An Efficient Bedside Measure Yields Prognostic Implications for Language Recovery in Acute Stroke Patients

一项高效的床旁评估方法对急性卒中患者的语言功能恢复具有预后意义

阅读:1

Abstract

BACKGROUND: It is estimated that ∼30% of stroke survivors have aphasia, a language disorder resulting from damage to left-hemisphere language networks. In acute care settings, efficient identification of aphasia is critical, but there is a paucity of efficient bedside assessments. OBJECTIVE: To determine whether objective measures on a picture description task administered within 48 hours post stroke (a) predict language recovery, (b) estimate left-hemisphere lesion volume and location, and (c) correlate with other bedside language assessments. METHOD: Behavioral data were scored at acute and chronic time points. Neuroimaging data were used to determine associations between the picture description task, other language assessments, and lesion volume and location. RESULTS: Acute content units, age, and total lesion volume predicted communication recovery; F3,18 = 3.98, P = 0.024; r = 0.40. Significant correlations were found between the picture description task and lesion volume and location. Picture description outcomes were also associated with other clinical language assessments. DISCUSSION: This picture description task quickly predicted the language performance (communication recovery and outcome) for patients who suffered a left-hemisphere stroke. Picture description task measures correlated with damage in the left hemisphere and with other, more time-consuming and cumbersome language assessments that are typically administered acutely at bedside. CONCLUSION: The predictive value of this picture description task and correlations with existing language assessments substantiate the clinical importance of a reliable yet rapid bedside measure for acute stroke patients that can be administered by a variety of health care professionals.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。