Principles of proportional recovery after stroke generalize to neglect and aphasia
| Autor: | N. A. Marchi, Adrian G. Guggisberg, Radek Ptak, M. Di Pietro, Armin Schnider |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Male
030506 rehabilitation medicine.medical_specialty medicine.medical_treatment media_common.quotation_subject Neglect Perceptual Disorders 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation Aphasia Linear regression Humans Medicine Stroke Aged media_common Rehabilitation business.industry Stroke Rehabilitation Linear model Cognition Recovery of Function Middle Aged medicine.disease ddc:616.8 Institutional repository Treatment Outcome Neurology Female Neurology (clinical) medicine.symptom 0305 other medical science business 030217 neurology & neurosurgery |
| Zdroj: | European Journal of Neurology, Vol. 24, No 8 (2017) pp. 1084-1087 |
| ISSN: | 1351-5101 |
| Popis: | Background and purpose Motor recovery after stroke can be characterized into two different patterns. A majority of patients recover about 70% of initial impairment, whereas some patients with severe initial deficits show little or no improvement. Here, we investigated whether recovery from visuospatial neglect and aphasia is also separated into two different groups and whether similar proportions of recovery can be expected for the two cognitive functions. Methods We assessed 35 patients with neglect and 14 patients with aphasia at 3 weeks and 3 months after stroke using standardized tests. Recovery patterns were classified with hierarchical clustering and the proportion of recovery was estimated from initial impairment using a linear regression analysis. Results Patients were reliably clustered into two different groups. For patients in the first cluster (n = 40), recovery followed a linear model where improvement was proportional to initial impairment and achieved 71% of maximal possible recovery for both cognitive deficits. Patients in the second cluster (n = 9) exhibited poor recovery ( |
| Databáze: | OpenAIRE |
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