Dataset Information

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

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 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/.

SUBMITTER: Biesbroek JM

PROVIDER: S-EPMC9079101 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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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 JM Weaver Nick A NA Aben Hugo P HP Kuijf Hugo J HJ Abrigo Jill J Bae Hee-Joon HJ Barbay Mélanie M Best Jonathan G JG Bordet Régis R Chappell Francesca M FM Chen Christopher P L H CPLH Dondaine Thibaut T van der Giessen Ruben S RS Godefroy Olivier O Gyanwali Bibek B Hamilton Olivia K L OKL Hilal Saima S Huenges Wajer Irene M C IMC Kang Yeonwook Y Kappelle L Jaap LJ Kim Beom Joon BJ Köhler Sebastian S de Kort Paul L M PLM Koudstaal Peter J PJ Kuchcinski Gregory G Lam Bonnie Y K BYK Lee Byung-Chul BC Lee Keon-Joo KJ Lim Jae-Sung JS Lopes Renaud R Makin Stephen D J SDJ Mendyk Anne-Marie AM Mok Vincent C T VCT Oh Mi Sun MS van Oostenbrugge Robert J RJ Roussel Martine M Shi Lin L Staals Julie J Valdés-Hernández Maria Del C MDC Venketasubramanian Narayanaswamy N Verhey Frans R J FRJ Wardlaw Joanna M JM Werring David J DJ Xin Xu X Yu Kyung-Ho KH van Zandvoort Martine J E MJE Zhao Lei L Biessels Geert Jan GJ

NeuroImage. Clinical 20220427

<h4>Background</h4>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.<h4>Aims</h4>To determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline.<h4>Methods</h4>We pooled data from patients with acute ischemic ...[more]

PMID: 35504223

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Project description:BackgroundPost-stroke cognitive impairment (PSCI) is a common sequela after stroke. China has a large population of stroke survivors, but a large-scale survey on the incidence and risk factors for PSCI has not been undertaken. We aimed to calculate the incidence and risk factors for vascular cognitive symptoms among first-ever stroke survivors in China through a multicenter cross-sectional study.MethodsFrom May 1, 2019 to November 30, 2019, patients with a clinical diagnosis of first-ever ischemic stroke were recruited from 563 hospitalized-based stroke center networks in 30 provinces of China. Cognitive impairment was measured by 5-min National Institute of Neurological Disease and Stroke-Canadian Stroke Network (NINDS-CSN) at 3-6 months after the indexed stroke. Stepwise multivariate regression and stratified analysis were performed to assess the association between PSCI and demographic variables.FindingsA total of 24,055 first-ever ischemic stroke patients were enrolled, with an average age of 70.25 ± 9.88 years. The incidence of PSCI as per the 5-min NINDS-CSN was 78.7%. Age ≥75 years old (OR: 1.887, 95%CI: 1.391-2.559), western regional residence (OR: 1.620, 95%CI: 1.411-1.860) and lower education level were associated with increased PSCI risk. Hypertension might be related to non-PSCI (OR: 0.832, 95%CI: 0.779-0.888). For patients under 45 years old, unemployment was an independent risk factor for PSCI (OR: 6.097, 95%CI: 1.385-26.830). For patients who were residents of the southern region (OR: 1.490, 95%CI: 1.185-1.873) and non-manual workers (OR: 2.122, 95%CI: 1.188-3.792), diabetes was related to PSCI.InterpretationPSCI is common in Chinese patients with first-ever stroke, and many risk factors are related to the occurrence of PSCI.FundingThe Beijing Hospitals Authority Youth Program (No. QMS20200801); Youth Program of the National Natural Science Foundation of China (No. 81801142); the Key Project of Science and Technology Development of China Railway Corporation (No. K2019Z005); The Capital Health Research and Development of Special (No. 2020-2-2014); Science and Technology Innovation 2030-Major Project (No. 2021ZD0201806).

Project description:Background and Aims: Systemic inflammation is associated with an increased risk of cognitive impairment and dementia, but the associations between them in stroke patients are less clear. We examined the impact of systemic inflammation represented as the neutrophil-lymphocyte ratio (NLR) on the development of post-stroke cognitive impairment (PSCI) and domain-specific cognitive outcomes 3-month after ischemic stroke. Methods: Using prospective stroke registry data, we consecutively enrolled 345 participants with ischemic stroke whose cognitive functions were evaluated 3-month after stroke. Their cognition was assessed with the Korean version of the Vascular Cognitive Impairment Harmonization Standards and the Korean-Mini Mental Status Examination. PSCI was defined as a z-score of < -2 standard deviations for age, sex, and education adjusted means in at least one cognitive domain. The participants were categorized into five groups according to the quintiles of NLR (lowest NLR, Q1). The cross-sectional association between NLR and PSCI was assessed using multiple logistic regression, adjusting for age, sex, education, vascular risk factors, and stroke type. Results: A total of 345 patients were enrolled. The mean age was 63.0 years and the median NIHSS score and NLR were 2 [1-4] and 2.26 [1.65-2.91], respectively. PSCI was identified in 71 (20.6%) patients. NLR was a significant predictor for PSCI both as a continuous variable (adjusted OR, 1.14; 95% CI, 1.00-1.31) and as a categorical variable (Q5, adjusted OR, 3.26; 95% CI, 1.17-9.08). Patients in the Q5 group (NLR ≥ 3.80) showed significantly worse performance in global cognition and in visuospatial and memory domains. Conclusions: NLR in the acute stage of ischemic stroke was independently associated with PSCI at 3 months after stroke, and high NLR was specifically associated with cognitive dysfunction in the memory and visuospatial domains. Thus, systemic inflammation may be a modifiable risk factor that may influence cognitive outcomes after stroke.

Project description:Purpose Atrial fibrillation (AF) is a significant independent risk factor for 1-year mortality in patients with first acute ischemic stroke (AIS). The CHA2DS2-VASc score was initially developed to assess the risk of stroke in patients with AF. Recently, this scoring system has been demonstrated to have clinical value for predicting long-term clinical outcomes in AIS but the evidence is insufficient. This large-scale prospective cohort study investigated the independent predictive value of the score in such patients. Methods We included patients with AIS from the Taiwan Stroke Registry (TSR) during 2006–2016 as the present study population. Patients were divided into those with high (≥2) and low (<2) CHA2DS2-VASc scores. We further analyzed and classified patients according to the presence of AF. The clinical endpoint was major adverse cardiac and cerebrovascular events (MACCEs) at 1 year after the index AIS. Results A total of 62,227 patients with AIS were enrolled. The median age was 70.3 years, and 59% of the patients were women. After confounding factors were controlled, patients with high CHA2DS2-VASc scores had significantly higher incidence of 1-year MACCEs (adjusted hazard ratio [HR] = 1.63; 95% confidence interval [CI] = 1.52, 1.76), re-stroke (adjusted HR = 1.28; 95% CI = 1.16, 1.42), and all-cause mortality (adjusted HR = 2.03; 95% CI = 1.83, 2.24) than those with low CHA2DS2-VASc scores did. In the comparison between AF and non-AF groups, the AF group had increased MACCEs (adjusted HR = 1.74; 95% CI = 1.60, 1.89), myocardial infarction (adjusted HR = 4.86; 95% CI = 2.07, 11.4), re-stroke (adjusted HR = 1.47; 95% CI = 1.26, 1.71), and all-cause mortality (adjusted HR = 1.90; 95% CI = 1.72, 2.10). The Kaplan–Meier curve revealed that both CHA2DS2-VASc scores and AF were independent risk predictors for 1-year MACCEs and mortality. Conclusions The CHA2DS2-VASc score and AF appeared to consistently predict 1-year MACCEs of AIS patients and provide more accurate risk stratification. Therefore, increased use of the CHA2DS2-VASc score may help improve the holistic clinical assessment of AIS patients with or without AF.

Project description:BackgroundWhereas the Montreal Cognitive Assessment (MoCA) and Addenbrooke's cognitive examination-revised (ACE-R) are commonly used tests for the detection of post-stroke cognitive impairment (PSCI), these instruments take 10-30 min to administer and do not assess processing speed, which is a critical impairment in PSCI. MemTrax (MTx) is a continuous recognition test, which evaluates complex information processing, accuracy, speed, and attention, in 2 min.AimTo evaluate whether MTx is an effective and practical tool for PSCI assessment.MethodsThis study enrolled acute ischemic stroke (AIS) patients who have assessed the cognitive status including MTx, clinical dementia rating (CDR), MoCA, Neuropsychiatric Inventory (NPI), Hamilton depression scale (HAMD), Hamilton anxiety scale (HAMA), the National Institute of Health Stroke Scale (NIHSS), modified Rankin scale (mRS), and Barthel Index of activity of daily living (BI) combined with the physical examinations of the neurologic system at the 90-day (D90) after the AIS. The primary endpoint of this study was establishing MTx cut-offs for distinguishing PSCI from AIS.ResultsOf the 104 participants, 60 were classified to the PSCI group. The optimized cut-off value of MTx-%C (percent correct) was 78%, with a sensitivity and specificity for detecting PSCI from Non-PSCI of 90.0 and 84.1%, respectively, and an AUC of 0.919. Regarding the MTx-Cp (Composite score = MTx-%C/MTx-RT), using 46.3 as a cut-off value, the sensitivity and specificity for detecting PSCI from Non-PSCI were 80.0 and 93.2%, with an AUC of 0.925. Multivariate linear regression showed that PSCI reduced the MTx-%C (Coef. -14.18, 95% CI -18.41∼-9.95, p < 0.001) and prolonged the MTx-RT (response time) (Coef. 0.29, 95% CI 0.16∼0.43, p < 0.001) and reduced the MTx-CP (Coef. -19.11, 95% CI -24.29∼-13.93, p < 0.001).ConclusionMemTrax (MTx) is valid and effective for screening for PSCI among target patients and is a potentially valuable and practical tool in the clinical follow-up, monitoring, and case management of PSCI.

Project description:BackgroundPost-stroke cognitive impairment (PSCI) occurs in up to 50% of stroke survivors. Presence of pre-existing vascular brain injury, in particular the extent of white matter hyperintensities (WMH), is associated with worse cognitive outcome after stroke, but the role of WMH location in this association is unclear.AimsWe determined if WMH in strategic white matter tracts explain cognitive performance after stroke.MethodsIndividual patient data from nine ischemic stroke cohorts with magnetic resonance imaging (MRI) were harmonized through the Meta VCI Map consortium. The association between WMH volumes in strategic tracts and domain-specific cognitive functioning (attention and executive functioning, information processing speed, language and verbal memory) was assessed using linear mixed models and lasso regression. We used a hypothesis-driven design, primarily addressing four white matter tracts known to be strategic in memory clinic patients: the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus.ResultsThe total study sample consisted of 1568 patients (39.9% female, mean age = 67.3 years). Total WMH volume was strongly related to cognitive performance on all four cognitive domains. WMH volume in the left anterior thalamic radiation was significantly associated with cognitive performance on attention and executive functioning and information processing speed and WMH volume in the forceps major with information processing speed. The multivariable lasso regression showed that these associations were independent of age, sex, education, and total infarct volume and had larger coefficients than total WMH volume.ConclusionThese results show tract-specific relations between WMH volume and cognitive performance after ischemic stroke, independent of total WMH volume. This implies that the concept of strategic lesions in PSCI extends beyond acute infarcts and also involves pre-existing WMH.Data access statementThe Meta VCI Map consortium is dedicated to data sharing, following our guidelines.

Dataset Information

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

Background

Aims

Methods

Results

Conclusions

Publications

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

Similar Datasets

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