Southerland, Andrew M.

Telemedicine for stroke (Telestroke) has been a key component to efficient, widespread acute stroke care for many years. The expansion of reimbursement through the Furthering Access to Stroke Telemedicine Act and rapid deployment of telemedicine resources during the COVID-19 public health emergency have further expanded remote care, with practitioners of varying educational backgrounds, and experience providing acute stroke care via telemedicine (Telestroke). Some Telestroke practitioners have not had fellowship-level vascular neurology training and many are without training specific to virtual modalities. While many vascular neurology fellowship programs incorporate Telestroke training into the curriculum, components of this curriculum are not consistent, extent of involvement is variable, and not all fellows receive hands-on training in remote care. Furthermore, the extent of training and evaluation of Telestroke in American Board of Psychiatry and Neurology training requirements and Accreditation Council for Graduate Medical Education assessments for vascular neurology fellowship are not standardized. We suggest that Telestroke be formally incorporated into vascular neurology fellowship curricula and provide considerations for key components of this training and metrics for evaluation.

Introduction: Intracranial aneurysm (IA) and abdominal aortic aneurysm (AAA) rupture carry high mortality (40% and 75% respectively) and substantial morbidity in survivors. Recent research suggests that IA and AAA share genetic risk in addition to environmental factors. Retrospective data from our institution identified a population harboring both IA and AAA and showed a high rupture rate for IA (44.2%). We previously demonstrated that screening for AAA in patients with IA is cost-effective based on estimated and published data. We hypothesize that screening for IA in patients with AAA is also cost-effective. Method: We developed a decision-making model using TreeAge Pro 2013 software assuming a hypothetical population with known AAA and truncated screening versus no screening for IA using magnetic resonance angiography. Based on IA size and location, patients were either treated endovascularly or placed on surveillance. Proportions, risks, utilities, and costs for each decision arm were derived from literature. Results: At a given rupture rate, incremental effectiveness varied linearly with coprevalence of AAA and IA. For an assumed rupture rate of 5%/year, screening was effective for coprevalence >6.8% (top graph) and was cost-effective for coprevalence >7.7%. The incremental cost-effectiveness ratio (ICER) favored screening (ICER=$54,193/QALY) at a 7.8% coprevalence and dropped to $27,841.50/QALY at 8.8% coprevalence. Our model was sensitive to IA rupture rate as well as coprevalence (bottom graph). Conclusion: Our model suggests the cost-effectiveness of screening for IA in patients with AAA, below the accepted societal threshold of an ICER $60,000/QALY at a coprevalence ≥7.8% and IA rupture rate ≥5%. These are plausible assumptions for this genetically high-risk population. Further prospective study is warranted to establish coprevalence of AAA and IA, rupture rates, and determine the benefit of dedicated screening.

Introduction: Estrogens have been associated with risk of stroke in both men and women. Estradiol and estrone are synthesized from testosterone via the aromatase enzyme in both men and postmenopausal women. Genetic variation affecting function of the aromatase gene (CYP19A1) has been linked to elevated estradiol levels. We tested the hypothesis that these variants, as well as a modifying gene, are associated with ischemic stroke in three cohorts: the Vitamin Intervention for Stroke Prevention trial (VISP), Women’s Health Initiative (WHI), and Genetic Susceptibility to Early-Onset Stroke study (GEOS). Methods: Genomic data for individuals of European descent with ischemic stroke was compared against an equal number of controls: VISP (1723 cases - 65% men), WHI (436 cases - all postmenopausal women), GEOS (557 cases - all men age <55). Genotyping was funded through the Genomics and Randomized Trials Network (GARNET) and Gene Environment Association Studies (GENEVA) consortia. All cohorts used the Illumina Omni1-Quad chip for genotyping with imputation as needed. Eight candidate single nucleotide polymorphisms (SNPs) in CYP19A1 on chromosome 15 and an additional regulatory SNP in a modifier locus on chromosome 8 were chosen for analysis due to coding status or previous association with estradiol levels. Analyses were adjusted for age, hormone therapy use (women), and the top three principal components. Association results were determined as odds ratios for individual SNPs (effect allele = minor), with significance level of p<0.05. Results: GWAS results are tabulated. There were no significant differences in allele frequency for four SNPs in CYP19A1 among stroke patients and controls. The additional four SNPs were monomorphic in all three populations. The modifier gene SNP (rs1864729) was less common among young men with prior stroke in GEOS, but not men in VISP or in women. Conclusions: Aromatase genetic variation was not associated with risk of stroke in these three cohorts. One SNP that modifies aromatase function was less common among young, but not older men with stroke. Replication in other studies is necessary.

BACKGROUND: Recent genome-wide association studies (GWAS) have identified a number of novel SNPs associated with blood pressure and hypertension-related traits although studies were very large (approaching 80K participants) and effect sizes were modest with per allele effect sizes as small variants as a single millimeter of mercury difference in blood pressure. However, because hypertension is the most potent modifiable risk factor for ischemic stroke, lowering blood pressure by a few mm Hg can translate into measurable decrease in stroke risk. METHODS: We investigated 22 hypertension (HTN) associated SNPs in a case-control analysis of ischemic stroke in multiple stroke studies including the Siblings With Ischemic Stroke Study (SWISS), the Ischemic Stroke Genetics Study (ISGS), the Bio-Repository of DNA in Stroke (BRAINS), the Vitamin Intervention for Stroke Prevention (VISP) trial, and the Women's Health Initiative (WHI). SWISS/ISGS/BRAINS were analyzed together and included subtype information. Genotyping was funded through the individual studies, the Genomics and Randomized Trials Network (GARNET) consortium, and the SHARe (SNP Health Association Resource). All studies had both raw and imputed GWAS data. Analyses included the following phenotypes: all ischemic stroke, stroke subtypes, and age-at-stroke-onset and were stratified by race. Analyses were minimally adjusted for age, sex and principal components 1 & 2. Alpha was set at 0.05. RESULTS: Eleven of the SNPs from the HTN GWAS were associated with ischemic stroke in European ancestry from one or more of the study populations. Two SNPs on chromosome 12 and one on chromosome 21 were associated in multiple European ancestry cohorts. No SNP was associated in all studies. A SNP previously associated with HTN in African ancestry populations was associated with stroke in African-Americans. Analysis of subtypes found associations with small vessel disease and cardioembolic stroke but not large artery disease. The case-only age-at-stroke-onset analysis also found associations for the two SNPs on chromosome 12. CONCLUSION: These data suggest that candidate SNPs from a HTN GWAS may be associated with ischemic stroke and warrant further investigation. Racial differences were observed. Replication in populations from the other SiGN (Stroke Genetics Network), GENEVA (Gene Environment Association Studies) consortium, and the ISGC (International Stroke Genetics Consortium) studies are underway.

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: Abdominal aortic aneurysm (AAA) rupture is associated with high mortality and morbidity. The U.S. Preventive Services Task Force recommends one-time ultrasound screening for AAA in men age 65-75 who have ever smoked. Little is known about other high-risk subpopulations. Recent linkage and genome-wide association studies confirm a shared genetic risk between AAA and intracranial aneurysms (IA). We tested the hypothesis that sonographic screening for AAA in individuals known to have IA is cost-effective. Methods: A decision tree model was developed to compare costs and outcomes of AAA screening compared to no screening in a hypothetical cohort of patients with IA. Event probabilities, utilities, and costs included in the model were derived through a comprehensive literature review. Expected outcomes of screening vs. no screening were measured in terms of quality-adjusted life years (QALY), lifetime costs and the overall cost-effectiveness ratio. Sensitivity analyses were performed to assess the effects of ranging baseline variables, within plausible minimum and maximum values, on model outcomes, as well as to identify thresholds of model variables where a decision alternative was dominated (both more expensive and less effective than the alternative). Results: In our base-case analysis, screening for AAA provided an additional 0.1055 QALYs (28.1521-screening, 28.0466-no screening) at an additional lifetime cost of $3.62 ($374.57-screening and $370.95-no screening). This yielded an incremental cost-effectiveness ratio (ICER) of $34.31/QALY. In sensitivity analyses, a prevalence of AAA in the IA population ≥ 7.5%, sensitivity of ultrasound screening ≥ 91%, or extrapolating the risk of AAA rupture to 6 years each caused the screening arm to dominate the model. Conclusion: Based on this model, screening for AAA in individuals with IA is cost-effective with an ICER of $34.31/QALY. This is well below accepted societal thresholds estimated to be less than $50,000/QALY. The sensitive variables in the model, particularly co-prevalence of IA and AAA, favored screening within conservative estimates from the literature. Prospective study evaluating the co-prevalence of IA and AAA will further elucidate the value of dedicated screening.

Background: Considerable disagreement exists among experts regarding the appropriate extent of diagnostic testing after ischemic stroke (IS). Evidence-based data guiding stroke evaluation for individual patients according to the underlying phenotype are unknown. We sought to determine the yield of cardiac and arterial evaluations for identifying an alternative major stroke etiology in patients with a given phenotype in the NINDS Stroke Genetics Network (SiGN). Methods: SiGN is a consortium of IS studies at 22 US and European sites aiming to identify stroke susceptibility genes. Adjudicators certified in Causative Classification of Stroke (CCS) system determined major etiologic stroke phenotypes based on chart review. All diagnostic data entered into the CCS software were stored in a confidential database. We determined the probability of identifying an alternative major abnormality based on cardiac (history, EKG, echocardiography) and arterial [intracranial (IC), extracranial (EC)] evaluations in 3 stroke phenotypes: lacunar infarct (LI), large artery atherosclerosis (LAA), and cardiac embolism (CE). Proportions of alternative major etiologies were calculated in patients with complete evaluations in each phenotype. Results: The analyses included 15720 patients. Among these, 2299 had phenotypic subtype of LI (1660 with cardiac and 1691 with arterial evaluations); 4228 had CE (2451 with arterial evaluation); and 2613 had LAA (2047 with cardiac evaluation). Cardiac evaluation revealed a major cardiac source of embolism in 12.3% of patients with LI and 20.3% with LAA. Echocardiography demonstrated an additional major structural cardiac source not seen by history/examination/EKG in 1.9% and 1.6% in LI and LAA respectively. Arterial evaluation led to the identification of ≥50%ipsilateral stenosis in 13.5% (IC: 8.9%, EC: 5.8%) of patients with LI and 17% (IC: 8.1%, EC: 11.3%) of those with CE. In LI patients with complete cardiac and vascular evaluations, 24.1% had an alternative major stroke etiology. Conclusions: A considerable proportion of IS patients with LI, LAA, and CE harbor an alternative major etiology. In the future, these results can be used to generate evidence-based and cost-effective evaluation and management strategies.

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.

Background: The risk for intracranial (IA) and abdominal aortic aneurysms (AAA) is partially heritable, with evidence mounting in favor of shared genetic risk for both. Methods: The Brain and Aortic Aneurysm Study (BAAS, NCT#17341) at University of Virginia seeks to determine the coprevalence of IA and AAA recruiting patients presenting with an aneurysm at one site and screening for aneurysm at the other. Participants undergo genetic screening and an interview where clinical, demographic, and radiographic data are collected. Recruitment and screening are ongoing, so preliminary demographic data regarding between group differences (IA vs. AAA) are presented. All clinical and demographic data were collected and recorded in REDCap and exported to Excel. We compared a total of 256 participants (IA=164, AAA=92) for demographic factors: age, sex, smoking and past medical history. Results: The AAA cohort was older (70.98 vs. 58.51, p<.001) and more male (79.34% vs. 23.78% p<.001). The AAA cohort had a higher proportion with diabetes mellitus (28.26% vs. 15.24%, p=.012), with hyperlipidemia (67.39% vs. 44.51%, p<.001) and higher smoking pack years (44.07 vs. 17.85, p<.001). The two groups did not differ in proportion with hypertension, coronary artery disease, or peripheral vascular disease (all p>.05). Conclusions: These data suggest that there may be subtle differences in the clinical profile of patients presenting with IA and AAA, especially when considering known aneurysmal risk factors like hypertension, diabetes, and smoking history. Further analyses will consider whether these factors modulate the coprevalence of the two types of aneurysms.