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Stroke. 2005 Jun;36(6):1172-7. Epub 2005 May 12.

Active finger extension predicts outcomes after constraint-induced movement therapy for individuals with hemiparesis after stroke.

Author information

  • 1Brain Rehabilitation Research Center, Gainesville, Florida, USA. sfritz@gwm.sc.edu

Abstract

BACKGROUND AND PURPOSE:

Constraint-induced movement therapy (CIMT) is a rehabilitative strategy used primarily with the post-stroke population to increase the functional use of the neurologically weaker upper extremity through massed practice while restraining the lesser involved upper extremity. Whereas research evidence supports CIMT, limited evidence exists regarding the characteristics of individuals who benefit most from this intervention. The goal of this study was to investigate the potential of 5 measures to predict functional CIMT outcomes.

METHODS:

A convenience sample of 55 individuals, >6 months after stroke, was recruited that met specific inclusion/exclusion criteria allowing for individuals whose upper extremity was mildly to severely involved. They participated in CIMT 6 hours per day. Pretest, post-test, and follow-up assessments were performed to assess the outcomes for the Wolf Motor Function Test (WMFT). The potential predictors were minimal motor criteria (active extension of the wrist and 3 fingers), active finger extension/grasp release, grip strength, Fugl-Meyer upper extremity motor score, and the Frenchay score. A step-wise regression analysis was used in which the potential predictors were entered in a linear regression model with simultaneous entry of the dependent variables' pretest score as the covariate. Two regressions models were determined for the dependent variable, for immediate post-test, and for follow-up post-test.

RESULTS:

Finger extension was the only significant predictor of WMFT outcomes.

CONCLUSIONS:

When using finger extension/grasp release as a predictor in the regression equations, one can predict individual's follow-up scores for CIMT. This experiment provides the most comprehensive investigation of predictors of CIMT outcomes to date.

PMID:
15890987
[PubMed - indexed for MEDLINE]
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