Perispinal Etanercept to improve STroke Outcomes (PESTO): Protocol for a multicenter, international, randomized placebo-controlled trial.

RATIONALE: A large proportion of stroke survivors will have long-lasting, debilitating neurological impairments, yet few efficacious medical treatment options are available. Etanercept inhibits binding of tumor necrosis factor to its receptor and is used in the treatment of inflammatory conditions. Perispinal subcutaneous injection followed by a supine, head down position may bypass the blood brain barrier. In observational studies and one small randomized controlled trial the majority of patients showed improvement in multiple post stroke impairments. AIM: Perispinal Etanercept to improve STroke Outcomes (PESTO) investigates whether perispinal subcutaneous injection of etanercept improves quality of life and is safe in patients with chronic, disabling, effects of stroke. METHODS AND DESIGN: PESTO is a multicenter, international, randomized placebo-controlled trial. Adult participants with a history of stroke between 1 and 15 years before enrollment and a current modified Rankin scale between 2 and 5 who are otherwise eligible for etanercept are randomized 1:1 to single dose injection of etanercept or placebo. STUDY OUTCOMES: The primary efficacy outcome is quality of life as measured using the Short Form 36 Health Inventory at day 28 after first injection. Safety outcomes include serious adverse events. SAMPLE SIZE TARGET: A total of 168 participants assuming an improvement of the SF-36 in 11% of participants in the control arm and in 30% of participants in the intervention arm, 80% power and 5% alpha. DISCUSSION: PESTO aims to provide level 1 evidence on the safety and efficacy of perispinal etanercept in patients with long-term disabling effects of stroke.

Genetic Insights on the Relation of Vascular Risk Factors and Cervical Artery Dissection.

BACKGROUND: The association between vascular risk factors and cervical artery dissections (CeADs), a leading cause of ischemic stroke (IS) in the young, remains controversial. OBJECTIVES: This study aimed to explore the causal relation of vascular risk factors with CeAD risk and recurrence and compare it to their relation with non-CeAD IS. METHODS: This study used 2-sample Mendelian randomization analyses to explore the association of blood pressure (BP), lipid levels, type 2 diabetes, waist-to-hip ratio, smoking, and body mass index with CeAD and non-CeAD IS. To simulate effects of the most frequently used BP-lowering drugs, this study constructed genetic proxies and tested their association with CeAD and non-CeAD IS. In analyses among patients with CeAD, the investigators studied the association between weighted genetic risk scores of vascular risk factors and the risk of multiple or early recurrent dissections. RESULTS: Genetically determined higher systolic BP (OR: 1.51; 95% CI: 1.32-1.72) and diastolic BP (OR: 2.40; 95% CI: 1.92-3.00) increased the risk of CeAD (P < 0.0001). Genetically determined higher body mass index was inconsistently associated with a lower risk of CeAD. Genetic proxies for ß-blocker effects were associated with a lower risk of CeAD (OR: 0.65; 95% CI: 0.50-0.85), whereas calcium-channel blockers were associated with a lower risk of non-CeAD IS (OR: 0.75; 95% CI: 0.63-0.90). Weighted genetic risk scores for systolic BP and diastolic BP were associated with an increased risk of multiple or early recurrent CeAD. CONCLUSIONS: These results are supportive of a causal association between higher BP and increased CeAD risk and recurrence and provide genetic evidence for lower CeAD risk under ß-blockers. This may inform secondary prevention strategies and trial design for CeAD.

Radiomics-Derived Brain Age Predicts Functional Outcome After Acute Ischemic Stroke.

BACKGROUND AND OBJECTIVES: While chronological age is one of the most influential determinants of poststroke outcomes, little is known of the impact of neuroimaging-derived biological "brain age." We hypothesized that radiomics analyses of T2-FLAIR images texture would provide brain age estimates and that advanced brain age of patients with stroke will be associated with cardiovascular risk factors and worse functional outcomes. METHODS: We extracted radiomics from T2-FLAIR images acquired during acute stroke clinical evaluation. Brain age was determined from brain parenchyma radiomics using an ElasticNet linear regression model. Subsequently, relative brain age (RBA), which expresses brain age in comparison with chronological age-matched peers, was estimated. Finally, we built a linear regression model of RBA using clinical cardiovascular characteristics as inputs and a logistic regression model of favorable functional outcomes taking RBA as input. RESULTS: We reviewed 4,163 patients from a large multisite ischemic stroke cohort (mean age = 62.8 years, 42.0% female patients). T2-FLAIR radiomics predicted chronological ages (mean absolute error = 6.9 years, r = 0.81). After adjustment for covariates, RBA was higher and therefore described older-appearing brains in patients with hypertension, diabetes mellitus, a history of smoking, and a history of a prior stroke. In multivariate analyses, age, RBA, NIHSS, and a history of prior stroke were all significantly associated with functional outcome (respective adjusted odds ratios: 0.58, 0.76, 0.48, 0.55; all p-values < 0.001). Moreover, the negative effect of RBA on outcome was especially pronounced in minor strokes. DISCUSSION: T2-FLAIR radiomics can be used to predict brain age and derive RBA. Older-appearing brains, characterized by a higher RBA, reflect cardiovascular risk factor accumulation and are linked to worse outcomes after stroke.

Development of a machine learning-based real-time location system to streamline acute endovascular intervention in acute stroke: a proof-of-concept study.

BACKGROUND: Delivery of acute stroke endovascular intervention can be challenging because it requires complex coordination of patient and staff across many different locations. In this proof-of-concept paper we (a) examine whether WiFi fingerprinting is a feasible machine learning (ML)-based real-time location system (RTLS) technology that can provide accurate real-time location information within a hospital setting, and (b) hypothesize its potential application in streamlining acute stroke endovascular intervention. METHODS: We conducted our study in a comprehensive stroke care unit in Melbourne, Australia that offers a 24-hour mechanical thrombectomy service. ML algorithms including K-nearest neighbors, decision tree, random forest, support vector machine and ensemble models were trained and tested on a public WiFi dataset and the study hospital WiFi dataset. The hospital dataset was collected using the WiFi explorer software (version 3.0.2) on a MacBook Pro (AirPort Extreme, Broadcom BCM43x×1.0). Data analysis was implemented in the Python programming environment using the scikit-learn package. The primary statistical measure for algorithm performance was the accuracy of location prediction. RESULTS: ML-based WiFi fingerprinting can accurately predict the different hospital zones relevant in the acute endovascular intervention workflow such as emergency department, CT room and angiography suite. The most accurate algorithms were random forest and support vector machine, both of which were 98% accurate. The algorithms remain robust when new data points, which were distinct from the training dataset, were tested. CONCLUSIONS: ML-based RTLS technology using WiFi fingerprinting has the potential to streamline delivery of acute stroke endovascular intervention by efficiently tracking patient and staff movement during stroke calls.

Cost-Effectiveness of Magnetic Resonance Imaging-Guided Thrombolysis for Patients With Stroke With Unknown Time of Onset.

OBJECTIVES: Patients waking up with stroke symptoms are often excluded from intravenous thrombolysis with alteplase (IV-tpa). The WAKE-UP trial, a European multicenter randomized controlled trial, proved the clinical effectiveness of magnetic resonance imaging-guided IV-tpa for these patients. This analysis aimed to assess the cost-effectiveness of the intervention compared to placebo. METHODS: A Markov model was designed to analyze the cost-effectiveness over a 25-year time horizon. The model consisted of an inpatient acute care phase and a rest-of-life phase. Health states were defined by the modified Rankin Scale (mRS). Initial transition probabilities to mRS scores were based on WAKE-UP data and health state utilities on literature search. Costs were based on data from the University Medical Center Hamburg-Eppendorf, literature, and expert opinion. Incremental costs and effects over the patients' lifetime were estimated. The analysis was conducted from a formal German healthcare perspective. Univariate and probabilistic sensitivity analyses were performed. RESULTS: Treatment with IV-tpa resulted in cost savings of €51 009 and 1.30 incremental gains in quality-adjusted life-years at a 5% discount rate. Univariate sensitivity analysis revealed incremental cost-effectiveness ratio being sensitive to the relative risk of favorable outcome on mRS for placebo patients after stroke, the costs of long-term care for patients with mRS 4, and patient age at initial stroke event. In all cases, IV-tpa remained cost-effective. Probabilistic sensitivity analysis proved IV-tpa cost-effective in >95% of the simulations results. CONCLUSIONS: Magnetic resonance imaging-guided IV-tpa compared to placebo is cost-effective in patients with ischemic stroke with unknown time of onset.

Excessive White Matter Hyperintensity Increases Susceptibility to Poor Functional Outcomes After Acute Ischemic Stroke.

Objective: To personalize the prognostication of post-stroke outcome using MRI-detected cerebrovascular pathology, we sought to investigate the association between the excessive white matter hyperintensity (WMH) burden unaccounted for by the traditional stroke risk profile of individual patients and their long-term functional outcomes after a stroke. Methods: We included 890 patients who survived after an acute ischemic stroke from the MRI-Genetics Interface Exploration (MRI-GENIE) study, for whom data on vascular risk factors (VRFs), including age, sex, atrial fibrillation, diabetes mellitus, hypertension, coronary artery disease, smoking, prior stroke history, as well as acute stroke severity, 3- to-6-month modified Rankin Scale score (mRS), WMH, and brain volumes, were available. We defined the unaccounted WMH (uWMH) burden via modeling of expected WMH burden based on the VRF profile of each individual patient. The association of uWMH and mRS score was analyzed by linear regression analysis. The odds ratios of patients who achieved full functional independence (mRS < 2) in between trichotomized uWMH burden groups were calculated by pair-wise comparisons. Results: The expected WMH volume was estimated with respect to known VRFs. The uWMH burden was associated with a long-term functional outcome (ß = 0.104, p < 0.01). Excessive uWMH burden significantly reduced the odds of achieving full functional independence after a stroke compared to the low and average uWMH burden [OR = 0.4, 95% CI: (0.25, 0.63), p < 0.01 and OR = 0.61, 95% CI: (0.42, 0.87), p < 0.01, respectively]. Conclusion: The excessive amount of uWMH burden unaccounted for by the traditional VRF profile was associated with worse post-stroke functional outcomes. Further studies are needed to evaluate a lifetime brain injury reflected in WMH unrelated to the VRF profile of a patient as an important factor for stroke recovery and a plausible indicator of brain health.

Cost-effectiveness of insertable cardiac monitors for diagnosis of atrial fibrillation in cryptogenic stroke in Australia.

INTRODUCTION: Detection of atrial fibrillation (AF) is required to initiate oral anticoagulation (OAC) after cryptogenic stroke (CS). However, paroxysmal AF can be difficult to diagnose with short term cardiac monitoring. Taking an Australian payer perspective, we evaluated whether long-term continuous monitoring for 3 years with an insertable cardiac monitor (ICM) is cost-effective for preventing recurrent stroke in patients with CS. METHODS: A lifetime Markov model was developed to simulate the follow-up of patients, comparing long-term continuous monitoring with an ICM to monitoring by conventional care. We used a linked evidence approach to estimate the rates of recurrent stroke when AF detection leads to initiation of OAC, as detected using ICM during the lifetime of the device or as detected using usual care. All diagnostic and patient management costs were modeled. Other model inputs were determined by literature review. Probabilistic sensitivity analysis (PSA) was undertaken to explore the effect of parameter uncertainty according to CHADS2 score and OAC treatment effect. RESULTS: In the base-case analysis, the model predicted an incremental cost-effectiveness ratio (ICER) of A$29 570 per quality-adjusted life year (QALY). Among CHADS2 subgroups analyses, the ICER ranged from A$26 342/QALY (CHADS2 = 6) to A$42 967/QALY (CHADS2 = 2). PSA suggested that the probabilities of ICM strategy being cost-effective were 53.4% and 78.7%, at thresholds of $30 000 (highly cost-effective) and $50 000 per QALY (cost-effective), respectively. CONCLUSIONS: Long-term continuous monitoring with an ICM is a cost-effective intervention to prevent recurrent stroke in patients following CS in the Australian context.

MRI Radiomic Signature of White Matter Hyperintensities Is Associated With Clinical Phenotypes.

OBJECTIVE: Neuroimaging measurements of brain structural integrity are thought to be surrogates for brain health, but precise assessments require dedicated advanced image acquisitions. By means of quantitatively describing conventional images, radiomic analyses hold potential for evaluating brain health. We sought to: (1) evaluate radiomics to assess brain structural integrity by predicting white matter hyperintensities burdens (WMH) and (2) uncover associations between predictive radiomic features and clinical phenotypes. METHODS: We analyzed a multi-site cohort of 4,163 acute ischemic strokes (AIS) patients with T2-FLAIR MR images with total brain and WMH segmentations. Radiomic features were extracted from normal-appearing brain tissue (brain mask-WMH mask). Radiomics-based prediction of personalized WMH burden was done using ElasticNet linear regression. We built a radiomic signature of WMH with stable selected features predictive of WMH burden and then related this signature to clinical variables using canonical correlation analysis (CCA). RESULTS: Radiomic features were predictive of WMH burden (R 2 = 0.855 ± 0.011). Seven pairs of canonical variates (CV) significantly correlated the radiomics signature of WMH and clinical traits with respective canonical correlations of 0.81, 0.65, 0.42, 0.24, 0.20, 0.15, and 0.15 (FDR-corrected p-values CV 1 - 6 < 0.001, p-value CV 7 = 0.012). The clinical CV1 was mainly influenced by age, CV2 by sex, CV3 by history of smoking and diabetes, CV4 by hypertension, CV5 by atrial fibrillation (AF) and diabetes, CV6 by coronary artery disease (CAD), and CV7 by CAD and diabetes. CONCLUSION: Radiomics extracted from T2-FLAIR images of AIS patients capture microstructural damage of the cerebral parenchyma and correlate with clinical phenotypes, suggesting different radiographical textural abnormalities per cardiovascular risk profile. Further research could evaluate radiomics to predict the progression of WMH and for the follow-up of stroke patients' brain health.

Application of a computational model in simulating an endovascular clot retrieval service system within regional Australia.

INTRODUCTION: The global demand for endovascular clot retrieval (ECR) has grown rapidly in recent years creating challenges to healthcare system planning and resource allocation. This study aims to apply our established computational model to predict and optimise the performance and resource allocation of ECR services within regional Australia, and applying data from the state of South Australia as a modelling exercise. METHOD: Local geographic information obtained using the Google Maps application program interface and real-world data was input into the discrete event simulation model we previously developed. The results were obtained after the simulation was run over 5 years. We modelled and compared a single-centre and two-centre ECR service delivery system. RESULTS: Based on the input data, this model was able to simulate the ECR delivery system in the state of South Australia from the moment when emergency services were notified of a potential stroke patient to potential delivery of ECR treatment. In the model, ECR delivery improved using a two-centre system compared to a one-centre system, as the percentage of stroke patients requiring ECR was increased. When 15% of patients required ECR, the proportion of 'failure to receive ECR' cases for a single-centre system was 17.35%, compared to 3.71% for a two-centre system. CONCLUSIONS: Geolocation and resource utilisation within the ECR delivery system are crucial in optimising service delivery and patient outcome. Under the model assumptions, as the number of stroke cases requiring ECR increased, a two-centre ECR system resulted in increased timely ECR delivery, compared to a single-centre system. This study demonstrated the flexibility and the potential application of our DES model in simulating the stroke service within any location worldwide.

Influence of stroke infarct location on quality of life assessed in a multivariate lesion-symptom mapping study.

Stroke has a deleterious impact on quality of life. However, it is less well known if stroke lesions in different brain regions are associated with reduced quality of life (QoL). We therefore investigated this association by multivariate lesion-symptom mapping. We analyzed magnetic resonance imaging and clinical data from the WAKE-UP trial. European Quality of Life 5 Dimensions (EQ-5D) 3 level questionnaires were completed 90 days after stroke. Lesion symptom mapping was performed using a multivariate machine learning algorithm (support vector regression) based on stroke lesions 22-36 h after stroke. Brain regions with significant associations were explored in reference to white matter tracts. Of 503 randomized patients, 329 were included in the analysis (mean age 65.4 years, SD 11.5; median NIHSS = 6, IQR 4-9; median EQ-5D score 90 days after stroke 1, IQR 0-4, median lesion volume 3.3 ml, IQR 1.1-16.9 ml). After controlling for lesion volume, significant associations between lesions and EQ-5D score were detected for the right putamen, and internal capsules of both hemispheres. Multivariate lesion inference analysis revealed an association between injuries of the cortico-spinal tracts with worse self-reported quality of life 90 days after stroke in comparably small stroke lesions, extending previous reports of the association of striato-capsular lesions with worse functional outcome. Our findings are of value to identify patients at risk of impaired QoL after stroke.

Artificial intelligence in clinical decision support and outcome prediction - applications in stroke.

Artificial intelligence (AI) is making a profound impact in healthcare, with the number of AI applications in medicine increasing substantially over the past five years. In acute stroke, it is playing an increasingly important role in clinical decision-making. Contemporary advances have increased the amount of information - both clinical and radiological - which clinicians must consider when managing patients. In the time-critical setting of acute stroke, AI offers the tools to rapidly evaluate and consolidate available information, extracting specific predictions from rich, noisy data. It has been applied to the automatic detection of stroke lesions on imaging and can guide treatment decisions through the prediction of tissue outcomes and long-term functional outcomes. This review examines the current state of AI applications in stroke, exploring their potential to reform stroke care through clinical decision support, as well as the challenges and limitations which must be addressed to facilitate their acceptance and adoption for clinical use.

Review of deep learning algorithms for the automatic detection of intracranial hemorrhages on computed tomography head imaging.

Artificial intelligence is a rapidly evolving field, with modern technological advances and the growth of electronic health data opening new possibilities in diagnostic radiology. In recent years, the performance of deep learning (DL) algorithms on various medical image tasks have continually improved. DL algorithms have been proposed as a tool to detect various forms of intracranial hemorrhage on non-contrast computed tomography (NCCT) of the head. In subtle, acute cases, the capacity for DL algorithm image interpretation support might improve the diagnostic yield of CT for detection of this time-critical condition, potentially expediting treatment where appropriate and improving patient outcomes. However, there are multiple challenges to DL algorithm implementation, such as the relative scarcity of labeled datasets, the difficulties in developing algorithms capable of volumetric medical image analysis, and the complex practicalities of deployment into clinical practice. This review examines the literature and the approaches taken in the development of DL algorithms for the detection of intracranial hemorrhage on NCCT head studies. Considerations in crafting such algorithms will be discussed, as well as challenges which must be overcome to ensure effective, dependable implementations as automated tools in a clinical setting.

Utility of Severity-Based Prehospital Triage for Endovascular Thrombectomy: ACT-FAST Validation Study.

BACKGROUND AND PURPOSE: Severity-based assessment tools may assist in prehospital triage of patients to comprehensive stroke centers (CSCs) for endovascular thrombectomy (EVT), but criticisms regarding diagnostic inaccuracy have not been adequately addressed. This study aimed to quantify the benefits and disadvantages of severity-based triage in a large real-world paramedic validation of the Ambulance Clinical Triage for Acute Stroke Treatment (ACT-FAST) algorithm. METHODS: Ambulance Victoria paramedics assessed the prehospital ACT-FAST algorithm in patients with suspected stroke from November 2017 to July 2019 following an 8-minute training video. All patients were transported to the nearest stroke center as per current guidelines. ACT-FAST diagnostic accuracy was compared with hospital imaging for the presence of large vessel occlusion (LVO) and need for CSC-level care (LVO, intracranial hemorrhage, and tumor). Patient-level time saving to EVT was modeled using a validated Google Maps algorithm. Disadvantages of CSC bypass examined potential thrombolysis delays in non-LVO infarcts, proportion of patients with false-negative EVT, and CSC overburdening. RESULTS: Of 517 prehospital assessments, 168/517 (32.5%) were ACT-FAST positive and 132/517 (25.5%) had LVO. ACT-FAST sensitivity and specificity for LVO was 75.8% and 81.8%, respectively. Positive predictive value was 58.8% for LVO and 80.0% when intracranial hemorrhage and tumor (CSC-level care) were included. Within the metropolitan region, 29/55 (52.7%) of ACT-FAST-positive patients requiring EVT underwent a secondary interhospital transfer. Prehospital bypass with avoidance of secondary transfers was modeled to save 52 minutes (95% CI, 40.0-61.5) to EVT commencement. ACT-FAST was false-positive in 8 patients receiving thrombolysis (8.1% of 99 non-LVO infarcts) and false-negative in 4 patients with EVT requiring secondary transfer (5.4% of 74 EVT cases). CSC bypass was estimated to over-triage 1.1 patients-per-CSC-per-week in our region. CONCLUSIONS: The overall benefits of an ACT-FAST algorithm bypass strategy in expediting EVT and avoiding secondary transfers are estimated to substantially outweigh the disadvantages of potentially delayed thrombolysis and over-triage, with only a small proportion of EVT patients missed.

Tranexamic acid in patients with intracerebral haemorrhage (STOP-AUST): a multicentre, randomised, placebo-controlled, phase 2 trial.

BACKGROUND: Despite intracerebral haemorrhage causing 5% of deaths worldwide, few evidence-based therapeutic strategies other than stroke unit care exist. Tranexamic acid decreases haemorrhage in conditions such as acute trauma and menorrhoea. We aimed to assess whether tranexamic acid reduces intracerebral haemorrhage growth in patients with acute intracerebral haemorrhage. METHODS: We did a prospective, double-blind, randomised, placebo-controlled, investigator-led, phase 2 trial at 13 stroke centres in Australia, Finland, and Taiwan. Patients were eligible if they were aged 18 years or older, had an acute intracerebral haemorrhage fulfilling clinical criteria (eg, Glasgow Coma Scale score of >7, intracerebral haemorrhage volume <70 mL, no identified or suspected secondary cause of intracerebral haemorrhage, no thrombotic events within the previous 12 months, no planned surgery in the next 24 h, and no use of anticoagulation), had contrast extravasation on CT angiography (the so-called spot sign), and were treatable within 4·5 h of symptom onset and within 1 h of CT angiography. Patients were randomly assigned (1:1) to receive either 1 g of intravenous tranexamic acid over 10 min followed by 1 g over 8 h or matching placebo, started within 4·5 h of symptom onset. Randomisation was done using a centralised web-based procedure with randomly permuted blocks of varying size. All patients, investigators, and staff involved in patient management were masked to treatment. The primary outcome was intracerebral haemorrhage growth (>33% relative or >6 mL absolute) at 24 h. The primary and safety analyses were done in the intention-to-treat population. The trial is registered at ClinicalTrials.gov (NCT01702636). FINDINGS: Between March 1, 2013, and Aug 13, 2019, we enrolled and randomly assigned 100 participants to the tranexamic acid group (n=50) or the placebo group (n=50). Median age was 71 years (IQR 57-79) and median intracerebral haemorrhage volume was 14·6 mL (7·9-32·7) at baseline. The primary outcome was not different between the two groups: 26 (52%) patients in the placebo group and 22 (44%) in the tranexamic acid group had intracerebral haemorrhage growth (odds ratio [OR] 0·72 [95% CI 0·32-1·59], p=0·41). There was no evidence of a difference in the proportions of patients who died or had thromboembolic complications between the groups: eight (16%) in the placebo group vs 13 (26%) in the tranexamic acid group died and two (4%) vs one (2%) had thromboembolic complications. None of the deaths was considered related to study medication. INTERPRETATION: Our study does not provide evidence that tranexamic acid prevents intracerebral haemorrhage growth, although the treatment was safe with no increase in thromboembolic complications. Larger trials of tranexamic acid, with simpler recruitment methods and an earlier treatment window, are justified. FUNDING: National Health and Medical Research Council, Royal Melbourne Hospital Foundation.

White matter hyperintensity burden in acute stroke patients differs by ischemic stroke subtype.

OBJECTIVE: To examine etiologic stroke subtypes and vascular risk factor profiles and their association with white matter hyperintensity (WMH) burden in patients hospitalized for acute ischemic stroke (AIS). METHODS: For the MRI Genetics Interface Exploration (MRI-GENIE) study, we systematically assembled brain imaging and phenotypic data for 3,301 patients with AIS. All cases underwent standardized web tool-based stroke subtyping with the Causative Classification of Ischemic Stroke (CCS). WMH volume (WMHv) was measured on T2 brain MRI scans of 2,529 patients with a fully automated deep-learning trained algorithm. Univariable and multivariable linear mixed-effects modeling was carried out to investigate the relationship of vascular risk factors with WMHv and CCS subtypes. RESULTS: Patients with AIS with large artery atherosclerosis, major cardioembolic stroke, small artery occlusion (SAO), other, and undetermined causes of AIS differed significantly in their vascular risk factor profile (all p < 0.001). Median WMHv in all patients with AIS was 5.86 cm3 (interquartile range 2.18-14.61 cm3) and differed significantly across CCS subtypes (p < 0.0001). In multivariable analysis, age, hypertension, prior stroke, smoking (all p < 0.001), and diabetes mellitus (p = 0.041) were independent predictors of WMHv. When adjusted for confounders, patients with SAO had significantly higher WMHv compared to those with all other stroke subtypes (p < 0.001). CONCLUSION: In this international multicenter, hospital-based cohort of patients with AIS, we demonstrate that vascular risk factor profiles and extent of WMH burden differ by CCS subtype, with the highest lesion burden detected in patients with SAO. These findings further support the small vessel hypothesis of WMH lesions detected on brain MRI of patients with ischemic stroke.

Prior Stroke in PFO Patients Is Associated With Both PFO-Related and -Unrelated Factors.

Background and Purpose: To identify factors associated with prior stroke at presentation in patients with cryptogenic stroke (CS) and patent foramen ovale (PFO). Methods: We studied cross-sectional data from the International PFO Consortium Study (NCT00859885). Patients with first-ever stroke and those with prior stroke at baseline were analyzed for an association with PFO-related (right-to-left shunt at rest, atrial septal aneurysm, deep venous thrombosis, pulmonary embolism, and Valsalva maneuver) and PFO-unrelated factors (age, gender, BMI, hypertension, diabetes mellitus, hypercholesterolemia, smoking, migraine, coronary artery disease, aortic plaque). A multivariable analysis was used to adjust effect estimation for confounding, e.g., owing to the age-dependent definition of study groups in this cross-sectional study design. Results: We identified 635 patients with first-ever and 53 patients with prior stroke. Age, BMI, hypertension, diabetes mellitus, hypercholesterolemia, coronary artery disease, and right-to-left shunt (RLS) at rest were significantly associated with prior stroke. Using a pre-specified multivariable logistic regression model, age (Odds Ratio 1.06), BMI (OR 1.06), hypercholesterolemia (OR 1.90) and RLS at rest (OR 1.88) were strongly associated with prior stroke.Based on these factors, we developed a nomogram to illustrate the strength of the relation of individual factors to prior stroke. Conclusion: In patients with CS and PFO, the likelihood of prior stroke is associated with both, PFO-related and PFO-unrelated factors.

Brain Volume: An Important Determinant of Functional Outcome After Acute Ischemic Stroke.

OBJECTIVE: To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS). PATIENTS AND METHODS: This study was conducted between July 1, 2014, and March 16, 2019. We analyzed cross-sectional data of the multisite, international hospital-based MRI-Genetics Interface Exploration study with clinical brain magnetic resonance imaging obtained on admission for index stroke and functional outcome assessment. Poststroke outcome was determined using the modified Rankin Scale score (0-6; 0 = asymptomatic; 6 = death) recorded between 60 and 190 days after stroke. Demographic characteristics and other clinical variables including acute stroke severity (measured as National Institutes of Health Stroke Scale score), vascular risk factors, and etiologic stroke subtypes (Causative Classification of Stroke system) were recorded during index admission. RESULTS: Utilizing the data from 912 patients with AIS (mean ± SD age, 65.3±14.5 years; male, 532 [58.3%]; history of smoking, 519 [56.9%]; hypertension, 595 [65.2%]) in a generalized linear model, brain volume (per 155.1 cm3) was associated with age (ß -0.3 [per 14.4 years]), male sex (ß 1.0), and prior stroke (ß -0.2). In the multivariable outcome model, brain volume was an independent predictor of modified Rankin Scale score (ß -0.233), with reduced odds of worse long-term functional outcomes (odds ratio, 0.8; 95% CI, 0.7-0.9) in those with larger brain volumes. CONCLUSION: Larger brain volume quantified on clinical magnetic resonance imaging of patients with AIS at the time of stroke purports a protective mechanism. The role of brain volume as a prognostic, protective biomarker has the potential to forge new areas of research and advance current knowledge of the mechanisms of poststroke recovery.

Postoperative Atrial Fibrillation Following Noncardiac Surgery Increases Risk of Stroke.

BACKGROUND: New-onset postoperative atrial fibrillation is well recognized to be an adverse prognostic marker in patients undergoing noncardiac surgery. Whether postoperative atrial fibrillation confers an increased risk of stroke remains unclear. METHODS: A systematic review and meta-analysis was performed to assess the risk of stroke after postoperative atrial fibrillation in noncardiac surgery. MEDLINE, Cochrane, and EMBASE databases were searched for articles published up to May 2019 for studies of patients undergoing noncardiac surgery that reported incidence of new atrial fibrillation and stroke. Event rates from individual studies were pooled and risk ratios (RR) were pooled using a random-effects model. RESULTS: Fourteen studies of 3,536,291 patients undergoing noncardiac surgery were included in the quantitative analysis (mean follow-up 1.4 ± 1 year). New atrial fibrillation occurred in 26,046 (0.74%), patients with a higher incidence following thoracic surgery. Stroke occurred in 279 (1.5%) and 6199 (0.4%) patients with and without postoperative atrial fibrillation, respectively. On pooled analysis, postoperative atrial fibrillation was associated with a significantly increased risk of stroke (RR 2.51; 95% confidence interval, 1.76-3.59), with moderate heterogeneity. The stroke risk was significantly higher with atrial fibrillation following nonthoracic, compared with thoracic, surgery (RR 3.09 vs RR 1.95; P = .01). CONCLUSION: New postoperative atrial fibrillation following noncardiac surgery was associated with a 2.5-fold increase in the risk of stroke. This risk was highest among patients undergoing nonthoracic noncardiac surgery. Given the documented efficacy of newer anticoagulants, randomized controlled trials are warranted to assess whether they can reduce the risk of stroke in these patients.

Carotid artery stenting: Current state of evidence and future directions.

Both carotid endarterectomy (CEA) and carotid artery stenting (CAS) are common treatments for carotid artery stenosis. Several randomized controlled trials (RCTs) have compared CEA to CAS in the treatment of carotid artery stenosis. These studies have suggested that CAS is more strongly associated with periprocedural stroke; however, CEA is more strongly associated with myocardial infarction. Published long-term outcomes report that CAS and CEA are similar. A reduction in complications associated with CAS has also been demonstrated over time. The symptomatic status of the patient and history of previous CEA or cervical radiotherapy are significant factors when deciding between CEA or CAS. Numerous carotid artery stents are available, varying in material, shape and design but with minimal evidence comparing stent types. The role of cerebral protection devices is unclear. Dual antiplatelet therapy is typically prescribed to prevent in-stent thrombosis, and however, evidence comparing periprocedural and postprocedural antiplatelet therapy is scarce, resulting in inconsistent guidelines. Several RCTs are underway that will aim to clarify some of these uncertainties. In this review, we summarize the development of varying techniques of CAS and studies comparing CAS to CEA as treatment options for carotid artery stenosis.

The 100 most cited articles in the endovascular management of acute ischemic stroke.

BACKGROUND AND PURPOSE: Endovascular thrombectomy (EVT) has revolutionized the management of acute ischemic stroke. Landmark clinical trials have shown EVT to be one of the most efficacious interventions in clinical medicine over the past 5 years. A method of recognition for an article in the scientific community is to use a citation rank list, in order to identify the seminal works in the academic medical literature. The objective of this study was to characterize the 100 most highly cited articles assessing endovascular management of acute ischemic stroke. METHODS: We conducted a retrospective bibliometric analysis using the Web of Science Citation Index Expanded database for the most cited works in the endovascular management of acute ischemic stroke. Citation count was used to rank the top 100 articles, which were then analyzed for authorship, year of publication, subject, study type, level of evidence, and subject. RESULTS: The mean number of citations was 245 (range 65-1726) and 394 on Google Scholar. The top 100 articles were cited an average of 43.9 times per year and published in 21 journals in the past two decades. The majority of papers (62) were classified as constituting levels 1, 2, or 3 evidence, and included 17 randomized controlled trials. Approximately two-thirds of the top 100 articles originated from the USA. CONCLUSIONS: This study details the most cited articles in the endovascular management of acute ischemic stroke, and furthermore shows that a high proportion of level I evidence exists for this intervention.