UNASSIGNED: Although white matter hyperintensity (WMH) shares similar vascular risk and pathology with small vessel occlusion (SVO) stroke, there were few studies to evaluate the impact of the burden of WMH volume on early and delayed stroke outcomes in SVO stroke.
UNASSIGNED: Using a multicenter registry database, we enrolled SVO stroke patients between August 2013 and November 2022. The WMH volume was estimated by automated methods using deep learning (VUNO Med-DeepBrain, Seoul, South Korea), which was a commercially available segmentation model. After propensity score matching (PSM), we evaluated the impact of WMH volume on early neurological deterioration (END) and poor functional outcomes at 3-month modified Ranking Scale (mRS), defined as mRS score >2 at 3 months, after an SVO stroke.
UNASSIGNED: Among 1,718 SVO stroke cases, the prevalence of subjects with severe WMH (Fazekas score ≥ 3) was 68.9%. After PSM, END and poor functional outcomes at 3-month mRS (mRS > 2) were higher in the severe WMH group (END: 6.9 vs. 13.5%, p < 0.001; 3-month mRS > 2: 11.4 vs. 24.7%, p < 0.001). The logistic regression analysis using the PSM cohort showed that total WMH volume increased the risk of END [odd ratio [OR], 95% confidence interval [CI]; 1.01, 1.00-1.02, p = 0.048] and 3-month mRS > 2 (OR, 95% CI; 1.02, 1.01-1.03, p < 0.001). Deep WMH was associated with both END and 3-month mRS > 2, but periventricular WMH was associated with 3-month mRS > 2 only.
UNASSIGNED: This study used automated methods using a deep learning segmentation model to assess the impact of WMH burden on outcomes in SVO stroke. Our findings emphasize the significance of WMH burden in SVO stroke prognosis, encouraging tailored interventions for better patient care.

UNASSIGNED: Stroke is a prominent cause of long-term adult impairment globally and a significant global health issue. Only 14% of stroke survivors achieve full recovery, while 25% to 50% require varying degrees of support, and over half become dependent. The aftermath of a stroke brings profound changes to an individual\'s life, with early choices significantly impacting their quality of life. This review aims to establish the efficacy of neuroimaging data in predicting long-term outcomes and recovery rates following a stroke.
UNASSIGNED: A scientific literature search was conducted using the Centre of Reviews and Dissemination (CRD) criteria and PRISMA guidelines for a combined meta-narrative and systematic quantitative review. The methodology involved a structured search in databases like PubMed and The Cochrane Library, following inclusion and exclusion criteria to identify relevant studies on neuroimaging biomarkers for stroke outcome prediction. Data collection utilized the Microsoft Edge Zotero plugin, with quality appraisal conducted via the CASP checklist. Studies published from 2010 to 2024, including observational, randomized control trials, case reports, and clinical trials. Non-English and incomplete studies were excluded, resulting in the identification of 11 pertinent articles. Data extraction emphasized study methodologies, stroke conditions, clinical parameters, and biomarkers, aiming to provide a thorough literature overview and evaluate the significance of neuroimaging biomarkers in predicting stroke recovery outcomes.
UNASSIGNED: The results of this systematic review indicate that integrating advanced neuroimaging methods with highly successful reperfusion therapies following a stroke facilitates the diagnosis of the condition and assists in improving neurological impairments resulting from stroke. These measures reduce the possibility of death and improve the treatment provided to stroke patients.
UNASSIGNED: These findings highlight the crucial role of neuroimaging in advancing our understanding of post-stroke outcomes and improving patient care.

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This article provides a comprehensive review of widely utilized stroke scales in both routine clinical settings and research. These scales are crucial for planning treatment, predicting outcomes, and helping stroke patients recover. They also play a pivotal role in planning, executing, and comprehending stroke clinical trials. Each scale presents distinct advantages and limitations, and the authors explore these aspects within the article. The authors\' intention is to provide the reader with practical insights for a clear understanding of these scales, and their effective use in their clinical practice.

OBJECTIVE: Stroke is the leading cause of adult-onset disability. Although clinical factors influence stroke outcome, there is a significant variability among individuals that may be attributed to genetics and epigenetics, including DNA methylation (DNAm). We aimed to study the association between DNAm and stroke prognosis.
RESULTS: To that aim, we conducted a two-phase study (discovery-replication and meta-analysis) in Caucasian patients with ischemic stroke from two independent centers (BasicMar [discovery, N = 316] and St. Pau [replication, N = 92]). Functional outcome was assessed using the modified Rankin Scale (mRS) at three months after stroke, being poor outcome defined as mRS > 2. DNAm was determined using the 450K and EPIC BeadChips in whole-blood samples collected within the first 24 h. We searched for differentially methylated positions (DMPs) in 370,344 CpGs, and candidates below p-value < 10-5 were subsequently tested in the replication cohort. We then meta-analyzed DMP results from both cohorts and used them to identify differentially methylated regions (DMRs). After doing the epigenome-wide association study, we found 29 DMPs at p-value < 10-5 and one of them was replicated: cg24391982, annotated to thrombospondin-2 (THBS2) gene (p-valuediscovery = 1.54·10-6; p-valuereplication = 9.17·10-4; p-valuemeta-analysis = 6.39·10-9). Besides, four DMRs were identified in patients with poor outcome annotated to zinc finger protein 57 homolog (ZFP57), Arachidonate 12-Lipoxygenase 12S Type (ALOX12), ABI Family Member 3 (ABI3) and Allantoicase (ALLC) genes (p-value < 1·10-9 in all cases).
CONCLUSIONS: Patients with poor outcome showed a DMP at THBS2 and four DMRs annotated to ZFP57, ALOX12, ABI3 and ALLC genes. This suggests an association between stroke outcome and DNAm, which may help identify new stroke recovery mechanisms.

OBJECTIVE: The purpose of this study was to investigate the predictive value of mean platelet volume (MPV) and platelet count (PC) in branch atheromatous disease (BAD).
METHODS: This retrospective study included 216 patients with BAD-stroke within 48 h of symptom onset. These patients were divided into good and poor prognosis groups according to their 3-month modified Rankin scale scores after discharge. Multiple logistic regression analysis was used to evaluate independent predictors of poor prognosis in BAD-stroke patients. Receiver-operating characteristic (ROC) analysis was used to estimate the predictive value of MPV and PC on BAD-stroke.
RESULTS: Our research showed that a higher MPV (aOR, 2.926; 95% CI, 2.040-4.196; p < .001) and PC (aOR, 1.013; 95% CI, 1.005-1.020; p = .001) were independently associated with poor prognosis after adjustment for confounders. The ROC analysis of MPV for predicting poor prognosis showed that the sensitivity and specificity were 74% and 84.9%, respectively, and that the AUC was .843 (95% CI, .776-.909, p < .001). The optimal cut-off value was 12.35. The incidence of early neurological deterioration (END) was 24.5% (53 of 163), and 66% of patients in the poor prognosis group had END (33 of 50). Multiple logistic regression analyses showed that elevated MPV and PC were associated with the occurrence of END (p < .05).
CONCLUSIONS: Our results suggested that an elevated MPV and PC may be important in predicting a worse outcome in BAD-stroke patients. Our study also demonstrated an independent association of MPV and PC with END, which is presumably the main reason for the poor prognosis.

OBJECTIVE: Whether different antihypertensive drug classes in high blood pressure (HBP) pre-stroke treatment affect dynamic cerebral autoregulation (dCA), stroke severity, and outcome.
METHODS: Among 337 consecutive ischemic stroke patients (female 102; median age 71 years [interquartile range, [IQR 60; 78]; NIHSS median 3 [IQR 1; 6]) with assessment of dCA, 183 exhibited the diagnosis of HBP. dCA parameters\' gain and phase were determined by transfer function analysis of spontaneous oscillations of blood pressure and cerebral blood flow velocity.
RESULTS: Patients used beta-blockers (n = 76), calcium channel blockers (60), diuretics (77), angiotensin-converting enzyme inhibitors (59), or angiotensin-1 receptor blockers (79), mostly in various combinations of two or three drug classes. dCA parameters did not differ between the non-HBP and the different HBP medication groups. Multinomial ordinal logistic regression models revealed that the use of diuretics decreased the likelihood of a less severe stroke (odds ratio 0.691, 95% CI 0.493; 0.972; p = 0.01) and that beta-blockers decreased the likelihood of a better modified Rankin score at 3 months (odds ratio 0.981, 95% CI 0.970; 0.992; p = 0.009). Other independent factors associated with stroke outcome were penumbra and infarct volume, treatment with mechanical thrombectomy, and the initial National Institute of Health Stroke Scale score.
CONCLUSIONS: In this cohort of ischemic minor to moderate stroke patients, pre-stroke antihypertensive treatment with diuretics was associated with a more severe neurological deficit on admission and pre-stroke treatment with beta-blockers with a poorer 3-month outcome. The antihypertensive drug class used pre-stroke did not impact dCA.

Ischemic stroke, which accounts for 87% of cerebrovascular accidents, is responsible for massive global burden both in terms of economic cost and personal hardship. Many stroke survivors face long-term disability-a phenotype associated with an increasing number of genetic variants. While clinical variables such as stroke severity greatly impact recovery, genetic polymorphisms linked to functional outcome may offer physicians a unique opportunity to deliver personalized care based on their patient\'s genetic makeup, leading to improved outcomes. A comprehensive catalogue of the variants at play is required for such an approach. In this review, we compile and describe the polymorphisms associated with outcome scores such as modified Rankin Scale and Barthel Index. Our search identified 74 known genetic polymorphisms spread across 48 features associated with various poststroke disability metrics. The known variants span diverse biological systems and are related to inflammation, vascular homeostasis, growth factors, metabolism, the p53 regulatory pathway, and mitochondrial variation. Understanding how these variants influence functional outcome may be helpful in maximizing poststroke recovery.

This dataset offers images of mouse brains impacted by photothrombotic stroke in the sensorimotor cortex published by Weber et al. NeuroImage (2024). Data is gathered using two primary techniques: (1) whole-brain ex-vivo magnetic resonance imaging (MRI) and (2) 40 µm thick coronal histological sections that undergo immunofluorescence staining with NeuroTrace. Infarct areas and volumes are assessed through MRI at two distinct time frames-three days (acute) and 28 days (chronic) following photothrombotic stroke induction. Subsequently, the brains are sectioned into 40 µm thick coronal slices, stained with NeuroTrace, and imaged as whole sections. The dataset holds considerable value for reuse, particularly for researchers focused on stroke volume estimation methods as well as those interested in comparing the efficacy of MRI and histological techniques.

The prediction of stroke outcome is challenging due to the high inter-individual variability in stroke patients. We recently suggested the adaptation of the concept of brain reserve (BR) to improve the prediction of stroke outcome. This concept was initially developed alongside the one for the cognitive reserve for neurodegeneration and forms a valuable theoretical framework to capture high inter-individual variability in stroke patients. In the present work, we suggest and discuss (i) BR-proxies-quantitative brain characteristics at the time stroke occurs (e.g., brain volume, hippocampus volume), and (ii) proxies of brain pathology reducing BR (e.g., brain atrophy, severity of white matter hyperintensities), parameters easily available from a routine MRI examination that might improve the prediction of stroke outcome. Though the influence of these parameters on stroke outcome has been partly reported individually, their independent and combined impact is yet to be determined. Conceptually, BR is a continuous measure determining the amount of brain structure available to mitigate and compensate for stroke damage, thus reflecting individual differences in neural resources and a capacity to maintain performance and recover after stroke. We suggest that stroke outcome might be defined as an interaction between BR at the time stroke occurs and lesion load. BR in stroke can potentially be influenced, e.g., by modifying cardiovascular risk factors. In addition to the potential power of the BR concept in a mechanistic understanding of inter-individual variability in stroke outcome and establishing individualized therapeutic approaches, it might help to strengthen the synergy of preventive measures in stroke, neurodegeneration, and healthy aging.