Fanny Munsch1, Sharmila Sagnier1, Julien Asselineau1, Antoine Bigourdan1, Charles R Guttmann1, Sabrina Debruxelles1, Mathilde Poli1, Pauline Renou1, Paul Perez1, Vincent Dousset1, Igor Sibon1, Thomas Tourdias2. 1. From the Université de Bordeaux, Bordeaux, France (F.M., C.R.G., V.D., I.S., T.T.); Neuroimagerie diagnostique et thérapeutique (F.M., A.B., V.D., T.T.), Unité neurovasculaire (S.S., S.D., M.P., P.R., I.S.), and Pôle de santé publique, Unité de Soutien Méthodologique à la Recherche Clinique et Epidémiologique (J.A., P.P.), CHU de Bordeaux, Bordeaux, France; INSERM, U862, Neurocentre Magendie, Bordeaux, France (F.M., V.D., T.T.); Center for Neurological Imaging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (C.R.G.); and INCIA, Bordeaux, France (I.S.). 2. From the Université de Bordeaux, Bordeaux, France (F.M., C.R.G., V.D., I.S., T.T.); Neuroimagerie diagnostique et thérapeutique (F.M., A.B., V.D., T.T.), Unité neurovasculaire (S.S., S.D., M.P., P.R., I.S.), and Pôle de santé publique, Unité de Soutien Méthodologique à la Recherche Clinique et Epidémiologique (J.A., P.P.), CHU de Bordeaux, Bordeaux, France; INSERM, U862, Neurocentre Magendie, Bordeaux, France (F.M., V.D., T.T.); Center for Neurological Imaging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (C.R.G.); and INCIA, Bordeaux, France (I.S.). thomas.tourdias@chu-bordeaux.fr.
Abstract
BACKGROUND AND PURPOSE: On top of functional outcome, accurate prediction of cognitive outcome for stroke patients is an unmet need with major implications for clinical management. We investigated whether stroke location may contribute independent prognostic value to multifactorial predictive models of functional and cognitive outcomes. METHODS: Four hundred twenty-eight consecutive patients with ischemic stroke were prospectively assessed with magnetic resonance imaging at 24 to 72 hours and at 3 months for functional outcome using the modified Rankin Scale and cognitive outcome using the Montreal Cognitive Assessment (MoCA). Statistical maps of functional and cognitive eloquent regions were derived from the first 215 patients (development sample) using voxel-based lesion-symptom mapping. We used multivariate logistic regression models to study the influence of stroke location (number of eloquent voxels from voxel-based lesion-symptom mapping maps), age, initial National Institutes of Health Stroke Scale and stroke volume on modified Rankin Scale and MoCA. The second part of our cohort was used as an independent replication sample. RESULTS: In univariate analyses, stroke location, age, initial National Institutes of Health Stroke Scale, and stroke volume were all predictive of poor modified Rankin Scale and MoCA. In multivariable analyses, stroke location remained the strongest independent predictor of MoCA and significantly improved the prediction compared with using only age, initial National Institutes of Health Stroke Scale, and stroke volume (area under the curve increased from 0.697-0.771; difference=0.073; 95% confidence interval, 0.008-0.155). In contrast, stroke location did not persist as independent predictor of modified Rankin Scale that was mainly driven by initial National Institutes of Health Stroke Scale (area under the curve going from 0.840 to 0.835). Similar results were obtained in the replication sample. CONCLUSIONS: Stroke location is an independent predictor of cognitive outcome (MoCA) at 3 months post stroke.
BACKGROUND AND PURPOSE: On top of functional outcome, accurate prediction of cognitive outcome for strokepatients is an unmet need with major implications for clinical management. We investigated whether stroke location may contribute independent prognostic value to multifactorial predictive models of functional and cognitive outcomes. METHODS: Four hundred twenty-eight consecutive patients with ischemic stroke were prospectively assessed with magnetic resonance imaging at 24 to 72 hours and at 3 months for functional outcome using the modified Rankin Scale and cognitive outcome using the Montreal Cognitive Assessment (MoCA). Statistical maps of functional and cognitive eloquent regions were derived from the first 215 patients (development sample) using voxel-based lesion-symptom mapping. We used multivariate logistic regression models to study the influence of stroke location (number of eloquent voxels from voxel-based lesion-symptom mapping maps), age, initial National Institutes of Health Stroke Scale and stroke volume on modified Rankin Scale and MoCA. The second part of our cohort was used as an independent replication sample. RESULTS: In univariate analyses, stroke location, age, initial National Institutes of Health Stroke Scale, and stroke volume were all predictive of poor modified Rankin Scale and MoCA. In multivariable analyses, stroke location remained the strongest independent predictor of MoCA and significantly improved the prediction compared with using only age, initial National Institutes of Health Stroke Scale, and stroke volume (area under the curve increased from 0.697-0.771; difference=0.073; 95% confidence interval, 0.008-0.155). In contrast, stroke location did not persist as independent predictor of modified Rankin Scale that was mainly driven by initial National Institutes of Health Stroke Scale (area under the curve going from 0.840 to 0.835). Similar results were obtained in the replication sample. CONCLUSIONS:Stroke location is an independent predictor of cognitive outcome (MoCA) at 3 months post stroke.
Authors: Sofia Ira Ktena; Markus D Schirmer; Mark R Etherton; Anne-Katrin Giese; Carissa Tuozzo; Brittany B Mills; Daniel Rueckert; Ona Wu; Natalia S Rost Journal: Stroke Date: 2019-09-12 Impact factor: 7.914
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Authors: Lei Zhao; J Matthijs Biesbroek; Lin Shi; Wenyan Liu; Hugo J Kuijf; Winnie Wc Chu; Jill M Abrigo; Ryan Kl Lee; Thomas Wh Leung; Alexander Yl Lau; Geert J Biessels; Vincent Mok; Adrian Wong Journal: J Cereb Blood Flow Metab Date: 2017-09-12 Impact factor: 6.200
Authors: Tina Kaffenberger; Vijay Venkatraman; Chris Steward; Vincent N Thijs; Julie Bernhardt; Patricia M Desmond; Bruce C V Campbell; Nawaf Yassi Journal: Neuroradiology Date: 2022-01-30 Impact factor: 2.995
Authors: Anna K Bonkhoff; Jae-Sung Lim; Hee-Joon Bae; Nick A Weaver; Hugo J Kuijf; J Matthijs Biesbroek; Natalia S Rost; Danilo Bzdok Journal: Brain Commun Date: 2021-05-22