Post‐stroke aphasia prognosis: a review of patient‐related and stroke‐related factors

Plowman, Emily K.; Hentz, Brecken; Ellis, Charles

doi:10.1111/j.1365-2753.2011.01650.x

Cited by 250 publications

(174 citation statements)

References 54 publications

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“…Extent of poststroke recovery varies with many patient-related factors (e.g., age at stroke onset, sex, handedness, socioeconomic status) and various stroke-and lesion-related factors (e.g., initial stroke severity, lesion size, stroke subtype, lesion location), but these factors have very limited predictive power for outcome (19)(20)(21)(22)(23)(24). Even good predictors, including initial stroke severity and lesion volume, leave most of the variability in outcome unexplained (25)(26)(27)(28).…”

Section: Discussionmentioning

confidence: 99%

Network measures predict neuropsychological outcome after brain injury

Warren

Power²,

Bruss

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

246

228

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Hubs are network components that hold positions of high importance for network function. Previous research has identified hubs in human brain networks derived from neuroimaging data; however, there is little consensus on the localization of such hubs. Moreover, direct evidence regarding the role of various proposed hubs in network function (e.g., cognition) is scarce. Regions of the default mode network (DMN) have been frequently identified as "cortical hubs" of brain networks. On theoretical grounds, we have argued against some of the methods used to identify these hubs and have advocated alternative approaches that identify different regions of cortex as hubs. Our framework predicts that our proposed hub locations may play influential roles in multiple aspects of cognition, and, in contrast, that hubs identified via other methods (including salient regions in the DMN) might not exert such broad influence. Here we used a neuropsychological approach to directly test these predictions by studying long-term cognitive and behavioral outcomes in 30 patients, 19 with focal lesions to six "target" hubs identified by our approaches (high system density and participation coefficient) and 11 with focal lesions to two "control" hubs (high degree centrality). In support of our predictions, we found that damage to target locations produced severe and widespread cognitive deficits, whereas damage to control locations produced more circumscribed deficits. These findings support our interpretation of how neuroimaging-derived network measures relate to cognition and augment classic neuroanatomically based predictions about cognitive and behavioral outcomes after focal brain injury.functional connectivity | neuropsychology | fMRI | brain hubs T he careful description of circumscribed cognitive and behavioral deficits following localized brain damage has provided much of our knowledge of the functional geography of the brain. In some cases, however, relatively small, circumscribed lesions seem to have broader effects than would be predicted from their size and location. Historically, these effects sometimes have been attributed to diaschisis (i.e., effects at a distance) owing to connections between affected and unaffected brain regions. The potential importance of interactivity among brain regions is supported by recent research (1-3); for example, He et al. (4) found that visuospatial inattention after right inferior parietal lesions was best explained by the effects of those lesions on more superior parietal activity.In the broadest sense, interactive explanations of brain function can be thought of as reflecting the organization of the brain as a large-scale network. The advent of large-scale network descriptions of brain structure and function extends the possibility of richer and broader explanations of unusually severe cognitive and behavioral consequences that sometimes follow circumscribed lesions. Some large-scale network studies have focused on "hubs," a term from network science that indicates potential points of impo...

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Section: Discussionmentioning

confidence: 99%

Network measures predict neuropsychological outcome after brain injury

Warren

Power²,

Bruss

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

246

228

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“…Predicting aphasia recovery after stroke has received renewed attention in recent literature with papers examining early aphasia diagnosis and the factors believed to affect recovery, whilst providing a description of natural language recovery across time, 2,3 using patient performance on language and cognitive tests to predict therapy gain in the chronic recovery phase 5,8,10 and providing a comprehensive literature review of the variables considered important in aphasia recovery. 11 The ability to more reliably predict improved aphasia outcomes in individual stroke survivors may allow the benefit of limited aphasia rehabilitation services in clinical settings to be maximised. Predictors of aphasia recovery including vascular risk factors, stroke type, infarct volume/size and location, initial aphasia severity and type, age, gender, handedness, level of education, performance on language assessments and intelligence have all been investigated in an attempt to determine both stroke 4,5 and aphasia outcomes [1][2][3][8][9][10] at various points in the recovery journey.…”

Section: Introductionmentioning

confidence: 99%

Amount of Therapy Matters in Very Early Aphasia Rehabilitation after Stroke: A Clinical Prognostic Model

et al. 2013

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“…[77][78][79] Other research has found that such characteristics had minimal or mixed effect on recovery from aphasia. 80,81 Evidence is equivocal about the extent to which stroke-related or neurological characteristics such as time post onset, type of aphasia, and location and size of the lesion impact recovery. [81][82][83][84][85] However, it is likely that the interplay of multiple characteristics influences recovery from aphasia.…”

Section: Introductionmentioning

confidence: 99%

“…80,81 Evidence is equivocal about the extent to which stroke-related or neurological characteristics such as time post onset, type of aphasia, and location and size of the lesion impact recovery. [81][82][83][84][85] However, it is likely that the interplay of multiple characteristics influences recovery from aphasia. 85 This article explores whether stroke/neurological characteristics of severity and type of aphasia, and time post onset impact improvements seen after participating in an intensive comprehensive aphasia program.…”

Section: Introductionmentioning

confidence: 99%

“…80 Some articles report that aphasia severity, lesion size, and lesion location are important for recovery. 81 Other have reported that type of stroke and aphasia, age, and education are factors which predict recovery. 115 Still others have noted that there is too much variability in initial severity, that lesion size and location might be a predictor, and that age, sex, handedness, and education do not seem to be important factors.…”

Section: Introductionmentioning

confidence: 99%

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Outcomes of an Intensive Comprehensive Aphasia Program

Babbitt¹

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Intensive comprehensive aphasia programs (ICAP) have increased over the last decade in the US and abroad. The increase in the number of clinical programs has outpaced the research that is necessary to establish the efficacy and effectiveness of these specialized treatment programs. The ICAP model incorporates principles from neuroplasticity, that is, intensive treatment provides a platform for the massed practice and repetition required to change the brain. It also incorporates comprehensive treatment that addresses not only impairment-based language deficits but also personal goals related to participation.Programs which offer intensive comprehensive treatment can provide up to 120 hours of treatment over several weeks (e.g., six hours a day, five days a week for four weeks). ICAPs are different from other types of aphasia services which generally provide two to three hours of therapy a week. This thesis examined one ICAP in depth to describe the structure, process, and outcomes using Donabedian's model of health care evaluation. This thesis also described the experiences of the ICAP from the perspectives of the primary stakeholders.Study One (Chapter Two) was a retrospective quantitative study using behavioral measures from an existing database that documented the outcomes of participants with aphasia. It found that first-time participants improved significantly in impairment-and participationbased measures, demonstrating moderate to large effect sizes. Participant characteristics were examined to determine if improvements were related to age, time post-onset, or type and severity of aphasia. None of these factors had an impact on the amount of change measured. Given that some participants did not make significant gains on a primary outcome measure, the Western Aphasia Battery -Revised Aphasia Quotient (WAB-R AQ), Study Two (Chapter Three) examined whether participant characteristics at baseline could predict who would make significant gains on the WAB-R AQ. Age and months post-onset were significantly different between the responder and the non-responder groups. Those who showed most gains on average were younger and a longer time post-onset. A logistic regression was performed and results indicated that only age (younger participants) predicted who would respond to treatment. Time post-onset, type and severity of aphasia, naming, non-verbal cognition, and communication confidence did not show significance in a predictive model. Studies Three and Four were qualitative studies involving interviews with therapists (Chapter Four) and people with aphasia and their families (Chapter Five). Both studies were 3 conducted using a phenomenological approach which allowed for the interviewees to describe their experiences in a semi-structured interview. The clinicians described the intensity of the therapy, the rewards, and challenges of the program. Therapists also considered that the ICAP model of service delivery had several positive benefits for them, but acknowledged that the intensity of therapy was challe...

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Post‐stroke aphasia prognosis: a review of patient‐related and stroke‐related factors

Cited by 250 publications

References 54 publications

Network measures predict neuropsychological outcome after brain injury

Network measures predict neuropsychological outcome after brain injury

Amount of Therapy Matters in Very Early Aphasia Rehabilitation after Stroke: A Clinical Prognostic Model

Outcomes of an Intensive Comprehensive Aphasia Program

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