Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke

Biesbroek, J Matthijs; Weaver, Nick A; Aben, Hugo P; Kuijf, Hugo J; Abrigo, Jill; Bae, Hee-Joon; Barbay, Mélanie; Best, Jonathan G; Bordet, Régis; Chappell, Francesca M; Chen, Christopher P L H; Dondaine, Thibaut; van der Giessen, Ruben S; Godefroy, Olivier; Gyanwali, Bibek; Hamilton, Olivia K L; Hilal, Saima; Huenges Wajer, Irene M C; Kang, Yeonwook; Kappelle, L Jaap; Kim, Beom Joon; Köhler, Sebastian; de Kort, Paul L M; Koudstaal, Peter J; Kuchcinski, Gregory; Lam, Bonnie Y K; Lee, Byung-Chul; Lee, Keon-Joo; Lim, Jae-Sung; Lopes, Renaud; Makin, Stephen D J; Mendyk, Anne-Marie; Mok, Vincent C T; Oh, Mi Sun; van Oostenbrugge, Robert J; Roussel, Martine; Shi, Lin; Staals, Julie; Valdés-Hernández, Maria Del C; Venketasubramanian, Narayanaswamy; Verhey, Frans R J; Wardlaw, Joanna M; Werring, David J; Xin, Xu; Yu, Kyung-Ho; van Zandvoort, Martine J E; Zhao, Lei; Biessels, Geert Jan

doi:https://doi.org/10.1016/j.nicl.2022.103018

Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke

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Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke

Biesbroek, J Matthijs; Weaver, Nick A; Aben, Hugo P; Kuijf, Hugo J; Abrigo, Jill; Bae, Hee-Joon; Barbay, Mélanie; Best, Jonathan G; Bordet, Régis; Chappell, Francesca M; Chen, Christopher P L H; Dondaine, Thibaut; van der Giessen, Ruben S; Godefroy, Olivier; Gyanwali, Bibek; Hamilton, Olivia K L; Hilal, Saima; Huenges Wajer, Irene M C; Kang, Yeonwook; Kappelle, L Jaap; Kim, Beom Joon; Köhler, Sebastian; de Kort, Paul L M; Koudstaal, Peter J; Kuchcinski, Gregory; Lam, Bonnie Y K; Lee, Byung-Chul; Lee, Keon-Joo; Lim, Jae-Sung; Lopes, Renaud; Makin, Stephen D J; Mendyk, Anne-Marie; Mok, Vincent C T; Oh, Mi Sun; van Oostenbrugge, Robert J; Roussel, Martine; Shi, Lin; Staals, Julie; Valdés-Hernández, Maria Del C; Venketasubramanian, Narayanaswamy; Verhey, Frans R J; Wardlaw, Joanna M; Werring, David J; Xin, Xu; Yu, Kyung-Ho; van Zandvoort, Martine J E; Zhao, Lei; Biessels, Geert Jan

(2022) NeuroImage. Clinical, volume 34, pp. 1 - 7

(Article)

Abstract

BACKGROUND: Post-stroke cognitive impairment (PSCI) is a common consequence of stroke. Accurate prediction of PSCI risk is challenging. The recently developed network impact score, which integrates information on infarct location and size with brain network topology, may improve PSCI risk prediction. AIMS: To determine if the network impact score is ... read more an independent predictor of PSCI, and of cognitive recovery or decline. METHODS: We pooled data from patients with acute ischemic stroke from 12 cohorts through the Meta VCI Map consortium. PSCI was defined as impairment in ≥ 1 cognitive domain on neuropsychological examination, or abnormal Montreal Cognitive Assessment. Cognitive recovery was defined as conversion from PSCI < 3 months post-stroke to no PSCI at follow-up, and cognitive decline as conversion from no PSCI to PSCI. The network impact score was related to serial measures of PSCI using Generalized Estimating Equations (GEE) models, and to PSCI stratified according to post-stroke interval (<3, 3-12, 12-24, >24 months) and cognitive recovery or decline using logistic regression. Models were adjusted for age, sex, education, prior stroke, infarct volume, and study site. RESULTS: We included 2341 patients with 4657 cognitive assessments. PSCI was present in 398/844 patients (47%) <3 months, 709/1640 (43%) at 3-12 months, 243/853 (28%) at 12-24 months, and 208/522 (40%) >24 months. Cognitive recovery occurred in 64/181 (35%) patients and cognitive decline in 26/287 (9%). The network impact score predicted PSCI in the univariable (OR 1.50, 95%CI 1.34-1.68) and multivariable (OR 1.27, 95%CI 1.10-1.46) GEE model, with similar ORs in the logistic regression models for specified post-stroke intervals. The network impact score was not associated with cognitive recovery or decline. CONCLUSIONS: The network impact score is an independent predictor of PSCI. As such, the network impact score may contribute to a more precise and individualized cognitive prognostication in patients with ischemic stroke. Future studies should address if multimodal prediction models, combining the network impact score with demographics, clinical characteristics and other advanced brain imaging biomarkers, will provide accurate individualized prediction of PSCI. A tool for calculating the network impact score is freely available at https://metavcimap.org/features/software-tools/lsm-viewer/.

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Keywords: Brain connectomics, Dementia, Diffusion-weighted imaging, Ischaemic stroke, Post-stroke cognitive impairment, Radiology Nuclear Medicine and imaging, Neurology, Clinical Neurology, Cognitive Neuroscience

DOI: https://doi.org/10.1016/j.nicl.2022.103018

ISSN: 2213-1582

Publisher: Elsevier

Note: Funding Information: This study was supported by a VIMP grant (project 7330505031) from The Netherlands Organisation for Health Research and Development (ZonMw) to JMB and GJB. The Meta VCI Map consortium is supported by Vici Grant 918.16.616 from ZonMw to GJB. The funding sources had no in role in study design, collection, analysis and interpretation of data, writing of the report, and the decision to submit the article for publication. Funding Information: The CASPER cohort was supported by Maastricht University, Health Foundation Limburg, and Stichting Adriana van Rinsum-Ponsen. The COAST study was funded by a National University Health System Start Up Grant ( NPR008/NH01M ) and a National Medical Research Council Centre Grant ( NMRC/CG/NUHS/2010 ). The CROMIS-2 cohort was funded by the UK Stroke Association and the British Heart Foundation (grant #TSA BHF 2009/01). The CU-STRIDE cohort was supported by the Health and Health Services Research Fund of the Food and Health Bureau of the Government of Hong Kong (grant #0708041), the Lui Che Woo Institute of Innovative Medicine, and Therese Pei Fong Chow Research Centre for Prevention of Dementia. The GRECogVASC cohort was funded by Amiens University Hospital and by a grant from the French Ministry of Health (grant #DGOS R1/2013/144). The MSS-2 cohort (ongoing) was funded by the Wellcome Trust (grant #WT088134/Z/09/A to JMW) and the Row Fogo Charitable Trust. The PROCRAS cohort was funded via ZonMW as part of the TopZorg project in 2015 (grant #842003011). The CODECS cohort (ongoing) is supported by a grant from Stichting Coolsingel (grant #514). The Bundang VCI and Hallym VCI cohort groups do not report any relevant funding sources. OKLH is funded by the College of Medicine and Veterinary Medicine at the University of Edinburgh, and is supported by the Wellcome Trust through the Translational Neuroscience PhD programme at the University of Edinburgh. Funding Information: The CASPER cohort was supported by Maastricht University, Health Foundation Limburg, and Stichting Adriana van Rinsum-Ponsen. The COAST study was funded by a National University Health System Start Up Grant (NPR008/NH01M) and a National Medical Research Council Centre Grant (NMRC/CG/NUHS/2010). The CROMIS-2 cohort was funded by the UK Stroke Association and the British Heart Foundation (grant #TSA BHF 2009/01). The CU-STRIDE cohort was supported by the Health and Health Services Research Fund of the Food and Health Bureau of the Government of Hong Kong (grant #0708041), the Lui Che Woo Institute of Innovative Medicine, and Therese Pei Fong Chow Research Centre for Prevention of Dementia. The GRECogVASC cohort was funded by Amiens University Hospital and by a grant from the French Ministry of Health (grant #DGOS R1/2013/144). The MSS-2 cohort (ongoing) was funded by the Wellcome Trust (grant #WT088134/Z/09/A to JMW) and the Row Fogo Charitable Trust. The PROCRAS cohort was funded via ZonMW as part of the TopZorg project in 2015 (grant #842003011). The CODECS cohort (ongoing) is supported by a grant from Stichting Coolsingel (grant #514). The Bundang VCI and Hallym VCI cohort groups do not report any relevant funding sources. OKLH is funded by the College of Medicine and Veterinary Medicine at the University of Edinburgh, and is supported by the Wellcome Trust through the Translational Neuroscience PhD programme at the University of Edinburgh. Publisher Copyright: © 2022 The Author(s)

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