Barrett, Kevin M.

Introduction: Carotid revascularization is known to prevent stroke in patients with high-grade carotid stenosis, but whether carotid revascularization may slow the progression of hemispheric WMD in patients with carotid stenosis to prevent cognitive decline have not been well described. Methods: We conducted a longitudinal study involving patients age ≥40 years with carotid stenosis on ultrasound from 2011-2015 with serial brain MRI scans at least 1 year apart followed for radiographic and clinical outcomes to 2020. Severity of carotid stenosis was defined as moderate 50-69%, high-grade 70-99%, or occluded. Hemispheric WMD volume was quantified from axial T2 FLAIR images. Patients were stratified by revascularization status. Primary outcome was change in WMD volume per year ipsilateral or contralateral to the index carotid. Hemispheric differences in the annual rate of WMD progression (cc/yr) were compared between revascularized vs not revascularized using multivariable linear regression analysis adjusted for variables that differed between revascularization status. Results: Of the 150 patients, moderate stenosis was present in 37.3%, high-grade stenosis in 42.0%, and carotid occlusion in 20.7%. Mean age was 71±10 years, 36.7% were female. Seventy-three (48.7%) had carotid revascularization with a median follow-up of 5.1 years. Baseline WMD volume was 4.86cc ipsilateral and 4.39cc contralateral to the index carotid. Patients who underwent revascularization trended to have slower WMD progression in the hemisphere ipsilateral to the index carotid compared to those not revascularized (0.32cc/yr vs 0.63 cc/yr, p=0.340). The same trend was not observed in the contralateral hemisphere. In adjusted models, carotid revascularization was associated with a 0.33 cc per year decrease in WMD progression between hemispheres compared to those not revascularized (β= -0.33, p=0.070). Conclusions: In this study with a median follow-up of 5 years, we found that carotid revascularization resulted in a 50% reduction in the annual rate of WMD progression. Intervention trials should test whether carotid revascularization slows WMD progression in patients with cognitive impairment to prevent further cerebrovascular events and cognitive decline.

Introduction: Collateral circulation plays a crucial role in determining the extent of brain tissue ischemia and functional outcome in large vessel occlusive (LVO) stroke. Heart failure (HF) is known to cause cerebral hypoperfusion, yet the relationship between HF and robustness of collateral flow has not been well described. Here we hypothesized that HF is associated with poor collateral flow and functional outcome in patients presenting with LVO treated with mechanical thrombectomy (MT). Methods: A single center retrospective study of patients presenting with LVO ischemic stroke who underwent MT between 2012-2020 was done. Single-phase CTA of head prior to MT was used to assess collateral status with poor status defined as ≤ 50% filling and good status as >50% filling. Classification of HF by left ventricular ejection fraction (LVEF) on echocardiogram was used where HF with reduced ejection fraction (HFrEF) had LVEF ≤40%, HF with preserved EF (HFpEF) had LVEF ≥50% with evidence of structural heart disease, and no HF was LVEF≥50% without structural heart disease. Functional outcome was modified Rankin scale (mRS) at 90 days with scores of 0-2 representing good outcome and 3-6 representing poor outcome. Multivariable logistic regression analyses were performed to evaluate the association between HF and poor collaterals after adjusting for vascular risk factors. Results: We identified 235 patients, mean age was 69 ±15 years, median NIHSS was 18, and 45.5% had HF (HFrEF 12.8%, HFmrEF 4.7%, HFpEF 28.1%) while 54.5% had no HF. Poor collaterals were seen in 47.7%, and those with HF were likely to have poor collaterals compared to those without HF (56.1% vs 35.1%, P=.001). There was a dose-dependent relationship between severity of HF and poor collaterals: adjusted odds of poor collaterals were 1.63 and 2.45 in HFpEF and HFrEF, compared to those without HF (trend p=.018). Patients with poor collaterals were likely to have poor outcome at 3 months compared to those with good collaterals (75.0% vs 57.8%; p=.015). Conclusion: Patients with HFrEF were twice as likely to have poor collaterals. This study demonstrated a likely mechanism for poor outcomes seen in ischemic stroke with HF, future studies may explore whether optimization of HF may augment collaterals to improve outcomes.

Background: Causative Classification of Stroke (CCS) system is a novel, web-based, and fully-computerized algorithm that integrates clinical, diagnostic, and etiologic stroke characteristics in an evidence-based manner (available at http://ccs.mgh.harvard.edu ) and provides in a given patient both phenotypic subtypes where abnormal evaluation findings are simply organized in major etiologic categories and causative subtypes where abnormal evaluation findings are filtered through a decision making process to identify the most likely cause of stroke. In this study, we sought to identify the concordance between phenotypic and causative CCS subtypes in the NINDS Stroke Genetics Network (SiGN). Methods: A total of 24 adjudicators from 15 US and European sites certified in CCS retrospectively determined CCS subtypes through chart review in 7134 patients. The CCS software provided causative subtypes in 3 confidence levels as “evident”, “probable” or “possible” based on the weight of causal evidence. We estimated how often CCS classified a given major abnormal evaluation finding as the causative stroke mechanism. Results: CCS assigned 55% of patients with the phenotype of moderate-to-severe atherosclerotic stenosis into the causative category of “evident large artery atherosclerosis”. Likewise, 50% of patients with a major cardiac source (such as atrial fibrillation) were classified into “evident cardio-aortic embolism”, and 74% of those with imaging evidence of a typical lacunar infarct into “evident small artery occlusion”. In 20% to 30% of patients, phenotypic and causative categories were the same but the causative subtype was assigned with a lower level of confidence. Six to 20% of patients with a given phenotypic feature were classified into a different causative category. Failure to investigate for other subtypes in the presence of a positive test finding and the presence of multiple competing etiologies were key contributors to the observed disconcordance between phenotypic and causative subtypes. Conclusions: Our findings show that the presence of a major abnormality in stroke evaluation does not necessarily mean that it is always the cause. The ability of CCS system to discriminate between phenotypic and causative characteristics of stroke etiology provides the opportunity to refine stroke phenotypes for use in research studies.

Introduction: Patients with carotid stenosis may have silent cerebrovascular disease due to chronic hypoperfusion and atheroembolism. If so, progression of silent disease may be preventable through revascularization. We aim to evaluate the association between carotid stenosis/occlusion and cerebral small vessel disease (SVD) burden ipsilateral to the cervical carotid stenosis. Methods: Patients age ≥40 years with carotid stenosis or occlusion on carotid ultrasound who underwent MRI brain and intracranial angiogram with gradable SVD on MRI from 2011-2015 were included. Severity of carotid stenosis was defined using NASCET criteria as 50-69% (moderate), 70-99% (high-grade), or occluded. WMH volume was quantified using an automated artificial intelligence algorithm applied to axial T2 FLAIR images. Images were also scored for presence of chronic lacune, cerebral microbleeds (CMB), and silent infarcts using STRIVE criteria. Differences in WMD volume between hemispheres ipsilateral and contralateral to the carotid stenosis were calculated, and prevalence of SVD and silent infarct were compared across severities of carotid stenosis. Results: Of the 183 patients, mean age was 71±10 years and 38% were female. Moderate and severe stenosis was present in 36% and 46.5%, respectively, and 18% had carotid occlusion. Mean WMH volume was 7271±522mm 3 . Patients with carotid stenosis had greater WMH volume ipsilateral to the side of carotid stenosis than the contralateral side (mean difference 224±206mm 3 ), and higher severity of stenosis was associated with greater hemispheric difference in WMH volume (moderate vs high; 164±274mm 3 vs 743±309 mm 3 , p=0.009). Silent infarcts were more prevalent in high-grade carotid stenosis than moderate grade (moderate vs high, 10.8% vs 36.5%; p=0.002). There were no differences in either lacunae or CMBs across severities. Conclusions: Greater than one third of patients with high-grade carotid stenosis had ipsilateral silent brain infarction, and the volume of WMH was greater on the side of carotid stenosis. Future analyses should consider the potential yield of screening for carotid atherosclerosis in patients with varying degrees of hemispheric WMH asymmetry.

The recognition and management of stroke in the prehospital setting has become increasingly important to improve patient outcomes. Several strategies to advance prehospital stroke care have been developed, including the mobile stroke unit and the telemedicine-enabled ambulance—or “mini-MSU.” These strategies both incorporate ambulance-based audio-visual telemedicine evaluation with a vascular neurologist to facilitate faster treatment but differ in several areas including upfront and recurring costs, scalability or growth potential, ability to integrate into existing emergency medical services systems, and interoperability across multiple specialties or conditions. While both the mobile stroke unit and mini-mobile stroke unit model are valid approaches to improve stroke care, the authors aim to compare these models based on costs, scalability, integration, and interoperability in order to guide our prehospital leaders to find the best solutions for their communities.

Objectives: Identification of gene variants of stroke subtypes is important for the development of tailored ischemic stroke therapies among various ethnic groups. Valid and reliable determination of ischemic stroke subtype is essential for achieving this goal and to standardize a classification scheme across multi-center studies and different populations. Causative Classification System for Ischemic Stroke (CCS) is a novel computerized subclassification tool developed to improve reliability and accuracy of classifying stroke types. The CCS algorithm relies on both phenotypic and causative stroke variables. A Hispanic subset of the SiGN, an important and distinct target population with greater risk of certain stroke subtypes, was evaluated with Trial of Org 10172 in Acute Stroke Treatment (TOAST) and CCS and the agreement between the two classification systems was analyzed. Methods: Over 6000 subjects at 15 sites across US and Europe were enrolled, with TOAST and CCS locally adjudicated. Blood collection and central data quality control (10% central readjudication) were performed on all participants. A subset of Hispanics was analyzed for the purpose of this study and the agreement between the TOAST and CCS were assessed by kappa statistic. Findings: Hispanics (n=595, 10.9%) compared to non-Hispanics (n=5457) were more likely to be younger (63.7 vs. 64.0), male (55% vs. 46%) and have fewer of the traditional stroke risk factors HTN (54% vs. 64%), Afib (11% vs. 14%), DM(23% vs. 25%), CAD(16% vs. 20%) and smoking(19% vs. 22%). While the TOAST showed no differences between stroke subtypes for Hispanic vs. non-Hispanics, in CCS, Hispanics were classified with more of large vessel (22% vs. 20%), cardioembolic (37% vs. 30%) and small vessel strokes (13% vs. 9%) and fewer with undetermined etiology (28% vs. 40%) as compared to non-Hispanics. TOAST and CCS offered moderate correlation across all stroke types in Hispanics: kappa of 0.66 for large artery atherosclerosis, 0.58 for cardioembolic, and 0.58 for small artery occlusion. Conclusion: CCS offers a more sensitive and accurate system for subphenotyping of strokes in Hispanics who tended to have relatively fewer risk factors and unclassified strokes. Further studies correlating the two classification systems and their relation to genotyping data are warranted.

Background: The Stroke Genetics Network (SiGN) funded by the NINDS aims to identify genetic risk factors in ischemic stroke using whole-genome association studies (GWAS). High quality phenotyping is crucial to successful application of GWAS. As a heterogenous disorder, stroke poses specific challenges. The Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification is a broadly used, but its validity is challenged especially when performed by multiple investigators with differing interpretations of the system. The Causative Classification System for Ischemic Stroke (CCS) system is a new, web-based, and computerized algorithm that integrates clinical, diagnostic, and etiologic stroke characteristics in an evidence-based manner ( ccs.mgh.harvard.edu ) to generate subtypes. Methods: In planning the SiGN proposal, a sample of 20 coded charts were collected from a subset of participating studies to assess feasibility of central adjudication and comparability to study-specific TOAST. Two central adjudicators reviewed all records and generated TOAST and CCS subtypes. These were compared to study-specific TOAST subtype and the CCS phenotype generated for SiGN by local trained adjudicators. CCS data is now available for 7134 included cases using both a 5 and a 7 category system as defined in the table . Results: All 4 phenotypes were available for 115 ischemic stroke cases from 6 studies in SiGN. Basic demographics were 54% women, 63% white, and median age between 65-74. Table 1 provides the agreement between the various subtypes. Table 2 describes the types of disagreement. Conclusions: Central adjudication with only two adjudicators and curated medical records yielded more consistent subtyping independent of phenotyping system. The agreement for TOAST was higher than published rates by independent groups (∼0.50). In contrast, the agreement for CCS was lower than previously published (0.85-0.95). Site adjudicators' familiarity with TOAST and inexperience with CCS may contribute. Although CCS is an automated algorithm and has a number of user friendly features, our findings suggest that formal training and certification process before starting to use CCS may be worthwhile to achieve optimal benefit from the system.