The association between aphasia severity, naming, verbal fluency and demographic variables in nonfluent post-stroke aphasia

Background: There are insufficiently clear and contradictory results in literature about how patient-related, stroke-related and language-related variables predict the aphasia severity after stroke and how these variables are interrelated. This study aimed to explore the association between aphasia severity and naming, verbal fluency, and demographic variables. Methods: 40 PwA with a left hemisphere stroke and nonfluent aphasia are included in this study. The entire battery of the Comprehensive Aphasia Test (CAT-HR, Swinburn et al., 2020), was administered to all subjects. Data on the severity of aphasia based on the total score on the Language Battery and performance on subtests Naming and Verbal fluency were extracted. Hierarchical regression model evaluated the association between Aphasia severity and Naming, Verbal fluency and demographic variables. Using nonparametric Spearman’s Rho coefficient, the correlations analyses between those variables and additional subtests of Verbal fluency (animals, sound) were conducted. Results: The results showed that demographic variables do not predict aphasia severity while naming explains most of the variance of aphasia severity. Additional correlation analysis showed significant correlation between aphasia severity and language variables, but not with demographic ones. Demographic variables Time post-stroke and Age were significantly correlated with Verbal fluency (sound). Conclusion: In this study, aphasia severity cannot be explained by used demographic variables. However, naming was found to be a strong predictor of aphasia severity. It is possible that the aphasia severity of nonfluent PwA is more dependent on stroke-related variables than demographic variables.