clinical assessments alone have low prognostic accuracy. Transcranial magnetic stimulation can be used to assess the functional integrity of the corticomotor pathway, and has some predictive value but is not superior when used in isolation due to its low negative predictive value. Neuroimaging measures can be used to assess the structural integrity of descending white matter tracts. Recent studies indicate that the integrity of corticospinal and alternate motor tracts in both hemispheres may be useful predictors of motor recovery after stroke. The PREP algorithm is currently the only sequential algorithm that combines clinical, neurophysiological and neuroimaging measures at the sub-acute stage to predict the potential for subsequent recovery of upper limb function. Future research could determine if a similar algorithmic approach may be useful for predicting the recovery of gait after stroke.