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. 2000 Mar;68(3):323-31.
doi: 10.1136/jnnp.68.3.323.

Value of somatosensory and motor evoked potentials in predicting arm recovery after a stroke

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Value of somatosensory and motor evoked potentials in predicting arm recovery after a stroke

H Feys et al. J Neurol Neurosurg Psychiatry. 2000 Mar.

Abstract

Objectives: Prediction of motor recovery in the arm in patients with stroke is generally based on clinical examination. However, neurophysiological measures may also have a predictive value. The aims of this study were to assess the role of somatosensory (SSEPs) and motor (MEPs) evoked potentials in the prediction of arm motor recovery and to determine whether these measures added further predictive information to that gained from clinical examination.

Methods: Sixty four patients who had had a stroke and presented with obvious motor deficit of the arm were examined in terms of three clinical variables (motor performance, muscle tone, and overall disability) and for SSEPs and MEPs. Clinical and neurophysiological examinations were done at entry to the study (2 to 5 weeks poststroke), and at about 2 months after stroke. Further clinical follow up was conducted at 6 and 12 months after stroke.

Results: Neurophysiological measures made in the acute phase were of little use alone in predicting motor recovery of the arm at 2, 6, and 12 months after stroke. At 2 months, the absence of SSEPs and MEPs indicated a very poor outcome. Conversely, if the responses were preserved, a great variation in motor outcome was found. Multiple regression analysis showed that the addition of SSEPs and MEPs to the clinical examination increased the possibility of predicting arm recovery in the long term. In the acute phase, the combination of the motor score and SSEPs were best able to predict outcome. The long term outcome based on variables taken at 2 months, was best predicted through incorporating the three clinical measures and MEPs.

Conclusions: Neurophysiological measures alone are of limited value in predicting long term outcome. However, predictive accuracy is substantially improved through the combined use of both of these measures and clinical variables.

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