Elsevier

The Lancet Neurology

Volume 9, Issue 12, December 2010, Pages 1228-1232
The Lancet Neurology

Rapid Review
Prediction of recovery of motor function after stroke

https://doi.org/10.1016/S1474-4422(10)70247-7Get rights and content

Summary

Background

Stroke is a leading cause of disability. The ability to live independently after stroke depends largely on the reduction of motor impairment and the recovery of motor function. Accurate prediction of motor recovery assists rehabilitation planning and supports realistic goal setting by clinicians and patients. Initial impairment is negatively related to degree of recovery, but inter-individual variability makes accurate prediction difficult. Neuroimaging and neurophysiological assessments can be used to measure the extent of stroke damage to the motor system and predict subsequent recovery of function, but these techniques are not yet used routinely.

Recent developments

The use of motor impairment scores and neuroimaging has been refined by two recent studies in which these investigations were used at multiple time points early after stroke. Voluntary finger extension and shoulder abduction within 5 days of stroke predicted subsequent recovery of upper-limb function. Diffusion-weighted imaging within 7 days detected the effects of stroke on caudal motor pathways and was predictive of lasting motor impairment. Thus, investigations done soon after stroke had good prognostic value. The potential prognostic value of cortical activation and neural plasticity has been explored for the first time by two recent studies. Functional MRI detected a pattern of cortical activation at the acute stage that was related to subsequent reduction in motor impairment. Transcranial magnetic stimulation enabled measurement of neural plasticity in the primary motor cortex, which was related to subsequent disability. These studies open interesting new lines of enquiry.

Where next?

The accuracy of prediction might be increased by taking into account the motor system's capacity for functional reorganisation in response to therapy, in addition to the extent of stroke-related damage. Improved prognostic accuracy could also be gained by combining simple tests of motor impairment with neuroimaging, genotyping, and neurophysiological assessment of neural plasticity. The development of algorithms to guide the sequential combinations of these assessments could also further increase accuracy, in addition to improving rehabilitation planning and outcomes.

Introduction

Stroke is the third most frequent cause of death and the most common cause of acquired adult disability in developed countries.1 Motor impairment is a frequent complication after stroke, and is an important contributory factor to a patient's ability to live independently.2 Decisions on the type, duration, and goals of rehabilitation are based on several factors, including estimates of the patient's potential for recovery of motor function, and have far-reaching consequences. Improvements in the accuracy of prognosis for the recovery of independence in daily activities would enable realistic goal-setting and efficient resource allocation by clinicians and patients.

The degree of motor impairment is the simplest indicator of prognosis, with greater initial impairment predicting worse functional recovery.3, 4 For example, voluntary shoulder and finger movements and leg motor power 7 days after stroke are strongly related to subsequent recovery of upper-limb function and gait, respectively.5, 6, 7 Notable inter-individual variability in the relation between initial impairment and subsequent recovery of function, however, means that accurate prognosis for each patient remains difficult (figure 1).8

Advances in neuroimaging with MRI and in non-invasive brain stimulation with transcranial magnetic stimulation (TMS) have provided new ways to visualise and understand the anatomical and functional changes in the motor system at given time points during the course of recovery.9, 10 Motor impairment at the subacute and chronic stages of recovery is clearly related to lesion location,11, 12, 13 the structural integrity of descending white matter pathways,14, 15 and cortical activation at rest16 and during voluntary movement.17 TMS can be used to focally stimulate the primary motor cortex (M1) and elicit motor evoked potentials (MEPs) in target muscles of the contralateral limb. The presence (and latency and amplitude) or absence of MEPs are measurements of the functional integrity and excitability of the corticomotor pathway, which are related to motor impairment at the time of testing.10 Studies of the upper limb show that ipsilesional corticomotor excitability is typically reduced after stroke, and recovery of motor function is associated with a return to balanced corticomotor excitability in the two hemispheres.18, 19 The few studies of lower-limb impairment have yielded mixed results.20, 21, 22

Use of MRI and TMS to assess the integrity of the corticomotor pathway can also assist with prediction of the patient's motor recovery.3, 23 When directly compared, the prognostic accuracy of TMS is similar to that of motor impairment assessment for the upper limb,24 and might be better when initial paresis is severe.25, 26 Assessment of the integrity of the corticomotor pathway, however, is not yet used routinely to make a prognosis, but there have been some interesting recent developments in this area.

Section snippets

Motor impairment scores

The sensitivity and specificity of voluntary finger extension and shoulder abduction as prognostic indicators have been assessed at multiple early time points by Nijland and colleagues.27 On the basis of findings in 156 patients, they reported that if both of these movements could be made within 72 h of stroke, there was a 98% probability of the patient recovering at least some manual dexterity within 6 months. If neither movement could be made within 72 h, the probability of recovering some

Neuroimaging

DeVetten and co-workers28 have recently reported the prognostic value of MRI when used at multiple early time points. In 20 patients, apparent diffusion coefficient maps were calculated from diffusion-weighted images acquired within 6 h and at 12 h, 24 h, and 7 days after stroke. Custom software was used to calculate signal intensity within regions of interest at three levels of the descending corticospinal tract, between the cervicomedullary junction and upper midbrain. These values were

Neurophysiological assessments

The prognostic accuracy of neurophysiological assessments has been extended by Di Lazzaro and colleagues,30 who used a repetitive TMS protocol to induce neural plasticity in M1 within 10 days of stroke in 17 patients. The protocol, known as intermittent theta-burst stimulation, can temporarily increase corticomotor excitability via mechanisms of synaptic plasticity.31 Intermittent theta-burst stimulation was delivered to ipsilesional M1, and a composite value of its immediate effects on the

Conclusions and future directions

The studies described above share some general limitations. First, the prognostic accuracy of the assessments was not confirmed with independent datasets. Second, the neuroimaging and neurophysiology studies did not compare the sensitivity or specificity of the new prognostic assessments with those of established clinical assessments. Finally, like most studies in this area, patients received so-called standard care, which is highly heterogeneous. Therapy type and dose are potential sources of

Search strategy and selection criteria

References for this Rapid Review were identified through searches of PubMed for articles published from January, 1980, to September, 2010. I used the terms “human”, “stroke”, “infarct”, “motor”, “prognosis”, “predict”, “rehabilitation”, and “recovery”. I also identified articles through searches of my own files. Only papers published in English were reviewed, and the final reference list was selected on the basis of originality, recency, and topical relevance.

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