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BMC Neurol ; 20(1): 263, 2020 Jul 01.
Article in English | MEDLINE | ID: mdl-32611393

ABSTRACT

BACKGROUND: Level of dependency after a stroke is important for long-term outcome in several aspects, but less is known about important predictors for outcome depending on functional dependency. The aim of the current study was to investigate self-perceived outcome and identify possible predictors of strength, participation, and emotional outcome 5 years after stroke based on functional dependency at discharge from hospital. METHODS: This observational cohort study included participants living in Gothenburg that were diagnosed with first ever stroke in 2009 and 2010. Baseline data were gathered from medical charts and the outcome was based on the Stroke Impact Scale (SIS) questionnaire mailed out 5 years post-stroke. Logistic regression identified potential predictors of better strength, participation, and emotional outcome. RESULTS: A total of 266 participants responded to the SIS. The functionally independent participants at hospital discharge reported significantly better scores in all SIS domains compared to the functionally dependent. For those who were functionally independent, only non-modifiable factors (age, sex, stroke type) were significant predictors of a better outcome. However, for the functionally dependent participants, modifiable factors such as feeling depressed, cardiovascular risk factors, and recurrent stroke were significant predictors of unfavourable outcome. CONCLUSIONS: Important factors for predicting a favourable outcome differed due to the level of functional dependency, and modifiable factors were only present in participants that were functionally dependent at discharge. Prevention, detection, and treatment of modifiable factors give an opportunity to reduce the burden of stroke for those who are most vulnerable.


Subject(s)
Self Concept , Stroke Rehabilitation , Stroke/physiopathology , Aged , Aged, 80 and over , Cohort Studies , Emotions , Female , Follow-Up Studies , Humans , Logistic Models , Male , Middle Aged , Patient Discharge , Surveys and Questionnaires
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