Long-term prognosis of aphasia after stroke
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 exam...
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Published in | Journal of neurology, neurosurgery and psychiatry Vol. 84; no. 3; pp. 310 - 315 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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BMJ Publishing Group Ltd
01.03.2013
BMJ Publishing Group LTD |
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Abstract | 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. |
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AbstractList | BACKGROUNDThe 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.METHODSWe 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.RESULTSThe 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.CONCLUSIONSThe 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. 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. 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. 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. 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. 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. BackgroundThe 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 1year after stroke.MethodsWe 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 6weeks after stroke; the ASRS at 1week and 1year. The relationships between linguistic, demographic and stroke characteristics, and good functional outcome at 1year (ASRS 4 or 5) were examined with logistic regression analyses.ResultsThe 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 6weeks after stroke to this model increased the explained variance to 65% and the AUC to 0.91.ConclusionsThe outcome of aphasia at 1year 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. |
Author | van de Sandt-Koenderman, Mieke W M E Dippel, Diederik W J Koudstaal, Peter J Lingsma, Hester F Visch-Brink, Evy G El Hachioui, Hanane |
Author_xml | – sequence: 1 givenname: Hanane surname: El Hachioui fullname: El Hachioui, Hanane email: h.hachiouiel@erasmusmc.nl organization: Department of Neurology, Erasmus MC University Medical Centre, Rotterdam, The Netherlands – sequence: 2 givenname: Hester F surname: Lingsma fullname: Lingsma, Hester F email: h.hachiouiel@erasmusmc.nl organization: Department of Public Health, Erasmus MC University Medical Centre, Rotterdam, The Netherlands – sequence: 3 givenname: Mieke W M E surname: van de Sandt-Koenderman fullname: van de Sandt-Koenderman, Mieke W M E email: h.hachiouiel@erasmusmc.nl organization: Department of Rehabilitation Medicine, Erasmus MC University Medical Centre, Rotterdam, The Netherlands – sequence: 4 givenname: Diederik W J surname: Dippel fullname: Dippel, Diederik W J email: h.hachiouiel@erasmusmc.nl organization: Department of Neurology, Erasmus MC University Medical Centre, Rotterdam, The Netherlands – sequence: 5 givenname: Peter J surname: Koudstaal fullname: Koudstaal, Peter J email: h.hachiouiel@erasmusmc.nl organization: Department of Neurology, Erasmus MC University Medical Centre, Rotterdam, The Netherlands – sequence: 6 givenname: Evy G surname: Visch-Brink fullname: Visch-Brink, Evy G email: h.hachiouiel@erasmusmc.nl organization: Department of Neurology, Erasmus MC University Medical Centre, Rotterdam, The Netherlands |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23117494$$D View this record in MEDLINE/PubMed |
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Snippet | Background The long-term functional outcome of aphasia after stroke is uncertain, even though this information is needed as early as possible for adequate... 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... BACKGROUNDThe long-term functional outcome of aphasia after stroke is uncertain, even though this information is needed as early as possible for adequate... BackgroundThe long-term functional outcome of aphasia after stroke is uncertain, even though this information is needed as early as possible for adequate... |
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SubjectTerms | 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 |
Title | Long-term prognosis of aphasia after stroke |
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