Aphasiology · 2020 · 22 citations · 21 references
Health ProfessionsNeurologySpeech-language PathologyAphasiaCognitive NeurologyNeuropsychologyAphasia AssessmentPost-stroke AphasiaStrokeAphasia PrognosisAphasia QuotientAphasia Severity Rating ScalesCerebrovascular AphasiaPost-stroke Aphasia ClassificationPost-stroke Aphasia DiagnosisStroke-related AphasiaWestern Aphasia Battery
Background: Recent studies have emphasized the importance of initial aphasia severity as a determinant of aphasia recovery. However, data on predictors of initial post-stroke aphasia severity itself are far from adequate in the available literature.Aims: The objective of the present study was to enumerate the predictors of initial aphasia severity following stroke.Methods & Procedures: Bengali version of Western Aphasia Battery (BWAB), a validated instrument, was used for language examination. All patients were examined for language deficit during the first week after stroke. Severity was estimated by deducing aphasia quotient (AQ) and considering the severity scale as per BWAB. Lesion assessment was carried out by magnetic resonance imaging (3T) in ischemic stroke (if no contraindications were found) and computed tomography in hemorrhagic stroke. Demographic factors (age, gender, bilingualism, and number of years of formal education), lesion-related factors (type of stroke, lesion volume, cortical versus sub-cortical location, and site of lesion), and initial aphasia type were independent variables, whereas initial aphasia severity (non-severe, AQ = 50 or more; severe, AQ <50) was the dependent variable. Appropriate statistical tests were applied for the analysis of collected data. Among the 515 screened participants with first-ever acute stroke, 208 presented aphasia.Outcomes & Results: On univariate analysis, the factors found to be associated with higher initial severity were monolingualism (p = .014), hemorrhagic stroke (p < .001), larger lesion volume (p < .001), cortico-subcortical mixed stroke lesion (p < .001), and a non-fluent type of aphasia (p < .001). As per binary logistic regression analysis, independent predictors of higher severity were higher volume of lesion (p < .001, OR = 1.651), hemorrhagic stroke (p = .004, OR = 11.987), and non-fluent aphasia (p = .012, OR = 4.796). The overall predictive value of the regression model was 90.4%.Conclusion: The most significant determinants of initial aphasia severity in our sample of stroke patients were lesion-related factors and non-fluent aphasia.
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