Modeling factors predictive of functional improvement following acute stroke

Ya Hsien Wang, Yea Ru Yang, Po Jung Pan, Ray Yau Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Background: Predicting functional improvement at an early stage after stroke is critical to setting treatment goals and strategies. The aim of this study was to identify factors that can predict motor function improvement at 3 months and 6 months poststroke. Methods: Forty-four patients with stroke were included in the study. We recorded age, interval between stroke onset and initiation of physical therapy, stroke type, history of diabetes or cardiovascular disease, functional status prior to stroke, cognition, motivation, walking ability, eating ability, hemineglect, sensory function, and brain lesion site as predictive factors. The Stroke Rehabilitation Assessment of Movement, Berg Balance Scale, Timed Up & Go Test, and the 6-Minute Walk Test were conducted upon intake and at 3 months and 6 months poststroke. Patients were assigned to a progressive group or a nonprogressive group based on their improvement in four functional measures. Variables for which there were significant group differences were used for stepwise discriminant analysis as determining factors and for setting the prediction model. Results: Patient age, history of diabetes, functional status prior to stroke, and motivation were predictive factors of functional progress at 3 months poststroke. Motivation and functional status prior to stroke predicted functional progress at 6 months poststroke. By comparing the discriminant function values of the progressive and nonprogressive groups, functional improvement can be predicted. Conclusion: Functional status prior to stroke and motivation are predictive of functional outcome at 3 months and 6 months poststroke. We have provided a formula that can be used to predict a patient's progress and then set treatment goals and programs accordingly.

Original languageEnglish
Pages (from-to)469-476
Number of pages8
JournalJournal of the Chinese Medical Association
Volume77
Issue number9
DOIs
StatePublished - 1 Sep 2014

Keywords

  • Functional improvement
  • Prediction
  • Stroke

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