Virtual International Stroke Trials Archive Research Articles

Enlarged perivascular spaces and cognitive impairment after stroke and transient ischemic attack.

Background Previous studies suggested that enlarged perivascular spaces are neuroimaging markers of cerebral small vessel disease. However, it is not clear whether enlarged perivascular spaces are associated with cognitive impairment. We aimed to determine the cross-sectional relationship between enlarged perivascular spaces and small vessel disease, and to investigate the relationship between enlarged perivascular spaces and subsequent cognitive impairment in patients with recent cerebral ischemic event. Methods Anonymized data were accessed from the virtual international stroke trial archive. We rated number of lacunes, white matter hyperintensities, brain atrophy, and enlarged perivascular spaces with validated scales on magnetic resonance brain images after the index stroke. We defined cognitive impairment as a mini mental state examination score of ≤26, recorded at one year post stroke. We examined the associations between enlarged perivascular spaces and clinical and imaging markers of small vessel disease at presentation and clinical evidence of cognitive impairment at one year using linear and logistic regression models. Results We analyzed data on 430 patients with mean (±SD) age 64.7 (±12.7) years, 276 (64%) males. In linear regression analysis, age (β = 0.24; p < 0.001), hypertension (β = 0.09; p = 0.025), and deep white matter hyperintensities (β = 0.31; p < 0.001) were associated with enlarged perivascular spaces. In logistic regression analysis, basal ganglia enlarged perivascular spaces were independently associated with cognitive impairment at one year after adjusting for clinical confounders (OR = 1.72, 95% CI = 1.22-2.42) and for clinical and imaging confounders (OR = 1.54; 95% CI = 1.03-2.31). Conclusions Our data show that in patients with ischemic cerebral events, enlarged perivascular spaces are cross-sectionally associated with age, hypertension, and white matter hyperintensities and suggest that enlarged perivascular spaces in the basal ganglia are associated with cognitive impairment after one year.

Impact of heart rate on admission on mortality and morbidity in acute ischaemic stroke patients - results from VISTA.

Elevated heart rate (HR) is associated with worse outcomes in patients with cardiovascular disease. Its predictive value in acute stroke patients is less well established. We investigated the effects of HR on admission in acute ischaemic stroke patients. Using the Virtual International Stroke Trials Archive (VISTA) database, the association between HR in acute stroke patients without atrial fibrillation and the pre-defined composite end-point of (recurrent) ischaemic stroke, transient ischaemic attack (TIA), myocardial infarction (MI) and vascular death within 90 days was analysed. Pre-defined secondary outcomes were the composite end-point components and any death, decompensated heart failure and degree of functional dependence according to the modified Rankin Scale after 90 days. HR was analysed as a categorical variable (quartiles). In all, 5606 patients were available for analysis (mean National Institutes of Health Stroke Scale 13; mean age 67 years; mean HR 77 bpm; 44% female) amongst whom the composite end-point occurred in 620 patients (11.1%). Higher HR was not associated with the composite end-point. The frequencies of secondary outcomes were 3.2% recurrent stroke (n = 179), 0.6% TIA (n = 35), 1.8% MI (n = 100), 6.8% vascular death (n = 384), 15.0% any death (n = 841) and 2.2% decompensated heart failure (n = 124). Patients in the highest quartile (HR> 86 bpm) were at increased risk for any death [adjusted hazard ratio (95% confidence interval) 1.40 (1.11-1.75)], decompensated heart failure [adjusted hazard ratio 2.20 (1.11-4.37)] and worse modified Rankin Scale [adjusted odds ratio 1.29 (1.14-1.52)]. In acute stroke patients, higher HR (>86 bpm) is linked to mortality, heart failure and higher degree of dependence after 90 days but not to recurrent stroke, TIA or MI.

Rate of perihaematomal oedema expansion is associated with poor clinical outcomes in intracerebral haemorrhage

BackgroundPerihaematomal edema (PHE) expansion rate may be a predictor of outcome after intracerebral haemorrhage (ICH). We determined whether PHE expansion rate in the first 72 hours after ICH predicts outcome,...

Determinants of post-stroke cognitive impairment: analysis from VISTA.

Post-stroke cognitive impairment (PSCI) occurs commonly and is linked with development of dementia. We investigated the relationship between demographic, clinical and stroke symptoms at stroke onset and the presence of PSCI at 1 and 3years after stroke. We accessed anonymized data from the Virtual International Stroke Trial Archive (VISTA), including demographic and clinical variables. Post-stroke cognitive impairment was defined as a Mini-Mental State Examination (MMSE) score of ≤26. We assessed univariate relationships between baseline stroke symptoms and PSCI at 1 and 3years following stroke, retaining the significant and relevant clinical factors as covariates in a final adjusted logistic regression model. We analysed data on 5435 patients with recent (median 33days) stroke or transient ischaemic attack (TIA). Mean (±SD) age was 62.6 (±12.6) years; 3476 (65%) patients were male. Follow-up data were available for 2270 and 1294 patients at 1 and 3years, respectively. At 1year, 781 (34%) patients had MMSE≤26; at 3years, 391 (30%) had MMSE≤26. After adjusting for age, stroke severity, hypertension, diabetes and type of qualifying event, initial stroke impairment (leg paralysis) was associated with increased rate of PSCI at 1year (OR=1.62; 95% CI=1.20-2.20) and at 3years (OR=1.95; 95% CI=1.23-3.09). Associations were consistent on subgroup analysis restricted to ischaemic stroke and transient ischaemic attack (N=4992). Besides well-known determinants of PSCI such as age, stroke severity and the presence of vascular risk factors, also leg paralysis is associated with subsequent of PSCI up to 3years after stroke.

Prophylactic Use of Antiepileptic Drugs in Patients with Spontaneous Intracerebral Hemorrhage

The effect of prophylactic antiepileptic drugs (AEDs) on mortality and functional outcome in patients with intracerebral hemorrhage (ICH) is uncertain. We used data from the Virtual International Stroke Trials Archive (VISTA) to evaluate the effect of prophylactic AEDs on ICH outcome. Univariate and multivariate logistic and Cox regression models were designed to determine the impact of prophylactic AEDs on mortality and disability, defined as a modified Rankin Scale (mRS) greater than 3 at 90 days following ICH. Of the 802 patients with ICH, 81 (10%) received prophylactic AEDs. Patients who received AED prophylaxis had higher ICH volume (median 23.2 cm(3) [IQR 10.5-38.0] versus 14.3 cm(3) [IQR 7.1-27.0], P= .001) and ICH score (median 1 cm(3) [IQR 0-2] versus 1 cm(3) [IQR 0-1], P = .03). In univariate analyses, AED prophylaxis was associated with higher probability of mRS greater than 3 at 90 days (62% versus 49%, P = .03) and a trend towards increased mortality (27% versus 18%, P = .06). Although seizure did not influence ICH outcome, any AED prophylaxis and phenytoin use in particular were both associated with mRS greater than 3 at 90 days (OR 1.66 [1.04-2.66], P = .03 for any AED; OR 1.97 [1.06-3.67], P = .03 for phenytoin prophylaxis) in univariate analyses. After adjustment for components of the ICH score, none of these associations remained significant. Patients with higher ICH scores and larger hemorrhages are more likely to receive prophylactic AEDs. We found no independent effect of prophylactic AED treatment on outcome after ICH.

Derivation and Validation of a Modified Short Form of the Stroke Impact Scale.

BackgroundThe Stroke Impact Scale (SIS) is a stroke‐specific, quality of life measure recommended for research and clinical practice. Completion rates are suboptimal and could relate to test burden. We derived and validated a short form SIS (SF‐SIS).Methods and ResultsWe examined data from the Virtual International Stroke Trial Archive, generating derivation and validation populations. We derived an SF‐SIS by selecting 1 item per domain of SIS, choosing items most highly correlated with total domain score. Our validation described agreement of SF‐SIS with original SIS and the SIS‐16 and correlation with Barthel Index, modified Rankin Scale, National Institutes of Health Stroke Scale, and Euro‐QoL 5 dimensions visual analog scales. We assessed discriminative validity (associations between SF‐SIS and factors known to influence outcome [age, physiological parameters, and comorbidity]). We assessed face validity and acceptability by sharing the SF‐SIS with a focus group of stroke survivors and multidisciplinary stroke healthcare staff. From 5549 acute study patients (mean age 68.5 [SD 13] years, mean SIS 64 [SD 32]) and 332 rehabilitation patients (mean age 65.7 [SD 11] years, mean SIS 61 [SD 11]), we derived an 8‐item SF‐SIS that demonstrated good agreement with original SIS and good correlation with our chosen functional and quality of life measures (all ρ>0.70, P<0.0001). Significant associations were seen with our chosen predictors of stroke outcome in the acute group (P<0.0001). The focus group agreed with the choice of items for SF‐SIS across 7 of 8 domains. ConclusionsUsing multiple, complementary methods, we have derived an SF‐SIS and demonstrated content, convergent, and discriminant validity. This shortened SIS should allow collection of robust quality of life data with less associated test burden.

Early Versus Late Assessment of Stroke Outcome.

What is the best timing for outcome assessment in patients with severe stroke in randomized controlled trials; early assessment at 3 months versus later at 6 to 12 months? Kennedy R. Lees The purpose of a clinical trial is usually to assess whether and to what extent a treatment improves outcome and to identify the type and frequency of any associated risks. The question that is posed here refers only to acute trials, in which enrollment occurs within hours after stroke onset and treatment is exhibited and probably completed within at most a few days. We can reasonably assume that the treatment exerts its beneficial effect only while it is being administered and that any adverse effects are similarly acute in onset. Patients with acute stroke, and especially patients with severe stroke, are typically elderly and have elevated risk of cardiovascular disease; indeed, stroke survivors are more likely to die from cardiovascular disease than recurrent stroke. Long-term follow-up will dilute effects of treatment with other events that are part of the natural history of the condition. Any benefit may be revealed reasonably quickly, but with extended follow-up, there is an inevitable convergence of outcomes between treatment groups as complications of age, and associated risk factors come into play. We must, therefore, look at the natural history of outcomes after stroke, especially among patients with initially severe stroke, to see when recovery typically reaches its plateau at the group level. Data from the Virtual International Stroke Trials Archive, 2015 (Dr Rachael MacIsaac, personal communication) on the distribution of outcomes across 1 year assessed by modified Rankin Scale (mRS) among 159 ischemic stroke patients with admission National Institutes of Health Stroke Scale score of ≥20 indicate that the proportions of patients with good outcomes—mRS scores of 0, 1, 2, 3, or 4—each …

Abstract WP354: Prophylactic Anti-epileptic Drugs and Spontaneous Intracerebral Hemorrhage

Introduction: Seizure is a common complication after intracerebral hemorrhage (ICH) but there are conflicting data about the impact of seizure on ICH outcome and the clinical utility of prophylactic antiepileptic drugs (AEDs) in ICH treatment. Hypothesis: We hypothesized that prophylactic AEDs would be associated with worse outcomes after ICH. Methods: We queried the Virtual International Stroke Trials Archive (VISTA), and identified 802 ICH patients who were followed for 90 days in prior clinical trials. Uni- and multivariate logistic and Cox regression models were designed to evaluate the effect of prophylactic AEDs on ICH outcome reflected by mortality and modified Rankin Scale (mRS)&gt;3 at 90 days. Results: Eighty two (10.2%) subjects received prophylactic AEDs after ICH. Patients who received AED prophylaxis had higher ICH volume (median [IQR] 23.2 [10.5, 38.0] vs. 14.3 [7.1, 27.0] cm3, P=0.001), and ICH score (1 [0, 2] vs. 1 [0, 1], P=0.028). In univariate analysis (Table), patients who received prophylactic AEDs had higher mRS at 90 days (4 [2, 6] and 3 [2, 5], P=0.03), and numerically greater mortality (27% vs. 18%, P=0.06). Phenytoin was the most commonly used AED and appeared to have a larger effect size than other AEDs. The ICH score and its components were strongly associated with outcomes (Table). Multivariable models adjusting for ICH score components attenuated the effect of prophylactic AEDs overall (mRS OR 1.33, 95% CI: 0.78-2.26, P=0.29; mortality HR 1.14, 95% CI: 0.72-1.80, P=0.58). Similar results were obtained for mRS and mortality outcomes when adjusted for overall ICH score, and for all AEDs as well as specifically for phenytoin. Conclusion: Patients with higher ICH scores and larger hemorrhages are more likely to receive prophylactic AEDs and more likely to have poor outcomes. In this large multitrial cohort from VISTA, prophylactic AEDs were not independently associated with outcome after adjustment for these confounders.

Abstract TP368: Prediction of Hemorrhagic Growth Using Textural Pattern Analysis

Introduction: The subjective characterization of non-contrast CT “swirl sign” along with hematoma volume have been used to predict intracerebral hemorrhage (ICH) growth. As early assessment of patients with acute stroke symptoms can be used to optimize treatment, a more robust, quantitative biomarker set could improve patient care. Hypothesis: Quantification of ICH lesion texture from CT scans taken at less than 3 hours from onset could be used to predict hemorrhagic growth at 24 hours. Methods: Baseline and 24-hour CT scans on 71 ICH stroke subjects were obtained from the Virtual International Stroke Trials Archive (VISTA). Semi-automated segmentation of ICH was used to determine lesion volume. Based on treatment effects seen with hemostatic agents, a 6mL absolute increase was initially selected for the growth threshold. First order statistics of CT pixel values within the lesions along with spatial parameters extracted from grey-level co-occurrence matrices (GLCM) were computed, as well as baseline lesion volume, location (deep/lobar), number of connected components, and information about intraventricular hemorrhage. Linear support vector machines were used for classification with 10-fold cross-validation. Results: By the 24-hour scan, 19 subjects showed ICH growth and 52 were stable. In predicting growth based on the initial CT scan, the coefficient of variation and GLCM contrast had the highest sensitivities for discrimination. A combination of textural features provided a classification accuracy of 68% (sensitivity 65%, specificity 68%). Results for classifying “any growth” were comparable. Conclusions: Patterns noted in standard-of-care CT are indicative of an increased risk of hematoma expansion. Imaging biomarkers based on texture analysis can be used to classify patients and may aid in understanding mechanisms of ICH enlargement and acute treatment selection.

Abstract WMP94: Perihematomal Edema and Functional Outcomes in Intracerebral Hemorrhage: Influence of Hematoma Volume and Location

Background and Purpose: Perihematomal edema is associated with poor outcomes following intracerebral hemorrhage (ICH). Perihematomal edema evolves in the early period after ICH, providing a therapeutic target and window for intervention. We studied the effect of perihematomal edema volume expansion in the first 72 hours (iPHE) and its relationship with functional outcomes. Methods: We used data contained in the Virtual International Stroke Trials Archive. We included patients who presented within six-hours of symptom onset, had baseline clinical, radiological and laboratory data, and further computed tomographic scan data at 72 hours and 90-day functional outcomes. We calculated iPHE and used logistic regression analysis to assess relationships with outcome. We adjusted for confounding variables and the primary outcome measure poor day-90 outcome (defined as modified Rankin Scale score of ≥ 3. We performed subgroup analyses by location and volume of ICH. Results: We included 596 patients with ICH. Median baseline hematoma volume was 15.0 mL (IQR: 7.9- 29.2) and median baseline perihematomal edema volume of 8.7 mL (IQR: 4.5- 15.5). Hematoma expansion occured in 122 (34.9%) patients. Median iPHE was 14.7 mL (IQR: 6.6-30.3). The odds of a poor outcome were greater with increasing iPHE (OR: 1.78, CI: 1.12- 2.64 per mL increase). Subgroup analyses showed iPHE was only related to poor functional outcomes in basal ganglia and small (&lt;30 mL) ICH. Conclusion: Absolute increase in PHE over 72 hours was associated with worse functional outcomes following ICH, particularly with basal ganglia ICH and hematomas &lt;30 mL.

Stroke Severity and Comorbidity Index for Prediction of Mortality after Ischemic Stroke from the Virtual International Stroke Trials Archive–Acute Collaboration

There is increasing interest in the use of administrative data (incorporating comorbidity index) and stroke severity score to predict ischemic stroke mortality. The aim of this study was to determine the optimal timing for the collection of stroke severity data and the minimum clinical dataset to be included in models of stroke mortality. To address these issues, we chose the Virtual International Stroke Trials Archive (VISTA), which contains National Institutes of Health Stroke Scale (NIHSS) on admission and at 24 hours, as well as outcome at 90 days. VISTA was searched for patients who had baseline and 24-hour NIHSS. Improvement in regression models was performed by the net reclassification improvement (NRI) method. The clinical data among 5206 patients were mean age, 69 ± 13; comorbidity index, 3.3 ± .9; median NIHSS at baseline, 12 (interquartile range [IQR] 8-17); NIHSS at 24 hours, 9 (IQR 8-15); and death at 90 days in 15%. The baseline model consists of age, gender, and comorbidity index. Adding the baseline NIHSS to model 1 improved the NRI by 0.671 (95% confidence interval [CI] 0.595-0.747) [or 67.1% correct reclassification between model 1 and model 2]. Adding the 24 hour NIHSS term to model 1 (model 3) improved the NRI by 0.929 (95% CI 0.857-1.000) for model 3 versus model 1. Adding the variable thrombolysis to model 3 (model 4) improve NRI by 0.1 (95% CI 0.023-0.178) [model 4 versus model 3]. The optimal model for the prediction of mortality was achieved by adding the 24-hour NIHSS and thrombolysis to the baseline model.

Lacunar Infarcts, Depression, and Anxiety Symptoms One Year after Stroke

Mood disorders are frequent after stroke and are associated with poorer quality of life. Previous studies have reported conflicting results as to stroke subtype in the incidence of poststroke mood disorders. We explored the relationship between subcortical ischemic stroke subtype (lacunar) and presence of such symptoms at 1 year after stroke. Anonymized data were accessed from the Virtual International Stroke Trials Archive. Stroke subtypes were classified according to the Trial of Org 10172 in Acute Stroke Treatment classification. Depression and anxiety symptoms were assessed using Hospital Anxiety and Depression Scale. We investigated independent predictors of depression and anxiety symptoms using a logistic regression model. Data were available for 2160 patients. Almost one fifth of the patients developed both anxiety and depression at 1-year follow-up. After adjusting for confounders, the lacunar subtype was least associated with both anxiety (odds ratio [OR] = .61; 95% confidence interval [CI] = .46-.80) and depression symptoms (OR = .71; CI = .55-.93) versus other stroke subtypes. Lacunar strokes have a weaker association with presence of anxiety and depression symptoms compared with other subtypes.

Online Tool to Improve Stratification of Adverse Events in Stroke Clinical Trials.

Knowing characteristic adverse events (AEs) and their incidence among patients participating in acute stroke trials may assist interpretation of future studies. We aimed to develop an online tool to inform stroke trial safety. We identified relevant AEs from patients within the Virtual International Stroke Trials Archive (VISTA), using receiver operating characteristic principles. We modeled their incidence on patient age, baseline National Institutes of Health Stroke Scale, and comorbidities using binary logistic regression. Models with an R(2) >5% were deemed powerful enough to predict expected AE incidences and were included. The calculator was developed using programs R and Visual Studios. Forty-eight of the most common AEs were identified and incorporated into the IschAEmic Stroke Calculator. The calculator, publicly available at http://www.vistacollaboration.org calculates the expected incidence of AEs or groups of AEs in a trial cohort and where possible compares them with the observed incidence. The IschAEmic Stroke Calculator is an open access resource to support safety interpretation within acute stroke trials. Prediction of AEs with higher likelihood of occurrence may direct preventive clinical measures.

Development of a decision analytic model to support decision making and risk communication about thrombolytic treatment.

BackgroundIndividualised prediction of outcomes can support clinical and shared decision making. This paper describes the building of such a model to predict outcomes with and without intravenous thrombolysis treatment following ischaemic stroke.MethodsA decision analytic model (DAM) was constructed to establish the likely balance of benefits and risks of treating acute ischaemic stroke with thrombolysis. Probability of independence, (modified Rankin score mRS ≤ 2), dependence (mRS 3 to 5) and death at three months post-stroke was based on a calibrated version of the Stroke-Thrombolytic Predictive Instrument using data from routinely treated stroke patients in the Safe Implementation of Treatments in Stroke (SITS-UK) registry. Predictions in untreated patients were validated using data from the Virtual International Stroke Trials Archive (VISTA). The probability of symptomatic intracerebral haemorrhage in treated patients was incorporated using a scoring model from Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) data.ResultsThe model predicts probabilities of haemorrhage, death, independence and dependence at 3-months, with and without thrombolysis, as a function of 13 patient characteristics. Calibration (and inclusion of additional predictors) of the Stroke-Thrombolytic Predictive Instrument (S-TPI) addressed issues of under and over prediction. Validation with VISTA data confirmed that assumptions about treatment effect were just. The C-statistics for independence and death in treated patients in the DAM were 0.793 and 0.771 respectively, and 0.776 for independence in untreated patients from VISTA.ConclusionsWe have produced a DAM that provides an estimation of the likely benefits and risks of thrombolysis for individual patients, which has subsequently been embedded in a computerised decision aid to support better decision-making and informed consent.

Perihematomal Edema and Functional Outcomes in Intracerebral Hemorrhage: Influence of Hematoma Volume and Location.

Perihematomal edema (PHE) is associated with poor outcomes after intracerebral hemorrhage (ICH). PHE evolves in the early period after ICH, providing a therapeutic target and window for intervention. We studied the effect of PHE volume expansion in the first 72 hours (iPHE) and its relationship with functional outcomes. We used data contained in the Virtual International Stroke Trials Archive. We included patients who presented within 6 hours of symptom onset, had baseline clinical, radiological, and laboratory data, and further computed tomographic scan data at 72 hours and 90-day functional outcomes. We calculated iPHE and used logistic regression analysis to assess relationships with outcome. We adjusted for confounding variables and the primary outcome measure poor day-90 outcome (defined as modified Rankin Scale score of ≥3. We performed subgroup analyses by location and by volume of ICH. We included 596 patients with ICH. Median baseline hematoma volume was 15.0 mL (IQR, 7.9-29.2) and median baseline PHE volume was 8.7 mL (IQR, 4.5-15.5). Hematoma expansion occurred in 122 (34.9%) patients. Median iPHE was 14.7 mL (IQR, 6.6-30.3). The odds of a poor outcome were greater with increasing iPHE (OR, 1.78; CI, 1.12-2.64 per mL increase). Subgroup analyses showed that iPHE was only related to poor functional outcomes in basal ganglia and small (<30 mL) ICH. Absolute increase in PHE during 72 hours was associated with worse functional outcomes after ICH, particularly with basal ganglia ICH and hematomas <30 mL.

Improved ischemic stroke outcome prediction using model estimation of outcome probability: the THRIVE-c calculation.

The Totaled Health Risks in Vascular Events (THRIVE) score is a previously validated ischemic stroke outcome prediction tool. Although simplified scoring systems like the THRIVE score facilitate ease-of-use, when computers or devices are available at the point of care, a more accurate and patient-specific estimation of outcome probability should be possible by computing the logistic equation with patient-specific continuous variables. We used data from 12 207 subjects from the Virtual International Stroke Trials Archive and the Safe Implementation of Thrombolysis in Stroke - Monitoring Study to develop and validate the performance of a model-derived estimation of outcome probability, the THRIVE-c calculation. Models were built with logistic regression using the underlying predictors from the THRIVE score: age, National Institutes of Health Stroke Scale score, and the Chronic Disease Scale (presence of hypertension, diabetes mellitus, or atrial fibrillation). Receiver operator characteristics analysis was used to assess model performance and compare the THRIVE-c model to the traditional THRIVE score, using a two-tailed Chi-squared test. The THRIVE-c model performed similarly in the randomly chosen development cohort (n = 6194, area under the curve = 0·786, 95% confidence interval 0·774-0·798) and validation cohort (n = 6013, area under the curve = 0·784, 95% confidence interval 0·772-0·796) (P = 0·79). Similar performance was also seen in two separate external validation cohorts. The THRIVE-c model (area under the curve = 0·785, 95% confidence interval 0·777-0·793) had superior performance when compared with the traditional THRIVE score (area under the curve = 0·746, 95% confidence interval 0·737-0·755) (P < 0·001). By computing the logistic equation with patient-specific continuous variables in the THRIVE-c calculation, outcomes at the individual patient level are more accurately estimated. Given the widespread availability of computers and devices at the point of care, such calculations can be easily performed with a simple user interface.

Googling Stroke ASPECTS to Determine Disability: Exploratory Analysis from VISTA-Acute Collaboration.

The summed Alberta Stroke Program Early CT Score (ASPECTS) is useful for predicting stroke outcome. The anatomical information in the CT template is rarely used for this purpose because traditional regression methods are not adept at handling collinearity (relatedness) among brain regions. While penalized logistic regression (PLR) can handle collinearity, it does not provide an intuitive understanding of the interaction among network structures in a way that eigenvector method such as PageRank can (used in Google search engine). In this exploratory analysis we applied graph theoretical analysis to explore the relationship among ASPECTS regions with respect to disability outcome. The Virtual International Stroke Trials Archive (VISTA) was searched for patients who had infarct in at least one ASPECTS region (ASPECTS ≤9, ASPECTS=10 were excluded), and disability (modified Rankin score/mRS). A directed graph was created from a cross correlation matrix (thresholded at false discovery rate of 0.01) of the ASPECTS regions and demographic variables and disability (mRS>2). We estimated the network-based importance of each ASPECTS region by comparing PageRank and node strength measures. These results were compared with those from PLR. There were 185 subjects, average age 67.5± 12.8 years (55% Males). Model 1: demographic variables having no direct connection with disability, the highest PageRank was M2 (0.225, bootstrap 95% CI 0.215-0.347). Model 2: demographic variables having direct connection with disability, the highest PageRank were M2 (0.205, bootstrap 95% CI 0.194-0.367) and M5 (0.125, bootstrap 95% CI 0.096-0.204). Both models illustrate the importance of M2 region to disability. The PageRank method reveals complex interaction among ASPECTS regions with respects to disability. This approach may help to understand the infarcted brain network involved in stroke disability.

β-Blockers, Pneumonia, and Outcome After Ischemic Stroke

Increased sympathetic drive after stroke is involved in the pathophysiology of several complications including poststroke immunudepression. β-Blocker (BB) therapy has been suggested to have neuroprotective properties and to decrease infectious complications after stroke. We aimed to examine the effects of random pre- and on-stroke BB exposure on mortality, functional outcome, and occurrence of pneumonia after ischemic stroke. Data including standard demographic and clinical variables as well as prestroke and on-stroke antihypertensive medication, incidence of pneumonia, functional outcome defined using modified Rankin Scale and mortality at 3 months were extracted from the Virtual International Stroke Trials Archive. For statistical analysis multivariable Poisson regression was used. In total, 5212 patients were analyzed. A total of 1155 (22.2%) patients were treated with BB before stroke onset and 244 (4.7%) patients were newly started with BB in the acute phase of stroke. Mortality was 17.5%, favorable outcome (defined as modified Rankin Scale, 0-2) occurred in 58.2% and pneumonia in 8.2% of patients. Prestroke BB showed no association with mortality. On-stroke BB was associated with reduced mortality (adjusted risk ratio, 0.63; 95% confidence interval, 0.42-0.96). Neither prestroke BB nor on-stroke BB showed an association with functional outcome. Both prestroke and on-stroke BB were associated with reduced frequency of pneumonia (adjusted risk ratio, 0.77; 95% confidence interval, 0.6-0.98 and risk ratio, 0.49; 95% confidence interval, 0.25-0.95). In this large nonrandomized comparison, on-stroke BB was associated with reduced mortality. Prestroke and on-stroke BB were inversely associated with incidence of nosocomial pneumonia. Randomized trials investigating the potential of β-blockade in acute stroke may be warranted.

International survey of acute stroke imaging used to make revascularization treatment decisions.

To assess the differences across continental regions in terms of stroke imaging obtained for making acute revascularization therapy decisions, and to identify obstacles to participating in randomized trials involving multimodal imaging. STroke Imaging Repository (STIR) and Virtual International Stroke Trials Archive (VISTA)-Imaging circulated an online survey through its website, through the websites of national professional societies from multiple countries as well as through email distribution lists from STIR and the above mentioned societies. We received responses from 223 centers (2 from Africa, 38 from Asia, 10 from Australia, 101 from Europe, 4 from Middle East, 55 from North America, 13 from South America). In combination, the sites surveyed administered acute revascularization therapy to a total of 25,326 acute stroke patients in 2012. Seventy-three percent of these patients received intravenous (i.v.) tissue plasminogen activator (tPA), and 27%, endovascular therapy. Vascular imaging was routinely obtained in 79% (152/193) of sites for endovascular therapy decisions, and also as part of standard IV tPA treatment decisions at 46% (92/198) of sites. Modality, availability and use of acute vascular and perfusion imaging before revascularization varied substantially between geographical areas. The main obstacles to participate in randomized trials involving multimodal imaging included: mainly insufficient research support and staff (50%, 79/158) and infrequent use of multimodal imaging (27%, 43/158) . There were significant variations among sites and geographical areas in terms of stroke imaging work-up used tomake decisions both for intravenous and endovascular revascularization. Clinical trials using advanced imaging as a selection tool for acute revascularization therapy should address the need for additional resources and technical support, and take into consideration the lack of routine use of such techniques in trial planning.

Abstract 13: Improved Ischemic Stroke Outcome Prediction Using Model Estimation Of Outcome Probability: The THRIVE-c Calculator

Introduction: The THRIVE score is a validated ischemic stroke outcome prediction tool. While simplified systems like the THRIVE score facilitate ease-of-use, when computers or devices are available at the point of care, a more accurate estimation of outcome probability is possible by computing the logistic equation with patient-specific continuous variables. Methods: We used data from 12,207 subjects from the Virtual International Stroke Trials Archive (VISTA) and the Safe Implementation of Thrombolysis in Stroke - Monitoring Study (SITS-MOST) study to develop and validate the performance of a model-derived estimation of outcome probability, the THRIVE-c calculation. Models were built with logistic regression using the underlying predictors from the THRIVE score: age, NIH Stroke Scale (NIHSS) score, and the Chronic Disease Scale (presence of hypertension, diabetes mellitus, or atrial fibrillation). Receiver-Operator Characteristics (ROC) analysis was used to assess model performance and compare the THRIVE-c model to the traditional THRIVE score. Results: The THRIVE-c model performed similarly in the randomly chosen development cohort (n=6194, AUC = 0.786, 95% CI 0.774-0.798) and validation cohort (n=6013, AUC = 0.784, 95% CI 0.772-0.796) (P=0.79). The THRIVE-c model (AUC = 0.785, 95% CI 0.777-0.793) had superior performance when compared to the traditional THRIVE score (AUC = 0.746, 95% CI 0.737-0.755), (P&lt;0.0001). Conclusion: By computing the logistic equation with patient-specific continuous variables in the THRIVE-c calculation, patient outcomes are more accurately estimated. Given the widespread availability of the computers and devices at the point of care, such calculations can be easily performed with a simple user interface. A web calculator for THRIVE-c is available at www.thrivescore.org.