[Classification of childhood arterial ischemic stroke].

The etiology of childhood arterial ischemic stroke is complex, and identifying the underlying cause is crucial for optimizing treatment and preventing recurrence. Currently, the classification methods for childhood arterial ischemic stroke are largely based on data from international studies, but a unified consensus have not yet been reached. This paper reviews the existing classification methods and their subtype definitions, and points out some doubts and ambiguities. On this basisi, combined with the data collected by Beijing Children's Hospital on Chinese children with arterial ischemic stroke, a new classification method (COIST) was proposed according to the etiology and pathogenesis, namely: inflammation (I), abnormal vascular structure (S), thrombophilia (T), heart disease (C), other identifiable causes (O), and uncertain causes; and various subtypes are listed. It is hoped that this new classification method can attract the attention and discussion of domestic colleagues, with the aim of further refinement, in order to help clinicians better understand and quickly identify the etiologies of childhood ischemic stroke.

Derivation and Validation of ICD-10 Codes for Identifying Incident Stroke.

Importance: Claims data with International Statistical Classification of Diseases, Tenth Revision (ICD-10) codes are routinely used in clinical research. However, the use of ICD-10 codes to define incident stroke has not been validated against expert-adjudicated outcomes in the US population. Objective: To develop and validate the accuracy of an ICD-10 code list to detect incident stroke events using Medicare inpatient fee-for-service claims data. Design, Setting, and Participants: This cohort study used data from 2 prospective population-based cohort studies, the Atherosclerosis Risk in Communities (ARIC) study and the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, and included participants aged 65 years or older without prior stroke who had linked Medicare claims data. Stroke events in the ARIC and REGARDS studies were identified via active surveillance and adjudicated by expert review. Medicare-linked ARIC data (2016-2018) were used to develop a list of ICD-10 codes for incident stroke detection. The list was validated using Medicare-linked REGARDS data (2016-2019). Data were analyzed from September 1, 2022, through September 30, 2023. Exposures: Stroke events detected in Medicare claims vs expert-adjudicated stroke events in the ARIC and REGARDS studies. Main Outcomes and Measures: The main outcomes were sensitivity and specificity of incident stroke detection using ICD-10 codes. Results: In the ARIC study, there were 110 adjudicated incident stroke events among 5194 participants (mean [SD] age, 80.1 [5.3] years) over a median follow-up of 3.0 (range, 0.003-3.0) years. Most ARIC participants were women (3160 [60.8%]); 993 (19.1%) were Black and 4180 (80.5%) were White. Using the primary diagnosis code on a Medicare billing claim, the ICD-10 code list had a sensitivity of 81.8% (95% CI, 73.3%-88.5%) and a specificity of 99.1% (95% CI, 98.8%-99.3%) to detect incident stroke. Using any diagnosis code on a Medicare billing claim, the sensitivity was 94.5% (95% CI, 88.5%-98.0%) and the specificity was 98.4% (95% CI, 98.0%-98.8%). In the REGARDS study, there were 140 adjudicated incident strokes among 6359 participants (mean [SD] age, 75.8 [7.0] years) over a median follow-up of 4.0 (range, 0-4.0) years. More than half of the REGARDS participants were women (3351 [52.7%]); 1774 (27.9%) were Black and 4585 (72.1%) were White. For the primary diagnosis code, the ICD-10 code list had a sensitivity of 70.7% (95% CI, 63.2%-78.3%) and a specificity of 99.1% (95% CI, 98.9%-99.4%). For any diagnosis code, the ICD-10 code list had a sensitivity of 77.9% (95% CI, 71.0%-84.7%) and a specificity of 98.9% (95% CI, 98.6%-99.2%). Conclusions and Relevance: These findings suggest that ICD-10 codes could be used to identify incident stroke events in Medicare claims with moderate sensitivity and high specificity.

Etiological Subclassification of Stroke in Older People ≥80 Years Compared to Younger People: A Systematic Review and Meta-Analysis.

BACKGROUND: Due to the rapid growth of the world´s oldest population, the number of older persons with stroke is expected to rise. Knowledge of stroke etiology is essential to offer personalized and equal health care across age groups. The present systematic review aimed to investigate the prevalence of etiological subtypes of ischemic and hemorrhagic stroke in older compared to younger people. METHODS: MEDLINE, Embase, Cochrane, Epistemonikos, and Cinahl were systematically searched for studies regarding etiological classification in people ≥80 years compared to those <80 years with ischemic or hemorrhagic stroke. RESULTS: Out of 28 441 identified articles, eight met the inclusion criteria. In total, 8223 individuals were included in meta-analyses, of whom 2997 were 80 years or older. We demonstrated a higher prevalence of cardioembolic stroke in people ≥80 years OR 1.68 (95% CI, 1.12-2.53). Small vessel disease was significantly less common in older people OR .64 (95% CI, .50-.81). Regarding large vessel disease, no statistically significant difference between the two groups was shown OR 1.05 (95% CI, .77-1.43). CONCLUSION: In people ≥80 years, cardioembolic stroke is more common, and small vessel disease less common compared to people <80 years. Overall, the results have to be interpreted with caution due to few studies. Large studies using validated classification systems are needed.

A systematic review of the incidence and outcomes of ICD-11 defined stroke.

BACKGROUND: The World Health Organisation has expanded the definition of stroke to include people with symptoms less than 24 h if they have evidence of stroke on neuroimaging. The impact is that people previously diagnosed as having a transient ischaemic attack (TIA) would now be considered to have had a stroke. This change will impact incidence and outcomes of stroke and increase eligibility for secondary prevention. We aimed to evaluate the new ICD-11 criteria retrospectively to previous TIA studies to understand the change in incidence and outcomes of this type of stroke. METHODS: We conducted a systematic review of observational studies of the incidence and outcomes of clinically defined TIA. We searched PubMed, EMBASE, and Google Scholar from inception to 23rd May 2023. Study quality was assessed using a risk of bias tool for prevalence studies. FINDINGS: Our review included 25 studies. The rate of scan positivity for stroke among those with clinically defined TIA was 24 %, (95 % CI, 16-33 %) but with high heterogeneity (I2 = 100 %, p <0.001). Sensitivity analyses provided evidence that heterogeneity could be explained by methodology and recruitment method. The scan positive rate when examining only studies at low risk of bias was substantially lower, at 13 % (95 % CI, 11-15 %, I2 = 0, p = 0.77). We estimate from population-based incidence studies that ICD-11 would result in an increase stroke incidence between 4.8 and 10.5 per 100,000 persons/year. Of those with DWI-MRI evidence of stroke, 6 % (95 % CI, 3-11 %) developed a recurrent stroke in the subsequent 90 days, but with substantial heterogeneity (I2 = 67 %, p = 0.02). CONCLUSION: The impact of the ICD-11 change in stroke definition on incidence and outcomes may have been overestimated by individual studies. Community-based stroke services with access to DWI MRI are likely to accurately diagnose greater numbers of people with mild ICD-11 stroke, increasing access to effective prevention.

LVONet: automatic classification model for large vessel occlusion based on the difference information between left and right hemispheres.

Objective.Stroke is a highly lethal condition, with intracranial vessel occlusion being one of its primary causes. Intracranial vessel occlusion can typically be categorized into four types, each requiring different intervention measures. Therefore, the automatic and accurate classification of intracranial vessel occlusions holds significant clinical importance for assessing vessel occlusion conditions. However, due to the visual similarities in shape and size among different vessels and variations in the degree of vessel occlusion, the automated classification of intracranial vessel occlusions remains a challenging task. Our study proposes an automatic classification model for large vessel occlusion (LVO) based on the difference information between the left and right hemispheres.Approach.Our approach is as follows. We first introduce a dual-branch attention module to learn long-range dependencies through spatial and channel attention, guiding the model to focus on vessel-specific features. Subsequently, based on the symmetry of vessel distribution, we design a differential information classification module to dynamically learn and fuse the differential information of vessel features between the two hemispheres, enhancing the sensitivity of the classification model to occluded vessels. To optimize the feature differential information among similar vessels, we further propose a novel cooperative learning loss function to minimize changes within classes and similarities between classes.Main results.We evaluate our proposed model on an intracranial LVO data set. Compared to state-of-the-art deep learning models, our model performs optimally, achieving a classification sensitivity of 93.73%, precision of 83.33%, accuracy of 89.91% and Macro-F1 score of 87.13%.Significance.This method can adaptively focus on occluded vessel regions and effectively train in scenarios with high inter-class similarity and intra-class variability, thereby improving the performance of LVO classification.

Non-invasive brain stimulation effectively improves post-stroke sensory impairment: a systematic review and meta-analysis.

More than half of stroke patients experience sensory dysfunction that affects their quality of life. Previous training modalities are ineffective in improving sensory function. In contrast, non-invasive brain stimulation (NIBS) is a new promising intervention for stroke rehabilitation. The aim of this meta-analysis was to summarize the current effectiveness of NIBS in the treatment of post-stroke sensory dysfunction. Articles published in PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), Chinese scientific journals full-text database (VIP), and Wanfang database from the inception to March 8, 2023 were searched. There were no restrictions on language. A total of 14 RCTs were included (combined n = 804). Moderate-quality evidence suggested that NIBS significantly improved sensory function after stroke, and significant effects were observed up to 1 year after the intervention. In subgroup analysis, treatment with transcranial direct current stimulation (tDCS) or repetitive transcranial magnetic stimulation (rTMS) was significantly more effective than controls for recovery of sensory function in stroke patients. Stimulation of the primary motor cortex (M1), primary somatosensory cortex (S1) or M1 + S1 stimulation sites significantly improved sensory function. NIBS for sensory dysfunction showed significant therapeutic potential in patients with different stages of stroke. No significant effects were observed in subjects with less than 10 NIBS stimulations. Significant therapeutic effects were observed with either high-frequency or low-frequency rTMS.

Disparities in transitions of acute stroke care: The transitions of care stroke disparities study methodological report.

OBJECTIVE: The Transitions of Stroke Care Disparities Study (TCSD-S) is an observational study designed to determine race-ethnic and sex disparities in post-hospital discharge transitions of stroke care and stroke outcomes and to develop hospital-level initiatives to reduce these disparities to improve stroke outcomes. MATERIALS AND METHODS: Here, we present the study rationale, describe the methodology, report preliminary outcomes, and discuss a critical need for the development, implementation, and dissemination of interventions for successful post-hospital transition of stroke care. The preliminary outcomes describe the demographic, stroke risk factor, socioeconomic, and acute care characteristics of eligible participants by race-ethnicity and sex. We also report on all-cause and vascular-related death, readmissions, and hospital/emergency room representations at 30- and 90-days after hospital discharge. RESULTS: The preliminary sample included data from 1048 ischemic stroke and intracerebral hemorrhage discharged from 10 comprehensive stroke centers across the state of Florida. The overall sample was 45% female, 22% Non-Hispanic Black and 21% Hispanic participants, with an average age of 64 ± 14 years. All cause death, readmissions, or hospital/emergency room representations are 10% and 19% at 30 and 90 days, respectively. One in 5 outcomes was vascular-related. CONCLUSIONS: This study highlights the transition from stroke hospitalization as an area in need for considerable improvement in systems of care for stroke patients discharged from hospital. Results from our preliminary analysis highlight the importance of investigating race-ethnic and sex differences in post-stroke outcomes.

Impact of Hypertensive Disorders of Pregnancy on the Risk of Stroke Stratified by Subtypes and Follow-Up Time.

BACKGROUND AND PURPOSE: Hypertensive disorders of pregnancy (HDP) comprise 4 subtypes. Previous studies have not investigated the relationship between stroke risk, different HDP subtypes, and follow-up time, which was the purpose of this study. METHODS: Data of 17 588 women aged 18 to 45 years who had a history of HDP in Taiwan from 2000 to 2017 was retrospectively reviewed. After matching with confounders, 13 617 HDP women and 54 468 non-HDP women were recruited. RESULTS: HDP women had an adjusted hazard ratio (aHR) of 1.71 (95% CI, 1.46-2.00) for stroke, and 1.60 (1.35-1.89) and 2.98 (2.13-4.18) for ischemic and hemorrhagic stroke, respectively (P<0.001 for all). The overall stroke risk in the HDP group was still 2.04 times 10 to 15 years after childbirth (1.47-2.83, P<0.001). Although the risks of both ischemic and hemorrhagic stroke persisted, their risk time trends were different. The risk of ischemic stroke reached peak during 1 to 3 years after childbirth with an aHR of 2.14 (1.36-3.38), while hemorrhagic stroke risk gradually increased and had an aHR of 4.64 (2.47-8.73) after 10 to 15 years of childbirth (both P<0.001). Among the 4 HDP subtypes, chronic hypertension with superimposed preeclampsia had the highest stroke risk (aHR=3.86, 1.91-7.82, P<0.001), followed by preeclampsia-eclampsia (aHR=2.00, 1.63-2.45, P<0.001), and gestational hypertension (aHR=1.68, 1.13-2.52, P<0.05); chronic preexisting hypertension had the lowest stroke risk (aHR=1.27, 0.97-1.68, P>0.05). Furthermore, multiple HDP combined with preeclampsia had aHR of 5.48 (1.14-26.42, P<0.05). CONCLUSIONS: The effect of HDP on the risk of future stroke persisted for up to 17 years, both for ischemic and hemorrhagic strokes. The presence of multiple HDP and preeclampsia further increase the stroke risk.

Improving Stroke Risk Prediction in the General Population: A Comparative Assessment of Common Clinical Rules, a New Multimorbid Index, and Machine-Learning-Based Algorithms.

BACKGROUND: There are few large studies examining and predicting the diversified cardiovascular/noncardiovascular comorbidity relationships with stroke. We investigated stroke risks in a very large prospective cohort of patients with multimorbidity, using two common clinical rules, a clinical multimorbid index and a machine-learning (ML) approach, accounting for the complex relationships among variables, including the dynamic nature of changing risk factors. METHODS: We studied a prospective U.S. cohort of 3,435,224 patients from medical databases in a 2-year investigation. Stroke outcomes were examined in relationship to diverse multimorbid conditions, demographic variables, and other inputs, with ML accounting for the dynamic nature of changing multimorbidity risk factors, two clinical risk scores, and a clinical multimorbid index. RESULTS: Common clinical risk scores had moderate and comparable c indices with stroke outcomes in the training and external validation samples (validation-CHADS2: c index 0.812, 95% confidence interval [CI] 0.808-0.815; CHA2DS2-VASc: c index 0.809, 95% CI 0.805-0.812). A clinical multimorbid index had higher discriminant validity values for both the training/external validation samples (validation: c index 0.850, 95% CI 0.847-0.853). The ML-based algorithms yielded the highest discriminant validity values for the gradient boosting/neural network logistic regression formulations with no significant differences among the ML approaches (validation for logistic regression: c index 0.866, 95% CI 0.856-0.876). Calibration of the ML-based formulation was satisfactory across a wide range of predicted probabilities. Decision curve analysis demonstrated that clinical utility for the ML-based formulation was better than that for the two current clinical rules and the newly developed multimorbid tool. Also, ML models and clinical stroke risk scores were more clinically useful than the "treat all" strategy. CONCLUSION: Complex relationships of various comorbidities uncovered using a ML approach for diverse (and dynamic) multimorbidity changes have major consequences for stroke risk prediction. This approach may facilitate automated approaches for dynamic risk stratification in the significant presence of multimorbidity, helping in the decision-making process for risk assessment and integrated/holistic management.

Prevalence of the Frank's sign by aetiopathogenic stroke subtype: A prospective analysis.

BACKGROUND AND PURPOSE: The Frank's sign is a diagonal earlobe crease running from the tragus to the edge of the auricle at an angle of 45°. Many studies have associated this sign with coronary artery disease and some with cerebrovascular disease. The objective of this study was to analyse the prevalence of the Frank's sign in patients suffering from acute stroke with a particular focus on its prevalence in each of the five aetiopathogenic stroke subtypes. Special interest is given to embolic stroke of undetermined source (ESUS), correlating the sign with clinical and radiological markers that support an underlying causal profile in this subgroup. METHODS: Cross-sectional descriptive study including 124 patients admitted consecutively to a stroke unit after suffering an acute stroke. The Frank's sign was evaluated by the same blinded member of the research team from photographs taken of the patients. The stroke subtype was classified following SSS-TOAST criteria and the aetiological study was performed following the ESO guidelines. RESULTS: The Frank's sign was present in 75 patients and was more prevalent in patients with an ischaemic stroke in comparison with haemorrhagic stroke (63.9 vs. 37.5, p<0.05). A similar prevalence was found in the different ischaemic stroke subtypes. The Frank's sign was significantly associated with age, particularly in patients older than 70 who had vascular risk factors. Atherosclerotic plaques found in carotid ultrasonography were significantly more frequent in patients with the Frank's sign (63.6%, p<0.05). Analysing the ESUS, we also found an association with age and a higher prevalence of the Frank's sign in patients with vascular risk factors and a tendency to a high prevalence of atherosclerosis markers. CONCLUSION: The Frank's sign is prevalent in all aetiopathogenic ischaemic stroke subtypes, including ESUS, where it could be helpful in suspecting the underlying cardioembolic or atherothrombotic origin and guiding the investigation of atherosclerosis in patients with ESUS and the Frank's sign.

Temporal trend and attributable risk factors of stroke burden in China, 1990-2019: an analysis for the Global Burden of Disease Study 2019.

BACKGROUND: Understanding the temporal trend of the disease burden of stroke and its attributable risk factors in China, especially at provincial levels, is important for effective prevention strategies and improvement. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is to investigate the disease burden of stroke and its risk factors at national and provincial levels in China from 1990 to 2019. METHODS: Following the methodology in the GBD 2019, the incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) of stroke cases in the Chinese population were estimated by sex, age, year, stroke subtypes (ischaemic stroke, intracerebral haemorrhage, and subarachnoid haemorrhage), and across 33 provincial administrative units in China from 1990 to 2019. Attributable mortality and DALYs of underlying risk factors were calculated by a comparative risk assessment. FINDINGS: In 2019, there were 3·94 million (95% uncertainty interval 3·43-4·58) new stroke cases in China. The incidence rate of stroke increased by 86·0% (73·2-99·0) from 1990, reaching 276·7 (241·3-322·0) per 100 000 population in 2019. The age-standardised incidence rate declined by 9·3% (3·3-15·5) from 1990 to 2019. Among 28·76 million (25·60-32·21) prevalent cases of stroke in 2019, 24·18 million (20·80-27·87) were ischaemic stroke, 4·36 million (3·69-5·05) were intracerebral haemorrhage, and 1·58 million (1·32-1·91) were subarachnoid haemorrhage. The prevalence rate increased by 106·0% (93·7-118·8) and age-standardised prevalence rate increased by 13·2% (7·7-19·1) from 1990 to 2019. In 2019, there were 2·19 million (1·89-2·51) deaths and 45·9 million (39·8-52·3) DALYs due to stroke. The mortality rate increased by 32·3% (8·6-59·0) from 1990 to 2019. Over the same period, the age-standardised mortality rate decreased by 39·8% (28·6-50·7) and the DALY rate decreased by 41·6% (30·7-50·9). High systolic blood pressure, ambient particulate matter pollution exposure, smoking, and diet high in sodium were four major risk factors for stroke burden in 2019. Moreover, we found marked differences of stroke burden and attributable risk factors across provinces in China from 1990 to 2019. INTERPRETATION: The disease burden of stroke is still severe in China, although the age-standardised incidence and mortality rates have decreased since 1990. The stroke burden in China might be reduced through blood pressure management, lifestyle interventions, and air pollution control. Moreover, because substantial heterogeneity of stroke burden existed in different provinces, improved health care is needed in provinces with heavy stroke burden. FUNDING: National Key Research and Development Program of China and Taikang Yicai Public Health and Epidemic Control Fund.

ADL Outcome of Stroke by Stroke Type and Time from Onset to Admission to a Comprehensive Inpatient Rehabilitation Ward.

OBJECTIVE: To examine the effect of onset to admission interval (OAI) and stroke type on activities of daily living (ADL) outcome. MATERIALS AND METHODS: Stroke patients (n=3112) admitted to and discharged from comprehensive inpatient rehabilitation wards at Nanakuri Memorial Hospital were classified into 8 OAI segments and by stroke type [intracerebral hemorrhage (ICH) and cerebral infarction (CI)]. Motor subscore of the Functional Independence Measure (FIM-M) on admission, FIM-M at discharge, FIM-M gain, length of stay (LOS), and FIM-M efficiency in the ICH and CI group matched by OAI segment were compared using the Wilcoxon test. Multiple comparisons using the Steel-Dwass test of FIM-M on admission, FIM-M at discharge, FIM-M gain, LOS, and FIM-M efficiency by OAI segments were performed. RESULTS: FIM-M on admission was lower in the ICH group than the CI group in matched OAI segments. However, FIM-M improvement was greater in the ICH group than the CI group, resulting in no difference in FIM-M between groups at discharge. In both groups, the longer the OAI, the lower the FIM-M on admission and at discharge. The distribution pattern of significant differences among OAI segments differed between the groups. LOS tended to be longer and FIM-M efficiency tended to be higher in the ICH group than in the CI group. CONCLUSIONS: The brain mass effect at the time of admission was larger and took longer to decrease in the ICH group than in the CI group. These results may improve prediction of outcomes in comprehensive inpatient rehabilitation wards.

Estimation of stroke severity with National Institutes of Health Stroke Scale grading and retinal features: A cross-sectional study.

ABSTRACT: To estimate National Institutes of Health Stroke Scale (NIHSS) grading of stroke patients with retinal characteristics.A cross-sectional study was conducted in Shenzhen Traditional Chinese Medicine Hospital. Baseline information and retinal photos were collected within 2 weeks of admission. An NIHSS score was measured for each patient by trained doctors. Patients were classified into 0 to 4 score group and 5 to 42 score group for analysis. Three multivariate logistic models, with traditional clinical characteristics alone, with retinal characteristics alone, and with both, were built.For clinical characteristics, hypertension duration is statistically significantly associated with higher NIHSS score (P = .014). Elevated total homocysteine levels had an OR of 0.456 (P = .029). For retinal characteristics, the fractal dimension of the arteriolar network had an OR of 0.245 (P < .001) for the left eyes, and an OR of 0.417 (P = .009) for right eyes. The bifurcation coefficient of the arteriole of the left eyes had an OR of 2.931 (95% CI 1.573-5.46, P = .001), the nipping of the right eyes had an OR of 0.092 (P = .003) showed statistical significance in the model.The area under receiver-operating characteristic curve increased from 0.673, based on the model with clinical characteristics alone, to 0.896 for the model with retinal characteristics alone and increased to 0.931 for the model with both clinical and retinal characteristics combined.Retinal characteristics provided more information than clinical characteristics in estimating NIHSS grading and can provide us with an objective method for stroke severity estimation.

Stroke Outcome Prediction Using Admission Nihss In Anterior And Posterior Circulation Stroke.

BACKGROUND: Stroke is a worldwide disease with high morbidity. Various scales are used to measure the severity and outcome of stroke. National Institute of Health Stroke Scale (NIHSS) is a quantifiable scale used to assess stroke severity. However, it is biased towards anterior circulation stroke as compared to posterior circulation stroke, giving higher values in the former. Therefore, it is imperative to know the mean values of NIHSS in each group to predict the functional outcome. The main aim of the study is to compare the mean NIHSS at the time of admission for determining favourable and unfavourable functional outcome in anterior and posterior circulation ischemic stroke. METHODS: It is a descriptive case study of six months' duration done in a Tertiary Care Hospital. All patients of 18 years and above with ischemic stroke involving single arterial territory presented in hospital within 72 hours were included. With the help of the WHO sample size calculator, a target population of 100 patients was determined with a confidence level of 95%. For mean difference we applied independent t test and t score with mean differences for NIHSS at admission and location of stroke has been calculated. Patients with haemorrhagic stroke, venous stroke secondary to Dural Sinus thrombosis, with concomitant disability because of any reason including previous stroke, stroke involving watershed areas and concomitant Acute Coronary Syndrome were excluded. A favourable outcome was defined as Modified Ranking scale score of ≤3 at 1-month post stroke. RESULTS: In anterior circulation, mean baseline NIHSS was 11.3 [SD 7.4], while in posterior circulation, mean NIHSS was 7.30 [SD 7.6]. Comparing the means for functional outcome in anterior circulation using independent t test score, a lower baseline NIHSS score was independently predictive of a favourable outcome for patients with AC (OR 1.268, 95% CI 1.76 -1.358) and PC (OR 1.534, 95% CI 1.321-1.891) stroke. CONCLUSIONS: The mean NIHSS of good functional outcome group is much lower for posterior circulation stroke as compared to anterior circulation stroke which highlights the need for basing the decision of acute stroke emergency management on full neurological examination, rather than a single scale, especially if the posterior circulation stroke is in question.

Noninvasive transcranial classification of stroke using a portable eddy current damping sensor.

Existing paradigms for stroke diagnosis typically involve computed tomography (CT) imaging to classify ischemic versus hemorrhagic stroke variants, as treatment for these subtypes varies widely. Delays in diagnosis and transport of unstable patients may worsen neurological status. To address these issues, we describe the development of a rapid, portable, and accurate eddy current damping (ECD) stroke sensor. Copper wire was wound to create large (11.4 cm), medium (4.5 cm), and small (1.5 cm) solenoid coils with varying diameters, with each connected to an inductance-to-digital converter. Eight human participants were recruited between December 15, 2019 and March 15, 2020, including two hemorrhagic stroke, two ischemic stroke, one subarachnoid hemorrhage, and three control participants. Observers were blinded to lesion type and location. A head cap with 8 horizontal scanning paths was placed on the patient. The sensor was tangentially rotated across each row on the patient's head circumferentially. Consent, positioning, and scanning with the sensor took roughly 15 min from start to end for each participant and all scanning took place at the patient bedside. The ECD sensor accurately classified and imaged each of the varying stroke types in each patient. The sensor additionally detected ischemic and hemorrhagic lesions located deep inside the brain, and its range is selectively tunable during sensor design and fabrication.

Predictors for affected stroke territory and outcome of acute stroke treatments are different for posterior versus anterior circulation stroke.

Distinct patient characteristics have been proposed for ischaemic stroke in the anterior versus posterior circulation. However, data on functional outcome according to stroke territory in patients with acute stroke treatment are conflicting and information on outcome predictors is scarce. In this retrospective study, we analysed functional outcome in 517 patients with stroke and thrombolysis and/or thrombectomy treated at the University Hospital Zurich. We compared clinical factors and performed multivariate logistic regression analyses investigating the effect of outcome predictors according to stroke territory. Of the 517 patients included, 80 (15.5%) suffered a posterior circulation stroke (PCS). PCS patients were less often female (32.5% vs. 45.5%, p = 0.031), received thrombectomy less often (28.7% vs. 48.3%, p = 0.001), and had lower median admission NIHSS scores (5 vs. 10, p < 0.001) as well as a better median three months functional outcome (mRS 1 vs. 2, p = 0.010). Predictors for functional outcome were admission NIHSS (OR 0.864, 95% CI 0.790-0.944, p = 0.001) in PCS and age (OR 0.952, 95% CI 0.935-0.970, p < 0.001), known symptom onset (OR 1.869, 95% CI 1.111-3.144, p = 0.018) and admission NIHSS (OR 0.840, 95% CI 0.806-0.876, p < 0.001) in ACS. Acutely treated PCS and ACS patients differed in their baseline and treatment characteristics. We identified specific functional outcome predictors of thrombolysis and/or thrombectomy success for each stroke territory.

The severity of microstrokes depends on local vascular topology and baseline perfusion.

Cortical microinfarcts are linked to pathologies like cerebral amyloid angiopathy and dementia. Despite their relevance for disease progression, microinfarcts often remain undetected and the smallest scale of blood flow disturbance has not yet been identified. We employed blood flow simulations in realistic microvascular networks from the mouse cortex to quantify the impact of single-capillary occlusions. Our simulations reveal that the severity of a microstroke is strongly affected by the local vascular topology and the baseline flow rate in the occluded capillary. The largest changes in perfusion are observed in capillaries with two inflows and two outflows. This specific topological configuration only occurs with a frequency of 8%. The majority of capillaries have one inflow and one outflow and is likely designed to efficiently supply oxygen and nutrients. Taken together, microstrokes bear potential to induce a cascade of local disturbances in the surrounding tissue, which might accumulate and impair energy supply locally.

A blockage in one of the tiny blood vessels or capillaries of the brain causes a 'microstroke'. Microstrokes do not cause the same level of damage as a major stroke, which is caused by a blockage in a larger blood vessel that completely cuts off oxygen to a part of the brain for a period. But microstrokes do increase the risk of developing conditions like dementia ­ including Alzheimer's disease ­ later in life. People with these neurodegenerative conditions have fewer capillaries in their brains. The capillaries make up a mesh-like network of millions of vessels that supply most of the energy and oxygen to the brain. Repeated microstrokes may contribute to progressive loss of capillaries over time. Reduced numbers of capillaries may increase memory loss and other brain difficulties. To better understand how microstrokes affect blood flow in the brain, Schmid et al. created a computer model to simulate blood flow in capillaries in the mouse brain. Then, they modeled what happens to the blood flow when one capillary is blocked. The experiments showed that the configuration of the blocked capillary determines how much blood flow in neighboring capillaries changes. Blockages in capillaries with two vessels feeding in and two vessels feeding out caused the greatest blood flow disturbances. But these 2-in-2-out vessels only make up about 8% of all brain capillaries. Blockages in capillaries with different configurations with respect to feeding vessels had less effect. The experiments suggest that most microstrokes have limited effects on blood flow on the scale of the entire brain because of redundancies in the capillary network in the brain. However, the ability of the capillary network to adapt and reroute blood flow in response to small blockages may decrease with aging. Over time, ministrokes in a single capillary may set off a chain reaction of disturbed blood flow and more blockages. This may decrease energy and oxygen supplies explaining age- and disease-related brain decline. Better understanding the effects of microstrokes on blood flow may help scientists develop new ways to prevent such declines.

First approach to distinguish between cardiac and arteriosclerotic emboli of individual stroke patients applying the histological THROMBEX-classification rule.

Endovascular treatment of strokes caused by large vessel occlusion enables the histopathological investigation of the retrieved embolus, possibly providing a novel opportunity to contribute to the diagnostic workup of etiology and to define secondary prevention measures in strokes with uncertain genesis. We aimed to develop a classification rule based on pathophysiological considerations and adjustment to reference thrombi for distinction between cardiac and arteriosclerotic emboli and to validate this classification rule on a patient cohort. From 125 patients with stroke due to large vessel occlusion and thrombectomy, 82 patients with known etiology (55 cardioembolic and 27 arterioembolic strokes) were included. The corresponding emboli were histologically evaluated by two raters blinded to the etiology of stroke by means of a novel classification rule. Presumed etiology and classification results were compared. Agreement concerning cardiac emboli was 72.2% (95% CI: 58.4-83.5) for rater I and 78.2% (95% CI: 65.0-88.2) for rater II. Agreement concerning arteriosclerotic emboli was 70.4% (95% CI: 49.8-86.3) for rater I and 74.1% (95% CI: 53.7-88.9) for rater II. Overall agreement reached 71.6% (95% CI: 60.5-81.1) for rater I and 76.8% (95% CI: 66.2-85.4) for rater II. Within the limits of generally restricted accuracy of histological evaluations, the classification rule differentiates between cardiac and arteriosclerotic emboli of acute ischemic stroke patients. Further improvement is needed to provide valuable complementary data for stroke etiology workup.