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Objectives The incidence of Guillain-Barré syndrome (GBS) changed significantly during the coronavirus disease 2019 (COVID-19) pandemic. Emerging reports suggest that viral vector-based vaccines may be associated with an elevated risk of GBS. Methods In this nationwide time-series correlation study, we examined the age-specific incidence of GBS from January 2011 to August 2022, as well as data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccinations and infections from February 2021 to August 2022. We compared the forecasted estimates of age-specific GBS incidence, using the pre-SARS-CoV-2 period as a benchmark, with the actual incidence observed during the post-vaccination period of the pandemic. Furthermore, we assessed the temporal association between GBS, SARS-CoV-2 vaccinations, and COVID-19 for different age groups. Results In the age group of 60 and older, the rate ratio was significantly elevated during June-August and November 2021. A significant, strong positive association was observed between viral vector-based vaccines and GBS incidence trends in this age group (r=0.52, p=0.022). For the 30 to 59 years age group, the rate ratio was notably high in September 2021. A statistically significant, strong positive association was found between mRNA-based vaccines and GBS incidence in this age group (r=0.61, p=0.006). Conclusion Viral vector-based SARS-CoV-2 vaccines were found to be temporally associated with an increased risk of GBS, particularly in older adults. To minimize age-specific and biological mechanism-specific adverse events, future vaccination campaigns should adopt a more personalized approach, such as recommending homologous mRNA-based SARS-CoV-2 vaccines for older adults to reduce the heightened risk of GBS.

Abstract Identifying the cerebral arterial branches is essential for undertaking a computational approach to cerebrovascular imaging. However, the complexity and inter-individual differences involved in this process have not been thoroughly studied. We used machine learning to examine the anatomical profile of the cerebral arterial tree. The method is less sensitive to inter-subject and cohort-wise anatomical variations and exhibits robust performance with an unprecedented in-depth vessel range. We applied machine learning algorithms to disease-free healthy control subjects (n = 42), patients with stroke with intracranial atherosclerosis (ICAS) (n = 46), and patients with stroke mixed with the existing controls (n = 69). We trained and tested 70% and 30% of each study cohort, respectively, incorporating spatial coordinates and geometric vessel feature vectors. Cerebral arterial images were analyzed based on the ‘segmentation-stacking’ method using magnetic resonance angiography. We precisely classified the cerebral arteries across the exhaustive scope of vessel components using advanced geometric characterization, redefinition of vessel unit conception, and post-processing algorithms. We verified that the neural network ensemble, with multiple joint models as the combined predictor, classified all vessel component types independent of inter-subject variations in cerebral arterial anatomy. The validity of the categorization performance of the model was tested, considering the control, ICAS, and control-blended stroke cohorts, using the area under the receiver operating characteristic (ROC) curve and precision-recall curve. The classification accuracy rarely fell outside each image’s 90–99% scope, independent of cohort-dependent cerebrovascular structural variations. The classification ensemble was calibrated with high overall area rates under the ROC curve of 0.99–1.00 [0.97–1.00] in the test set across various study cohorts. Identifying an all-inclusive range of vessel components across controls, ICAS, and stroke patients, the accuracy rates of the prediction were: internal carotid arteries, 91–100%; middle cerebral arteries, 82–98%; anterior cerebral arteries, 88–100%; posterior cerebral arteries, 87–100%; and collections of superior, anterior inferior, and posterior inferior cerebellar arteries, 90–99% in the chunk-level classification. Using a voting algorithm on the queued classified vessel factors and anatomically post-processing the automatically classified results intensified quantitative prediction performance. We employed stochastic clustering and deep neural network ensembles. Ma-chine intelligence-assisted prediction of vessel structure allowed us to personalize quantitative predictions of various types of cerebral arterial structures, contributing to precise and efficient decisions regarding the cerebrovascular disease.

Background Although it is well known that the disordered brain provokes cardiac autonomic dysfunction, the detailed location of brain lesions related to cardiac function warrants further investigation. We aimed to elucidate the brain lesions topographically associated with left ventricular (LV) systolic function measured by myocardial strain in patients with acute ischemic stroke without preexisting primary cardiac dysfunction by using support vector regression lesion‐symptom mapping. Methods and Results Subjects were those with LV ejection fraction of 50% or more among patients with acute ischemic stroke registered in the Samsung Medical Center stroke registry between 2016 and 2017. To evaluate LV systolic performance and contractility, we measured LV ejection fraction and LV global and regional longitudinal strain using 2‐dimensional speckle‐tracking echocardiography. The association between stroke lesion location and cardiac strain was assessed using support vector regression lesion‐symptom mapping. Of a total of 776 patients, 286 subjects (mean age of 67.0 years, 65.4% men) were finally enrolled in this study. The mean global longitudinal strain was −17.0±3.4%, and the mean LV ejection fraction was 64.7±5.7%. The support vector regression lesion‐symptom mapping analysis revealed that the right insula and peri‐insular regions and left parietal cortex were associated with impaired LV global longitudinal strain in patients with acute ischemic stroke. In addition, impaired regional longitudinal strain showed topographical associations with these regions. Conclusions This study suggests that brain lesions in the right insula and peri‐insular regions and left parietal cortex are topographically associated with impaired LV strain in patients with acute ischemic stroke without preexisting cardiac dysfunction.

Background: Triglyceride (TG)/high-density lipoprotein cholesterol ratio (THR) is a marker of dyslipidemia, and high THR is associated with an increase in cardiovascular events. In the present study, whether THR was associated with various markers of cerebral vascular pathologies, atherosclerosis of major cerebral arteries, including large artery atherosclerosis (LAA) and cerebral small vessel disease (SVD), in neurologically healthy individuals was investigated.Methods: Vascular risk factors, brain magnetic resonance imaging (MRI) scans, and MR angiograms of 851 study subjects were evaluated. Findings of extracranial atherosclerosis (ECAS) and intracranial atherosclerosis (ICAS) were considered indices of LAA based on brain MR angiograms. The presence of silent lacunar infarct (SLI) and white matter hyperintensities (WMHs) were evaluated as indices of SVD based on brain MRIs.Results: Subjects with ICAS (odds ratio, 1.83; 95% confidence interval, 1.06–3.16; P = 0.03) were significantly more likely to have high THR tertile (THR > 2.06) than low THR tertile (THR < 1.37) after adjusting for cardiovascular risk factors. THR was higher in subjects with multiple ICAS lesions than in those with single ECAS or without ICAS lesions. Associations among THR tertiles in ECAS, SLI, and WMHs were not significant.Conclusion: In the present study, a positive association between high THR and the development of ICAS was observed in neurologically healthy participants.

Background and Objective: The blood neutrophil/lymphocyte ratio (NLR) is a marker of peripheral inflammation, with a high NLR associated with an increased risk of cardiovascular events and poor prognosis in ischemic stroke. However, few data are available on the differential impact of the blood NLR on different silent cerebral vascular pathologies, including cerebral large-artery atherosclerosis (LAA) and cerebral small-vessel disease (CSVD), in neurologically healthy individuals.Methods: We evaluated cardiovascular risk factors, brain magnetic resonance imaging (MRI), and MR angiography of 950 individuals without any neurological diseases. The study participants were divided into three groups according to NLR tertile (low, middle, and high). The presences of extracranial (EC) and intracranial (IC) atherosclerosis were considered to indicate LAA on brain MR angiography. The presences of silent lacunar infarction (SLI) and cerebral white matter hyperintensities (WMHs) were analyzed as indices of CSVD on brain MRI.Results: In univariate analysis, the high NLR tertile group showed a high prevalence of old age, hyperlipidemia, and renal dysfunction and higher fasting glucose. Multivariable logistic regression analysis revealed that indices of LAA (EC atherosclerosis [odds ratio: 1.88; 95% confidence interval: 1.14–3.09; p = 0.01] and IC atherosclerosis [odds ratio: 1.87; 95% confidence interval: 1.15–3.06; p = 0.01]) were more prevalent in the highest NLR tertile group than in the lowest NLR tertile group after adjustment for cardiovascular risk factors. However, no significant differences were found in the prevalence of CSVD indices (SLI and WMHs) among the three NLR tertile groups.Conclusions: A high NLR is associated with the development of cerebral LAA but not CSVD.

Background: The clinical significance of cerebral white matter hyperintensities (WMH) on brain magnetic resonance imaging (MRI) has recently increased, and recognized now as a risk factor for future stroke and dementia. High levels of plasma homocysteine (Hcyt) are associated with cerebral WMH. Recent studies suggest a different anatomy and physiology in the arteriolar system may be supplied to the periventricular and deep subcortical white matter. We hypothesize that plasma Hcyt levels have differing impacts on periventricular WMH (PVWMH) than on deep subcortical WMH (DSWMH).Methods: We evaluated plasma Hcyt levels from 937 neurologically healthy participants. The severity of PVWMH and DSWMH was evaluated by the use of a manual grading scale. Moderate to severe PVWMH and DSWMH levels were defined when the Fazekas score was two or three, respectively. Predominant PVWMH (pred-PVWMH) and predominant DSWMH (pred-DSWMH) were defined as having a difference of Fazekas score between PVWMH and DSWMH of two or more. Other confounding variables including age, sex, vascular risk factors, and estimated glomerular filtration rate (eGFR) were also analyzed.Results: Logistic regression revealed that, after adjusting for the confounding variables, PVWMH was associated with old age, hypertension, diabetes mellitus, low eGFR, and high plasma Hcyt levels. DSWMH was associated with old age, hypertension, and hypercholesterolemia but not with plasma Hcyt levels. Plasma Hcyt levels were associated with pred-PVWMH but not with pred-DSWMH.Conclusions: High plasma Hcyt levels are strongly associated with the development of PVWMH but not DSWMH. Our results suggest the possibility that different pathogeneses exist for PVWMH and DSWMH and that dysregulated Hcyt metabolism associated with the development of PVWMH.

Objectives: We aimed to investigate the demographics and medical management factors associated with dependence on hypnotics among outpatients with neurological disorders and insomnia. Methods: We reviewed electronic medical records of patients who received an initial hypnotic prescription between January 2014 and January 2016 and had later visited a neurological outpatient clinic before January 2018. We assessed patient demographics, the effectiveness of hypnotics, prescription periods, and hypnotic intake methods during the follow-up period. Results: Of 242 patients diagnosed with insomnia, we enrolled 114 patients (more women than men, at 61.4 versus 38.6%) who visited outpatient clinics regularly during the follow-up period. The mean age at onset was 65.8 ± 14.4 years. The most frequent neurological disorder was cerebrovascular disease, followed by neurodegenerative disease. During the 2-year period, 35.9% of participants remained hypnotics-free. Patients on zolpidem showed significantly greater insomnia improvement with hypnotic discontinuation than those on benzodiazepines and combination therapy (p=0.004). However, the type of hypnotics and demographic factors were not found to be independent risk factors. Multivariable analysis showed that longer periods between regular visits and a lower ratio of receiving number of pills to the time interval (days) between regular visits were independent risk factors for dependence on hypnotics. Conclusions: We found that low-dose and/or intermittent intake of hypnotics as well as frequent doctor visits could prevent dependence on hypnotics. It is important to establish the best practical guidelines for medical hypnotics management in outpatient primary care settings, including neurological clinics. [ABSTRACT FROM AUTHOR]