Left Hemisphere Bias of NIH Stroke Scale Is Most Severe for Middle Cerebral Artery Strokes

Vitti, Emilia; Kim, Nicholas; Stockbridge, Melissa D.; Hillis, Argye E.; Faria, Andréia V.

doi:10.3389/fneur.2022.912782

Cited by 9 publications

(4 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both unsupervised learning techniques identify a higher number of clusters in the left hemisphere. Possibly, this reflects the higher sensitivity of the NIHSS towards left lesions [15]. In addition, our results confirm the unreliability of the limb ataxia subtest, which is scored in supra-, infra-tentorial and in bilateral lesions.…”

Section: Discussionsupporting

confidence: 79%

Behavior Clusters in Ischemic Stroke using NIHSS

Tshimanga,

Zanola,

Facchini

et al. 2023

Preprint

View full text Add to dashboard Cite

BACKGROUNDStroke is one of the leading causes of death and disability. The resulting behavioral deficits can be measured with clinical scales of motor, sensory, and cognitive impairment. The most common of such scales is the National Institutes of Health Stroke Scale, or NIHSS. Computerized tomography (CT) and magnetic resonance imaging (MRI) scans show predominantly subcortical or subcortical-cortical lesions, with pure cortical lesions occurring less frequently. While many experimental studies have correlated specific deficits (e.g. motor or language impairment) with stroke lesion locations, the mapping between symptoms and lesions is not straightforward in clinical practice. The advancement of machine learning and data science in recent years has shown unprecedented opportunities even in the biomedical domain. Nevertheless, their application to medicine is not simple, and the development of data driven methods to learn general mathematical models of diseases from healthcare data is still an unsolved challenge.METHODSIn this paper we measure statistical similarities of stroke patients based on their NIHSS scores, and we aggregate symptoms profiles through two different unsupervised machine learning techniques: spectral clustering and affinity propagation.RESULTSWe identify clusters of patients with largely overlapping, coherent lesions, based on the similarity of behavioral profiles.CONCLUSIONSOverall, we show that an unsupervised learning workflow, open source and transferable to other conditions, can identify coherent mathematical representations of stroke lesions based only on NIHSS data.

show abstract

Section: Discussionsupporting

confidence: 79%

Behavior Clusters in Ischemic Stroke using NIHSS

Tshimanga,

Zanola,

Facchini

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…NIHSS in aphasia might score 7 points more if compared to scoring 2 points in neglect. As a result, patients with left hemisphere stroke with aphasia usually score higher scores [ 15 ].…”

Section: Discussionmentioning

confidence: 99%

NIHSS is deficient in acute stroke presenting with cortical deafness; clinical skills remain the backbone: a case report

Roushdy

Mikhail

Abdel-Aziz

2023

Egypt J Neurol Psychiatry Neurosurg

View full text Add to dashboard Cite

Background National institutes of health stroke scale (NIHSS) is used, since its appearance in analysis of stroke in any national or international single center or multicenter study. It is also the golden standard assessment scale for stroke patients whether by emergency medical services on the way to hospital or by emergency room staff and by neurologists whether juniors or senior consultants. Yet, it is not capable of identifying all stroke cases. Along the current case report a relatively rare case of cortical deafness is presented highlighting its rarity and its vascular mechanism as well as how defective is NIHSS in recognizing it. Case presentation 72-year-old female patient presented with sudden episodic less than 60 min duration of bilateral deafness; initial imaging showed right hemispheric encephalomalacia of old stroke. Patient was initially managed as psychogenic case especially that her NIHSS was zero. On returning again to emergency room she was administered thrombolysis and regained full hearing power. Follow-up imaging revealed a new ischemic stroke along her left auditory cortex explaining her cortical deafness. Conclusion Cortical deafness might be missed especially that NIHSS does not detect it. NIHSS role as the only golden standard scale for diagnosing and following up stroke cases ought to be revised.

show abstract

“…That is, individuals with left-hemisphere strokes score more highly than those with right-hemisphere strokes, even when controlling for both age and overall stroke volume. [11][12][13][14][15] This is due to the potential of the test to capture the effects of language deficits across multiple items, whereas deficits of communication and cognition more commonly associated with right-hemisphere damage are assessed only in the item neglect/inattention (neglect occurs in ≈38% of patients after right-hemisphere stroke versus 18% after left-hemisphere stroke). 16 To evaluate the best language of a patient, administration of the NIHSS includes asking the patient to describe the cookie theft picture, originally a stimulus in the Boston Diagnostic Aphasia Evaluation, 17 to read words and sentences written on a card, and to identify the names of items (cacti, a glove, a chair, a key, a hammock, and a feather).…”

Section: See Related Article P 452mentioning

confidence: 99%

mentioning

confidence: 99%

New Picture Stimuli for the NIH Stroke Scale: A Validation Study

Stockbridge,

Kelly,

Newman-Norlund

et al. 2024

Stroke

Self Cite

View full text Add to dashboard Cite

BACKGROUND: The National Institutes of Health Stroke Scale is a widely accepted tool for structured graded neurological examination of stroke or suspected stroke in the hyperacute setting. Concerns have arisen about the use of its picture stimuli in a contemporary and global health context. Here, we present new stimuli prepared to serve the needs of stroke providers worldwide: the precarious painter image description and updated objects for naming. METHODS: This was a validation study of 101 healthy fluent English speakers. Participants were reached by the Johns Hopkins Outpatient Center, the University of South Carolina, and Prisma Health from 2022 to 2023 and included residents of the United States, Germany, Canada, the United Kingdom, Australia, and Zambia. Participants were recorded in person or via video conferencing when asked to describe the new picture, while a subset named seven illustrations. Multivariate analyses of variance were used for primary analyses. In a complementary investigation, 299 attendees of the 2023 International Stroke Conference were asked about their preference for the existing or new stimuli and why. RESULTS: Each of the 44 content units from the picture description was included by at least 5% of respondents in the demographically representative subsample. Performance was similar across healthy participants irrespective of age, sex, race, ethnicity, or education. Typical descriptions were characterized by an average of 23 content units (SD=5) conveyed with 167 syllables (SD=79). The new naming stimuli were recognized by 100% of participants from many countries as being familiar and identifiable, and names provided in response to the task were highly convergent. The majority of stroke health care providers preferred both the precarious painter and naming stimuli. CONCLUSIONS: The description of the new National Institutes of Health Stroke Scale picture, the precarious painter, results in rich samples among healthy speakers that will provide an appropriate basis for the detection of language deficits.

show abstract

Left Hemisphere Bias of NIH Stroke Scale Is Most Severe for Middle Cerebral Artery Strokes

Cited by 9 publications

References 40 publications

Behavior Clusters in Ischemic Stroke using NIHSS

Behavior Clusters in Ischemic Stroke using NIHSS

NIHSS is deficient in acute stroke presenting with cortical deafness; clinical skills remain the backbone: a case report

New Picture Stimuli for the NIH Stroke Scale: A Validation Study

Contact Info

Product

Resources

About