Reduced Alcohol Consumption and Major Adverse Cardiovascular Events Among Individuals With Previously High Alcohol Consumption.

Importance: Cardiovascular benefits of mild to moderate alcohol consumption need to be validated in the context of behavioral changes. The benefits of reduced alcohol consumption among people who drink heavily across different subtypes of cardiovascular disease (CVD) are unclear. Objective: To investigate the association between reduced alcohol consumption and risk of major adverse cardiovascular events (MACEs) in individuals who drink heavily across different CVD subtypes. Design, Setting, and Participants: This cohort study analyzed data from the Korean National Health Insurance Service-Health Screening database and self-reported questionnaires. The nationally representative cohort comprised Korean citizens aged 40 to 79 years who had national health insurance coverage on December 31, 2002, and were included in the 2002 to 2003 National Health Screening Program. People who drank heavily who underwent serial health examinations over 2 consecutive periods (first period: 2005-2008; second period: 2009-2012) were included and analyzed between February and May 2023. Heavy drinking was defined as more than 4 drinks (56 g) per day or more than 14 drinks (196 g) per week for males and more than 3 drinks (42 g) per day or more than 7 drinks (98 g) per week for females. Exposures: Habitual change in heavy alcohol consumption during the second health examination period. People who drank heavily at baseline were categorized into 2 groups according to changes in alcohol consumption during the second health examination period as sustained heavy drinking or reduced drinking. Main Outcomes and Measures: The primary outcome was the occurrence of MACEs, a composite of nonfatal myocardial infarction or angina undergoing revascularization, any stroke accompanied by hospitalization, and all-cause death. Results: Of the 21 011 participants with heavy alcohol consumption at baseline (18 963 males [90.3%]; mean [SD] age, 56.08 [6.16] years) included in the study, 14 220 (67.7%) sustained heavy drinking, whereas 6791 (32.2%) shifted to mild to moderate drinking. During the follow-up of 162 378 person-years, the sustained heavy drinking group experienced a significantly higher incidence of MACEs than the reduced drinking group (817 vs 675 per 100 000 person-years; log-rank P = .003). Reduced alcohol consumption was associated with a 23% lower risk of MACEs compared with sustained heavy drinking (propensity score matching hazard ratio [PSM HR], 0.77; 95% CI, 0.67-0.88). These benefits were mostly accounted for by a significant reduction in the incidence of angina (PSM HR, 0.70; 95% CI, 0.51-0.97) and ischemic stroke (PSM HR, 0.66; 95% CI, 0.51-0.86). The preventive attributes of reduced alcohol intake were consistently observed across various subgroups of participants. Conclusions and Relevance: Results of this cohort study suggest that reducing alcohol consumption is associated with a decreased risk of future CVD, with the most pronounced benefits expected for angina and ischemic stroke.

New Directions in Infection-Associated Ischemic Stroke.

The relationship between infections and stroke has not been fully characterized, probably delaying the development of specific treatments. This narrative review addresses mechanisms of stroke linked to infections, including hypercoagulability, endothelial dysfunction, vasculitis, and impaired thrombolysis. SARS-CoV-2, the virus that causes COVID-19, may promote the development of stroke, which may represent its most severe neurological complication. The development of specific therapies for infection-associated stroke remains a profound challenge. Perhaps the most important remaining issue is the distinction between infections that trigger a stroke versus infections that are truly incidental. This distinction likely requires the establishment of appropriate biomarkers, candidates of which are elevated levels of fibrin D-dimer and anticardiolipin/antiphospholipid antibodies. These candidate biomarkers might have potential use in identifying pathogenic infections preceding stroke, which is a precursor to establishing specific therapies for this syndrome.

Predicting short-term outcomes in atrial-fibrillation-related stroke using machine learning.

Background: Prognostic prediction and the identification of prognostic factors are critical during the early period of atrial-fibrillation (AF)-related strokes as AF is associated with poor outcomes in stroke patients. Methods: Two independent datasets, namely, the Korean Atrial Fibrillation Evaluation Registry in Ischemic Stroke Patients (K-ATTENTION) and the Korea University Stroke Registry (KUSR), were used for internal and external validation, respectively. These datasets include common variables such as demographic, laboratory, and imaging findings during early hospitalization. Outcomes were unfavorable functional status with modified Rankin scores of 3 or higher and mortality at 3 months. We developed two machine learning models, namely, a tree-based model and a multi-layer perceptron (MLP), along with a baseline logistic regression model. The area under the receiver operating characteristic curve (AUROC) was used as the outcome metric. The Shapley additive explanation (SHAP) method was used to evaluate the contributions of variables. Results: Machine learning models outperformed logistic regression in predicting both outcomes. For 3-month unfavorable outcomes, MLP exhibited significantly higher AUROC values of 0.890 and 0.859 in internal and external validation sets, respectively, than those of logistic regression. For 3-month mortality, both machine learning models exhibited significantly higher AUROC values than the logistic regression for internal validation but not for external validation. The most significant predictor for both outcomes was the initial National Institute of Health and Stroke Scale. Conclusion: The explainable machine learning model can reliably predict short-term outcomes and identify high-risk patients with AF-related strokes.

A multimodal screening system for elderly neurological diseases based on deep learning.

In this paper, we propose a deep-learning-based algorithm for screening neurological diseases. We proposed various examination protocols for screening neurological diseases and collected data by video-recording persons performing these protocols. We converted video data into human landmarks that capture action information with a much smaller data dimension. We also used voice data which are also effective indicators of neurological disorders. We designed a subnetwork for each protocol to extract features from landmarks or voice and a feature aggregator that combines all the information extracted from the protocols to make a final decision. Multitask learning was applied to screen two neurological diseases. To capture meaningful information about these human landmarks and voices, we applied various pre-trained models to extract preliminary features. The spatiotemporal characteristics of landmarks are extracted using a pre-trained graph neural network, and voice features are extracted using a pre-trained time-delay neural network. These extracted high-level features are then passed onto the subnetworks and an additional feature aggregator that are simultaneously trained. We also used various data augmentation techniques to overcome the shortage of data. Using a frame-length staticizer that considers the characteristics of the data, we can capture momentary tremors without wasting information. Finally, we examine the effectiveness of different protocols and different modalities (different body parts and voice) through extensive experiments. The proposed method achieves AUC scores of 0.802 for stroke and 0.780 for Parkinson's disease, which is effective for a screening system.

Incidence and risk of stroke in Korean patients with congenital heart disease.

OBJECTIVES: The incidence and risk of ischemic stroke (IS) and hemorrhagic stroke (HS) in Korean patients with CHD have not been reported, therefore, we aimed to investigate this. MATERIALS AND METHODS: Participants were selected from the Korean National Health Insurance Service benefit records from 2006-2017. Cases were extracted using diagnosis codes related to CHD. Controls without CHD were selected through age- and sex-matched random sampling at a 1:10 ratio. RESULTS: The case and control groups included 232,203 and 3,024,633 participants, respectively. The median (interquartile range) follow-up period was 7.28 (3.59-8.73) years. The incidence rates of IS and HS per 100,000 person-years were much higher in cases than in controls (IS: 135 vs. 47; HS: 41.7 vs. 24.9). After adjusting for confounders, CHD was a risk factor for IS and HS (subdistribution HR; 1.96 and 1.71, respectively). In patients with CHD, the following risk factors were identified: diabetes, heart failure, and atrial fibrillation for any stroke; hypertension, atrial septal defects, and use of antiplatelet agents for IS only; and coronary artery bypass graft surgery for HS only. CONCLUSIONS: Korean patients with CHD have a high risk of stroke. A personalized preventive approach is needed to reduce the incidence of stroke in this population.

D-dimer to fibrinogen ratio predicts early neurological deterioration in ischemic stroke with atrial fibrillation.

INTRODUCTION: The D-dimer to fibrinogen ratio (DFR) is a good indicator of clot-producing activity in thrombotic disease, but its clinical usefulness in stroke patients with nonvalvular atrial fibrillation (NVAF) has not been studied. We evaluated the association between the DFR and early neurological deterioration (END) in acute ischemic stroke (AIS) patients with NVAF. METHODS: We included consecutive AIS patients with NVAF between 2013 and 2015 from the registry of a real-world prospective cohort from 11 large centers in South Korea. END was defined as an increase ≥2 in the total NIHSS score or ≥ 1 in the motor NIHSS score within the first 72 h of admission. The DFR was calculated as follows: DFR = D-dimer (mg/L)/fibrinogen (mg/dL) x 100. RESULTS: A total of 1018 AIS patients with NVAF were evaluated. In multivariable logistic regression analysis, the highest DFR tertile was closely associated with END (adjusted odds ratio [aOR] = 2.14, 95 % confidence interval [CI]: 1.24-3.69). Hypertension (aOR = 1.71, 95 % CI: 1.09-2.70), initial NIHSS score (aOR = 1.05, 95 % CI: 1.02-1.07) and use of anticoagulants (aOR = 0.41, 95 % CI: 0.28-0.60) were also correlated with END. In addition to END, the DFR was correlated with discharge NIHSS and modified Rankin Scale (mRS) scores and the 3-month mRS score. CONCLUSIONS: High DFR values were associated with END in AIS patients with NVAF. As the DFR is an indicator directly related to the main pathological mechanism of NVAF patients (fibrinolysis and coagulation), it may be useful in predicting their prognosis.

Zebrafish thrombosis models according to the location of thrombus formation.

Background: Ischemic stroke becomes a major cause of death and disability. It can develop due to intravascular or cardiac thromboemboli. Animal models that reflect diverse stroke mechanisms remain under development. Using photochemical thrombosis, we developed a feasible zebrafish model according to the thrombus location (intracerebral vs. intracardiac). We validated the model using real-time imaging and thrombolytic agent. Methods: We used transgenic zebrafish larvae (flk:gfp), which express specific fluorescence in endothelial cells. We injected Rose Bengal, a photosensitizer as a mixture of photosensitizer, and a fluorescent agent into the cardinal vein of the larvae. We then evaluated real-time thrombosis in vivo by inducing thrombosis through exposure to a confocal laser (560 nm) and staining the blood flow (RITC-dextran). We validated intracerebral and intracardiac thrombotic models with checking the activity of tissue plasminogen activator (tPA). Results: The photochemical agent induced the formation of intracerebral thrombi in transgenic zebrafish. Real-time imaging techniques confirmed the formation of the thrombi. The damage and apoptosis of the vessel's endothelial cells were seen in the in vivo model. An intracardiac thrombosis model was developed by the same method using photothrombosis, and the model was validated through thrombolysis by tPA. Conclusions: We developed and validated two zebrafish thrombosis models that are readily available, cost-effective, and intuitive for assessing the efficacy of thrombolytic agents. These models can be used for a broad spectrum of future studies, such as screening and efficacy assessment of new antithrombotic agents.

Appendicular Skeletal Muscle Mass Associated with Sarcopenia as a Predictor of Poor Functional Outcomes in Ischemic Stroke.

Purpose: Several studies have examined the clinical impact of poststroke and stroke-related sarcopenia on stroke recovery. However, few studies have investigated the effect of sarcopenia detected shortly after stroke on functional prognosis. We predicted functional outcomes using early screening for sarcopenia in patients with acute ischemic stroke. We also examined the effect of sarcopenia detected shortly after stroke on functional prognosis. Patients and Methods: Patients diagnosed with acute ischemic stroke within 2 days of symptom onset were consecutively enrolled at a tertiary university hospital. Appendicular skeletal muscle mass (ASM) was measured using dual-energy X-ray absorptiometry during early hospitalization. Sarcopenia was diagnosed based on low ASM and strength criteria of the Asian Working Group for Sarcopenia (AWGS) and European Working Group on Sarcopenia in Older People (EWGSOP2). The primary outcome was poor functional outcome, defined as a modified Rankin score of 4-6 and all-cause mortality at 3 months. Results: Of the 653 patients, 214 (32.8%) and 174 (26.6%) had sarcopenia according to the AWGS and EWGSOP2 criteria, respectively. Irrespective of the definition, the sarcopenia group had a significantly higher proportion of patients with poor functional outcomes and all-cause mortality. Multivariate logistic regression analysis revealed that height-adjusted ASM was independently associated with poor functional outcomes (odds ratio: 0.61; 95% confidence interval: 0.40-0.91; P <0.005), and they were negatively correlated. However, the association between 3-month mortality, skeletal muscle mass, and sarcopenia was not sustained in multivariate analyses. Conclusion: Height-adjusted ASM associated with sarcopenia is a potential predictor of poor functional outcomes at 3 months in patients with acute stroke. However, owing to the limitations of this study, further research is required to confirm these findings.

Stroke-Specific Predictors of Major Bleeding in Anticoagulated Patients With Stroke and Atrial Fibrillation: A Nationwide Multicenter Registry-Based Study.

BACKGROUND AND PURPOSE: The congestive heart failure, hypertension, age, diabetes, previous stroke/transient ischemic attack (CHA2DS2-VASc) and hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio, elderly, drugs/alcohol (HAS-BLED) scores have been validated in estimating the risks of ischemic stroke and major bleeding, respectively, in patients with atrial fibrillation (AF). This study investigated stroke-specific predictors of major bleeding in patients with stroke and AF who were taking oral anticoagulants (OACs). METHODS: Subjects were selected from patients enrolled in the Korean ATrial fibrillaTion EvaluatioN regisTry in Ischemic strOke patieNts (K-ATTENTION) nationwide multicenter registry between 2013 and 2015. Patients were excluded if they were not taking OACs, had no brain imaging data, or had intracranial bleeding directly related to the index stroke. Major bleeding was defined according to International Society of Thrombosis and Haemostasis criteria. Cox regression analyses were performed to assess the associations between clinical variables and major bleeding and Kaplan-Meier estimates were performed to analyze event-free survival. RESULTS: Of a total of 3,213 patients, 1,414 subjects (mean age of 72.6 years, 52.5% males) were enrolled in this study. Major bleeding was reported in 34 patients during the median follow-up period of 1.73 years. Multivariable analysis demonstrated that initial National Institutes of Health Stroke Scale scores (hazard ratio [HR] 1.07, p=0.006), hypertension (HR 3.18, p=0.030), persistent AF type (HR 2.51, p=0.016), and initial hemoglobin level (HR 0.74, p=0.001) were independently associated with major bleeding risk. Except for hypertension, these associations remained significant after adjusting for the HAS-BLED score. Intracranial atherosclerosis presented a trend of association without statistical significance (HR 2.21, p=0.050). CONCLUSIONS: This study found that major bleeding risk was independently associated with stroke-specific factors in anticoagulated patients with stroke and AF. This has the clinical implication that baseline characteristics of patients with stroke and AF should be considered in secondary prevention, which would bring the net clinical benefit of balancing recurrent stroke prevention with minimal bleeding complications.

Obesity paradox and stroke outcomes according to stroke subtype: a propensity score-matched analysis.

OBJECTIVE: Obesity has traditionally been considered a risk factor for ischemic stroke. However, some clinical observations have reported a complex relationship between patients who are overweight or obese with paradoxically better stroke outcomes. Stroke subtypes have differing distributions of risk factors, so this study aimed to explain the relationship between body mass index (BMI) and functional prognosis according to stroke subtype. METHODS: A prospective institutional database on stroke was accessed between March 2014 and December 2021, and consecutive patients with ischemic stroke were retrospectively selected. BMI was categorized into five groups (underweight, normal weight, overweight, obese, and morbid obesity). The outcome of interest in this study was the modified Rankin Scale (mRS) at 90 d, which was divided into favorable (mRS = 0-2) and unfavorable (mRS ≥ 3) groups. The relationship between functional outcome and BMI was analyzed according to stroke subtype. RESULTS: Among 2779 patients with stroke, 913 (32.9%) had unfavorable outcomes. After a propensity score-matched analysis, obesity was inversely associated with unfavorable outcomes (adjusted odds ratio [aOR] = 0.61, 95% confidence interval [95% CI]: 0.46-0.80) in all patients with stroke. Among the stroke subtypes, overweight (aOR = 0.38, 95% CI: 0.20-0.74) and obese (aOR = 0.40, 95% CI: 0.21-0.76) groups were inversely associated with unfavorable outcomes in the cardioembolism subtype. Obesity (aOR = 0.55, 95% CI: 0.32-0.95) was inversely associated with unfavorable outcomes in the small vessel disease subtype. There was no significant relationship between stroke outcome and BMI classification in the large artery disease subtype. CONCLUSIONS: These findings suggest that the obesity paradox in ischemic stroke outcomes might differ according to the stroke subtype.

Moderate-Intensity Rosuvastatin Plus Ezetimibe Versus High-Intensity Rosuvastatin for Target Low-Density Lipoprotein Cholesterol Goal Achievement in Patients With Recent Ischemic Stroke: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Moderate-intensity statin plus ezetimibe versus high-intensity statin alone may provide a greater low-density lipoprotein cholesterol (LDL-C) reduction in patients with recent ischemic stroke. METHODS: This randomized, open-label, controlled trial assigned patients with recent ischemic stroke <90 days to rosuvastatin/ezetimibe 10/10 mg once daily (ROS10/EZT10) or to rosuvastatin 20 mg once daily (ROS20). The primary endpoint was LDL-C reduction ≥50% from baseline at 90 days. Key secondary endpoints were LDL-C <70 mg/dL and multiple lipid goal achievement, and composite of major vascular events. RESULTS: Of 584 randomized, 530 were included in the modified intention-to-treat analysis. The baseline LDL-C level was 130.2±34.7 mg/dL in the ROS10/EZT10 group and 131.0±33.9 mg/dL in the ROS20 group. The primary endpoint was achieved in 198 patients (72.5%) in the ROS10/EZT10 group and 148 (57.6%) in the ROS20 group (odds ratio [95% confidence interval], 1.944 [1.352-2.795]; P= 0.0003). LDL-C level <70 mg/dL was achieved in 80.2% and 65.4% in the ROS10/EZT10 and ROS20 groups (P=0.0001). Multiple lipid goal achievement rate was 71.1% and 53.7% in the ROS10/EZT10 and ROS20 groups (P<0.0001). Major vascular events occurred in 1 patient in the ROS10/EZT10 group and 9 in the ROS20 group (P=0.0091). The adverse event rates did not differ between the two groups. CONCLUSION: Moderate-intensity rosuvastatin plus ezetimibe was superior to high-intensity rosuvastatin alone for intensive LDL-C reduction in patients with recent ischemic stroke. With the combination therapy, more than 70% of patients achieved LDL-C reduction ≥50% and 80% had an LDL-C <70 mg/dL at 90 days.

Major Adverse Cardiovascular Events in Korean Congenital Heart Disease Patients: A Nationwide Age- and Sex-Matched Case-Control Study.

PURPOSE: Congenital heart disease (CHD) is a known risk factor for acquired cardiovascular and cerebrovascular diseases. However, available evidence on CHD is limited mostly to Western populations. This study aimed to evaluate the prevalence of vascular events and all-cause mortality in Korean patients with CHD and to further corroborate CHD as a predictor of vascular events and all-cause mortality. MATERIALS AND METHODS: The claims data of the Korean National Health Insurance Service (NHIS) were retrospectively reviewed. Information regarding diagnostic codes, comorbidities, medical services, income level, and residential area was also collected. Outcomes of interest included stroke, myocardial infarction (MI), all-cause mortality, and major adverse cardiovascular events (MACE). RESULTS: We included 232203 patients with CHD and 3024633 individuals without CHD as a control group through age- and sex-matched 1:10 random sampling. The prevalences of hypertension, congestive heart failure, ischemic heart disease, hyperlipidemia, and atrial fibrillation were significantly higher in the CHD group, which had a more than two-fold higher incidence of vascular events and all-cause mortality, than in the group without CHD. Multivariable models demonstrated that CHD was a significant risk factor for stroke, MI, all-cause mortality, and MACE. CONCLUSION: In conclusion, this nationwide study demonstrates that Korean patients with CHD have a high incidence of comorbidities, vascular events, and mortality. CHD has been established as an important predictor of cardiovascular events. Further studies are warranted to identify high-risk patients with CHD and related factors to prevent vascular events.

Deep-Learning-Based Stroke Screening Using Skeleton Data from Neurological Examination Videos.

According to the Korea Institute for Health and Social Affairs, in 2017, the elderly, aged 65 or older, had an average of 2.7 chronic diseases per person. The concern for the medical welfare of the elderly is increasing due to a low birth rate, an aging population, and the lack of medical personnel. The demand for services that take user age, cognitive capacity, and difficulty into account is rising. As a result, there is an increased demand for smart healthcare systems that can lower hospital admissions and offer patients individualized care. This has motivated us to develop an AI system that can easily screen and manage neurological diseases through videos. As neurological diseases can be diagnosed by visual analysis to some extent, in this study, we set out to estimate the possibility of a person having a neurological disease from videos. Among neurological diseases, we focus on stroke because it is a common condition in the elderly population and results in high mortality and morbidity worldwide. The proposed method consists of three steps: (1) transforming neurological examination videos into landmark data, (2) converting the landmark data into recurrence plots, and (3) estimating the possibility of a stroke using deep neural networks. Major features, such as the hand, face, pupil, and body movements of a person are extracted from test videos taken under several neurological examination protocols using deep-learning-based landmark extractors. Sequences of these landmark data are then converted into recurrence plots, which can be interpreted as images. These images can be fed into convolutional neural networks to classify stroke using feature-fusion techniques. A case study of the application of a disease screening test to assess the capability of the proposed method is presented.

Plasma Total Homocysteine Level Is Related to Unfavorable Outcomes in Ischemic Stroke With Atrial Fibrillation.

Background Unlike patients with stroke caused by other mechanisms, the effect of elevated plasma total homocysteine (tHcy) on the prognosis of patients with both ischemic stroke and atrial fibrillation (AF) is unknown. This study aimed to evaluate the association between tHcy level and the functional outcome of patients with AF-related stroke. Methods and Results We included consecutive patients with AF-related stroke between 2013 and 2015 from the registry of a real-world prospective cohort from 11 large centers in South Korea. A 3-month modified Rankin Scale score ≥3 was considered an unfavorable outcome. Since tHcy is strongly affected by renal function, we performed a subgroup analysis according to the presence of renal dysfunction. A total of 910 patients with AF-related stroke were evaluated (mean age, 73 years; male sex, 56.0%). The mean tHcy level was 11.98±8.81 µmol/L. In multivariable analysis, the tHcy level (adjusted odds ratio, 1.04; 95% CI, 1.01-1.07, per 1 µmol/L) remained significantly associated with unfavorable outcomes. In the subgroup analysis based on renal function, tHcy values above the cutoff point (≥14.60 µmol/L) showed a close association with the unfavorable outcome only in the normal renal function group (adjusted odds ratio, 3.10; 95% CI, 1.60-6.01). In patients with renal dysfunction, tHcy was not significantly associated with the prognosis of AF-related stroke. Conclusions A higher plasma tHcy level was associated with unfavorable outcomes in patients with AF-related stroke. This positive association may vary according to renal function but needs to be verified in further studies.

FIB-4 index and liver fibrosis are risk factors for long-term outcomes in atrial fibrillation-related stroke.

OBJECTIVE: Liver fibrosis (LF) is associated with a poor prognosis in patients with ischemic stroke (IS). We aimed to assess whether LF affects long-term outcomes in patients with atrial fibrillation-related stroke or such effects vary according to sex. METHODS: We conducted a multicenter prospective cohort study of Korean patients with atrial fibrillation-related IS. We calculated the fibrosis-4 (FIB-4) index, and LF degree was categorized into two groups (non-advanced vs. advanced) based on the FIB-4 index. Recurrent IS, major adverse cardiac events (MACEs), and all-cause mortality were evaluated using Cox proportional hazard model. RESULTS: A total of 2897 patients were included; the median age was 75 (interquartile range 68-80) years, and 51.8% were men. The median follow-up period was 16.3 months. Of these patients, 23% had advanced LF indicated by FIB-4 index. Multivariable analysis in all populations demonstrated that the FIB-4 index and advanced LF were significantly associated with MACEs and all-cause mortality but not with recurrent IS. Furthermore, a sex disparity was observed in the outcomes of the patients. A high FIB-4 index in men was a significant predictor of recurrent IS [subdistribution hazard ratio (95% confidence interval): 1.08 (1.02-1.14)]. However, the significance of advanced LF disappeared in MACEs in women and in all-cause mortality in men. CONCLUSION: The FIB-4 index and advanced LF indicated by FIB-4 index are independent prognostic factors for long-term outcomes in Asian patients with atrial fibrillation-related IS. However, these predictors may contribute differently to patient outcomes depending on the sex.

Antiplatelet regimens after ischemic stroke or transient ischemic attack: a systematic review and updated network meta-analysis.

Background: It is still uncertain which antiplatelet regimen had the greatest net clinical benefit in patients who have suffered a transient ischemic attack or non-cardioembolic ischemic stroke, and it is necessary to choose the optimal regimen according to the clinical situation. Methods: We utilized 3 databases of Medline, Embase, and the Cochrane Central Register of Controlled Trials to find randomized controlled trials that met our criteria, and performed network meta-analyses in recurrent stroke, composite outcomes, major bleeding events, recurrent ischemic stroke, and all bleeding events. Three-dimensional clustered rank plots were used to obtain the net clinical benefit. Subgroup analyses were performed according to the symptom-onset-to-treatment time (<72 and >72 h), stroke subtypes (large artery atherosclerosis and small vessel occlusion), and dual antiplatelet agent treatment duration. Results: A total of 69 trials were enrolled. Cilostazol was associated with a lower risk of recurrent stroke, major bleeding events, composite outcomes, recurrent ischemic stroke, and all bleeding events compared to low to medium dose aspirin. The three-dimensional rank plot showed that cilostazol had the highest net clinical benefit. The combination of aspirin plus clopidogrel had greater efficacy in the <72 h after stroke onset and large artery atherosclerosis subgroups, and when it was restricted to1 month of use major bleeding risk was not higher than aspirin. The combination of aspirin plus dipyridamole had greater efficacy and safety comparable to aspirin in terms of small vessel occlusion. Conclusions: The efficacy and safety profiles among antiplatelet regimens may differ according to clinical situation, although cilostazol, aspirin plus clopidogrel, and aspirin plus dipyridamole may be considered as preferable options.

Predicting Stenosis Aggravation in Follow-Up High-Resolution Magnetic Resonance Images of Patients with Intracranial Atherosclerosis.

BACKGROUND: High-resolution magnetic resonance imaging (HRMRI) can provide information on the histopathological characteristics of intracranial atherosclerotic lesions causing arterial stenosis; however, its clinical application in intracranial atherosclerosis lacks standardization for predicting stenosis. Therefore, this study investigated the characteristics of HRMRI that can predict progression based on comparisons of follow-up HRMRI. METHODS: We retrospectively enrolled patients who underwent HRMRI within 7 days of symptom onset to evaluate the characteristics associated with intracranial stenotic lesions. Among them, patients diagnosed with severe stenosis due to atherosclerosis and who underwent follow-up HRMRI 12-24 months after initial HRMRI were included in the final study. We analyzed distinct features, such as stenosis aggravation, the presence of initial plaque enhancement, increment of plaque enhancement, the existence of both eccentric and concentric plaques, and the presence of initial intraplaque hematoma on initial and follow-up HRMRI. RESULTS: Among 442 patients who underwent HRMRI for severe stenosis due to atherosclerosis, 35 underwent follow-up HRMRI 12-24 months later. Patients with stenosis aggravation showed a higher incidence of plaque enhancement (87.5% vs. 3.7%, p < 0.001) and the presence of both concentric and eccentric plaques (75.0% vs. 11.1%; p = 0.001). The area under the curve for the increment of plaque enhancement was 0.92 (95% confidence interval [CI] 0.78-1.00, p ≤ 0.001), while that for the presence of both concentric and eccentric plaques was 0.82 (95% CI 0.63-1.00, p < 0.007). CONCLUSIONS: The presence of both concentric and eccentric plaques and an increase in plaque enhancement were the strongest predictors of aggravation of intracranial artery stenosis.

Synergy Through Integration of Wearable EEG and Virtual Reality for Mild Cognitive Impairment and Mild Dementia Screening.

Virtual reality (VR) technologies have shown promising potential in the early diagnosis of dementia by enabling accessible and regular assessment. However, previous VR studies were restricted to the analysis of behavioral responses, so information about degenerated brain dynamics could not be directly acquired. To address this issue, we provide a cognitive impairment (CI) screening tool based on a wearable EEG device integrated into a VR platform. Subjects were asked to use a hardware setup consisting of a frontal six-channel EEG device mounted on a VR device and to perform four cognitive tasks in VR. Behavioral response profiles and EEG features were extracted during the tasks, and classifiers were trained on extracted features to differentiate subjects with CI from healthy controls (HCs). Notably, the performance of the patient classification consistently improved when EEG characteristics measured during cognitive tasks were additionally included in feature attributes than when only the task scores or resting-state EEG features were used, suggesting that our protocol provides discriminative information for screening. These results propose that the integration of EEG devices into a VR framework could emerge as a powerful and synergistic strategy for constructing an easily accessible EEG-based CI screening tool.