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Utilizing Repetitive Transcranial Magnetic Stimulation to Improve Language Function in Stroke Patients with Chronic Non-fluent Aphasia
Published on: July 2, 2013
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Recovery from aphasia in the first year after stroke.
Stephen M Wilson1,2, Jillian L Entrup1, Sarah M Schneck1
1Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
Brain : a Journal of Neurology
|April 7, 2022
Summary
Stroke aphasia recovery is dynamic and depends on lesion location. Most patients show improvement within a year, with persistent deficits mainly in those with extensive brain damage.
Area of Science:
- Neuroscience
- Neurology
- Speech and Language Pathology
Background:
- Aphasia frequently follows stroke, impacting speech and language.
- Recovery patterns and influencing factors, like lesion characteristics, are not fully understood.
- Understanding stroke-induced aphasia recovery is crucial for clinical prognostication.
Purpose of the Study:
- To comprehensively describe aphasia recovery patterns in the first year post-stroke.
- To investigate the influence of lesion location and extent on recovery trajectories.
- To identify predictors of persistent aphasia deficits.
Main Methods:
- Recruited 334 patients with acute left hemisphere stroke.
- Assessed speech and language using the Quick Aphasia Battery (QAB) within 5 days, and longitudinally at 1, 3 months, and 1 year.
- Manually delineated lesions from acute MRI/CT scans and grouped patients by lesion patterns.
Main Results:
- Aphasia is dynamic, multidimensional, and gradated, not explained by subtypes or fluency.
- Good recovery was observed in patients with circumscribed frontal lesions, and surprisingly, also in many with larger frontal or circumscribed temporal/parietal lesions.
- Persistent deficits were most common in patients with extensive middle cerebral artery or temporoparietal damage.
Conclusions:
- Lesion location and extent significantly influence aphasia recovery dynamics.
- Recovery rates and outcomes vary across different speech and language domains.
- Findings enable clinicians to better predict individual patient recovery trajectories post-stroke.
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