BACKGROUND: The influence of lesion size and laterality on each component of the National Institutes of Health Stroke Scale has not been delineated. The objective of this study was to use perfusion-weighted imaging to characterize the association of ischaemic volume and laterality on each component item and the total score of the <National Institutes of Health Stroke Scale. METHODS: We analysed consecutive right-handed patients with first-ever supratentorial acute ischaemic strokes who underwent acute perfusion-weighted imaging at a single centre. Perfusion deficits were defined as mean transit time > 10 s. Ordinal regression was used to clarify the relationship between ischaemic volume, laterality, and <National Institutes of Health Stroke Scale scores. RESULTS: Among 111 patients, 58 were left-hemisphere stroke, and 53 right-hemisphere stroke. Median ischaemic volume was 53 ml in left-hand stroke and 65 ml in right-hand stroke and median total National Institutes of Health Stroke Scale was 10 in left-hand stroke and eight in right-hand stroke. For individual National Institutes of Health Stroke Scale items, ischaemic volume correlated most closely with commands and visual field and most weakly with ataxia and neglect. Left-hand stroke predicted higher scores of total National Institutes of Health Stroke Scale and National Institutes of Health Stroke Scale items of questions, commands, right limb weakness, and language. Right-hand stroke predicted higher scores of left limb weakness and extinction. CONCLUSIONS: Larger perfusion defects contribute to higher scores on the total and most individual items of the National Institutes of Health Stroke Scale. However, lesion laterality contributes substantially to half the item scores, with greater association of left than right-brain side. These findings indicate that imaging-deficit correlations will be improved by designating lesions into an atlas, taking into account side in addition to size.
BACKGROUND: The influence of lesion size and laterality on each component of the National Institutes of Health Stroke Scale has not been delineated. The objective of this study was to use perfusion-weighted imaging to characterize the association of ischaemic volume and laterality on each component item and the total score of the <National Institutes of Health Stroke Scale. METHODS: We analysed consecutive right-handed patients with first-ever supratentorial acute ischaemic strokes who underwent acute perfusion-weighted imaging at a single centre. Perfusion deficits were defined as mean transit time > 10 s. Ordinal regression was used to clarify the relationship between ischaemic volume, laterality, and <National Institutes of Health Stroke Scale scores. RESULTS: Among 111 patients, 58 were left-hemisphere stroke, and 53 right-hemisphere stroke. Median ischaemic volume was 53 ml in left-hand stroke and 65 ml in right-hand stroke and median total National Institutes of Health Stroke Scale was 10 in left-hand stroke and eight in right-hand stroke. For individual National Institutes of Health Stroke Scale items, ischaemic volume correlated most closely with commands and visual field and most weakly with ataxia and neglect. Left-hand stroke predicted higher scores of total National Institutes of Health Stroke Scale and National Institutes of Health Stroke Scale items of questions, commands, right limb weakness, and language. Right-hand stroke predicted higher scores of left limb weakness and extinction. CONCLUSIONS: Larger perfusion defects contribute to higher scores on the total and most individual items of the National Institutes of Health Stroke Scale. However, lesion laterality contributes substantially to half the item scores, with greater association of left than right-brain side. These findings indicate that imaging-deficit correlations will be improved by designating lesions into an atlas, taking into account side in addition to size.
Authors: T Brott; H P Adams; C P Olinger; J R Marler; W G Barsan; J Biller; J Spilker; R Holleran; R Eberle; V Hertzberg Journal: Stroke Date: 1989-07 Impact factor: 7.914
Authors: Nina M Menezes; Hakan Ay; Ming Wang Zhu; Chloe J Lopez; Aneesh B Singhal; Jari O Karonen; Hannu J Aronen; Yawu Liu; Juho Nuutinen; Walter J Koroshetz; A Gregory Sorensen Journal: Stroke Date: 2006-11-22 Impact factor: 7.914
Authors: Lee H Schwamm; Gregg C Fonarow; Mathew J Reeves; Wenqin Pan; Michael R Frankel; Eric E Smith; Gray Ellrodt; Christopher P Cannon; Li Liang; Eric Peterson; Kenneth A Labresh Journal: Circulation Date: 2008-12-15 Impact factor: 29.690
Authors: Werner Hacke; Markku Kaste; Erich Bluhmki; Miroslav Brozman; Antoni Dávalos; Donata Guidetti; Vincent Larrue; Kennedy R Lees; Zakaria Medeghri; Thomas Machnig; Dietmar Schneider; Rüdiger von Kummer; Nils Wahlgren; Danilo Toni Journal: N Engl J Med Date: 2008-09-25 Impact factor: 91.245
Authors: J-M Olivot; M Mlynash; G Zaharchuk; M Straka; R Bammer; N Schwartz; M G Lansberg; M E Moseley; G W Albers Journal: Neurology Date: 2009-03-31 Impact factor: 9.910
Authors: Johanna Mucke; Markus Möhlenbruch; Philipp Kickingereder; Pascal J Kieslich; Philipp Bäumer; Christoph Gumbinger; Jan Purrucker; Sibu Mundiyanapurath; Heinz-Peter Schlemmer; Martin Bendszus; Alexander Radbruch Journal: PLoS One Date: 2015-04-07 Impact factor: 3.240