Long-term prognosis of aphasia after stroke

• Published in: Journal of neurology, neurosurgery and psychiatry Vol. 84; no. 3; pp. 310 - 315
• Main Authors: El Hachioui, Hanane, Lingsma, Hester F, van de Sandt-Koenderman, Mieke W M E, Dippel, Diederik W J, Koudstaal, Peter J, Visch-Brink, Evy G
• Format: Journal Article
• Language: English
• Published: England BMJ Publishing Group Ltd 01.03.2013; BMJ Publishing Group LTD
• Subjects: Aged; APHASIA; Aphasia - complications; Aphasia - diagnosis; Cardiac arrhythmia; Cardiovascular disease; Cerebrovascular Disease; Female; Heart; Humans; Ischemia; Language; Linguistics; Logistic Models; Male; Medical prognosis; Patients; Phonology; Prognosis; Prospective Studies; Recovery of Function; Rehabilitation; Risk Factors; ROC Curve; Semantics; Severity of Illness Index; Speech Therapy; Stroke; Stroke - complications; Stroke - diagnosis; Syntax; Time Factors; Variables; Verbal communication; Vocational education
• ISSN: 0022-3050; 1468-330X
• DOI: 10.1136/jnnp-2012-302596

Background The long-term functional outcome of aphasia after stroke is uncertain, even though this information is needed as early as possible for adequate patient care and support. This observational prospective study was aimed at predicting functional outcome at 1 year after stroke. Methods We examined linguistic components (ScreeLing) and functional verbal communication (Aphasia Severity Rating Scale, ASRS) in 147 aphasic patients. The ScreeLing was administered at 1, 2 and 6 weeks after stroke; the ASRS at 1 week and 1 year. The relationships between linguistic, demographic and stroke characteristics, and good functional outcome at 1 year (ASRS 4 or 5) were examined with logistic regression analyses. Results The baseline linguistic components (ie, semantics, phonology and syntax) were significant predictors (p<0.001) for 1-year outcome in univariable analyses. In multivariable analysis, these variables explained 46.5% of the variance, with phonology being the only significant predictor (p=0.003). Age, Barthel Index score, educational level and haemorrhagic stroke were identified as other significant predictors of outcome. A prognostic model of these five baseline predictors explained 55.7% of the variance. The internally validated area under the receiver operating characteristic curve (AUC) was 0.89, indicating good predictive performance. Adding the degree of phonological recovery between 1 and 6 weeks after stroke to this model increased the explained variance to 65% and the AUC to 0.91. Conclusions The outcome of aphasia at 1 year after stroke can be predicted in the first week by the phonology score, the Barthel Index score, age, educational level and stroke subtype, with phonology being the strongest predictor.