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BACKGROUND: Inter-observer variability in stroke aetiological classification may have an effect on trial power and estimation of treatment effect. We modelled the effect of misclassification on required sample size in a hypothetical cardioembolic (CE) stroke trial. METHODS: We performed a systematic review to quantify the reliability (inter-observer variability) of various stroke aetiological classification systems. We then modelled the effect of this misclassification in a hypothetical trial of anticoagulant in CE stroke contaminated by patients with non-cardioembolic (non-CE) stroke aetiology. Rates of misclassification were based on the summary reliability estimates from our systematic review. We randomly sampled data from previous acute trials in CE and non-CE participants, using the Virtual International Stroke Trials Archive. We used bootstrapping to model the effect of varying misclassification rates on sample size required to detect a between-group treatment effect across 5000 permutations. We described outcomes in terms of survival and stroke recurrence censored at 90 days. RESULTS: From 4655 titles, we found 14 articles describing three stroke classification systems. The inter-observer reliability of the classification systems varied from 'fair' to 'very good' and suggested misclassification rates of 5% and 20% for our modelling. The hypothetical trial, with 80% power and alpha 0.05, was able to show a difference in survival between anticoagulant and antiplatelet in CE with a sample size of 198 in both trial arms. Contamination of both arms with 5% misclassified participants inflated the required sample size to 237 and with 20% misclassification inflated the required sample size to 352, for equivalent trial power. For an outcome of stroke recurrence using the same data, base-case estimated sample size for 80% power and alpha 0.05 was n = 502 in each arm, increasing to 605 at 5% contamination and 973 at 20% contamination. CONCLUSIONS: Stroke aetiological cl

Background and aim: The availability and access of hospital administrative data [coding for Charlson comorbidity index (CCI)] in large data form has resulted in a surge of interest in using this information to predict mortality from stroke. The aims of this study were to determine the minimum clinical data set to be included in models for predicting disability after ischemic stroke adjusting for CCI and clinical variables and to evaluate the impact of CCI on prediction of outcome. Method(s): We leverage anonymized clinical trial data in the Virtual International Stroke Trials Archive. This repository contains prospective data on stroke severity and outcome. The inclusion criteria were patients with available stroke severity score such as National Institutes of Health Stroke Scale (NIHSS), imaging data, and outcome disability score such as 90-day Rankin Scale. We calculate CCI based on comorbidity data in this data set. For logistic regression, we used these calibration statistics: Nagelkerke generalised R2 and Brier score; and for discrimination we used: area under the receiver operating characteristics curve (AUC) and integrated discrimination improvement (IDI). The IDI was used to evaluate improvement in disability prediction above baseline model containing age, sex, and CCI. Result(s): The clinical data among 5,206 patients (55% males) were as follows: mean age 69 +/- 13 years, CCI 4.2 +/- 0.8, and median NIHSS of 12 (IQR 8, 17) on admission and 9 (IQR 5, 15) at 24 h. In Model 2, adding admission NIHSS to the baseline model improved AUC from 0.67 (95% CI 0.65-0.68) to 0.79 (95% CI 0.78-0.81). In Model 3, adding 24-h NIHSS to the baseline model resulted in substantial improvement in AUC to 0.90 (95% CI 0.89-0.91) and increased IDI by 0.23 (95% CI 0.22-0.24). Adding the variable recombinant tissue plasminogen activator did not result in a further change in AUC or IDI to this regression model. In Model 3, the variable NIHSS at 24 h explains 87.3% of the variance of

Background and aim: The availability and access of hospital administrative data [coding for Charlson comorbidity index (CCI)] in large data form has resulted in a surge of interest in using this information to predict mortality from stroke. The aims of this study were to determine the minimum clinical data set to be included in models for predicting disability after ischemic stroke adjusting for CCI and clinical variables and to evaluate the impact of CCI on prediction of outcome. Method(s): We leverage anonymized clinical trial data in the Virtual International Stroke Trials Archive. This repository contains prospective data on stroke severity and outcome. The inclusion criteria were patients with available stroke severity score such as National Institutes of Health Stroke Scale (NIHSS), imaging data, and outcome disability score such as 90-day Rankin Scale. We calculate CCI based on comorbidity data in this data set. For logistic regression, we used these calibration statistics: Nagelkerke generalised R2 and Brier score; and for discrimination we used: area under the receiver operating characteristics curve (AUC) and integrated discrimination improvement (IDI). The IDI was used to evaluate improvement in disability prediction above baseline model containing age, sex, and CCI. Result(s): The clinical data among 5,206 patients (55% males) were as follows: mean age 69 +/- 13 years, CCI 4.2 +/- 0.8, and median NIHSS of 12 (IQR 8, 17) on admission and 9 (IQR 5, 15) at 24 h. In Model 2, adding admission NIHSS to the baseline model improved AUC from 0.67 (95% CI 0.65-0.68) to 0.79 (95% CI 0.78-0.81). In Model 3, adding 24-h NIHSS to the baseline model resulted in substantial improvement in AUC to 0.90 (95% CI 0.89-0.91) and increased IDI by 0.23 (95% CI 0.22-0.24). Adding the variable recombinant tissue plasminogen activator did not result in a further change in AUC or IDI to this regression model. In Model 3, the variable NIHSS at 24 h explains 87.3% of the variance of

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.Copyright © 2015 Beare et al.

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.Copyright © 2015 Beare et al. This is an open access article distributed under the terms of the Cr

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.Copyright © 2015 Beare et al.

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.Copyright © 2015 Beare et al. This is an open access article distributed under the terms of the Cr

The aim of the ICARO-3 study was to evaluate whether intra-arterial treatment, compared to intravenous thrombolysis, increases the rate of favourable functional outcome at 3 months in acute ischemic stroke and extracranial ICA occlusion. ICARO-3 was a non-randomized therapeutic trial that performed a non-blind assessment of outcomes using retrospective data collected prospectively from 37 centres in 7 countries. Patients treated with endovascular treatment within 6 h from stroke onset (cases) were matched with patients treated with intravenous thrombolysis within 4.5 h from symptom onset (controls). Patients receiving either intravenous or endovascular therapy were included among the cases. The efficacy outcome was disability at 90 days assessed by the modified Rankin Scale (mRS), dichotomized as favourable (score of 0–2) or unfavourable (score of 3–6). Safety outcomes were death and any intracranial bleeding. Included in the analysis were 324 cases and 324 controls: 105 cases (32.4 %) had a favourable outcome as compared with 89 controls (27.4 %) [adjusted odds ratio (OR) 1.25, 95 % confidence interval (CI) 0.88–1.79, p = 0.1]. In the adjusted analysis, treatment with intra-arterial procedures was significantly associated with a reduction of mortality (OR 0.61, 95 % CI 0.40–0.93, p = 0.022). The rates of patients with severe disability or death (mRS 5–6) were similar in cases and controls (30.5 versus 32.4 %, p = 0.67). For the ordinal analysis, adjusted for age, sex, NIHSS, presence of diabetes mellitus and atrial fibrillation, the common odds ratio was 1.15 (95 % IC 0.86–1.54), p = 0.33. There were more cases of intracranial bleeding (37.0 versus 17.3 %, p = 0.0001) in the intra-arterial procedure group than in the intravenous group. After the exclusion of the 135 cases treated with the combination of I.V. thrombolysis and I.A. procedures, 67/189 of those trea

RATIONALE: Thrombolysis with intravenous alteplase is both effective and safe when administered to particular types of patient within 4·5 hours of having an ischemic stroke. However, the extent to which effects might vary in different types of patient is uncertain. AIMS AND DESIGN: We describe the protocol for an updated individual patient data meta-analysis of trials of intravenous alteplase, including results from the recently reported third International Stroke Trial, in which a wide range of patients enrolled up to six-hours after stroke onset were randomized to alteplase vs. control. STUDY OUTCOMES: This protocol will specify the primary outcome for efficacy, specified prior to knowledge of the results from the third International Stroke Trial, as the proportion of patients having a 'favorable' stroke outcome, defined by modified Rankin Score 0-1 at final follow-up at three- to six-months. The primary analysis will be to estimate the extent to which the known benefit of alteplase on modified Rankin Score 0-1 diminishes with treatment delay, and the extent to which it is independently modified by age and stroke severity. Key secondary outcomes include effect of alteplase on death within 90 days; analyses of modified Rankin Score using ordinal, rather than dichotomous, methods; and effects of alteplase on symptomatic intracranial hemorrhage, fatal intracranial hemorrhage, symptomatic ischemic brain edema and early edema, effacement and/or midline shift. DISCUSSION: This collaborative meta-analysis of individual participant data from all randomized trials of intravenous alteplase vs. control will demonstrate how the known benefits of alteplase on ischemic stroke outcome vary across different types of patient.

Background and Purpose-: The beneficial effect of intravenous thrombolytic therapy in patients with acute ischemic stroke attributable to internal carotid artery (ICA) occlusion remains unclear. The aim of this study was to evaluate the efficacy and safety of intravenous recombinant tissue-type plasminogen activator in these patients. Methods-: ICARO was a case-control multicenter study on prospectively collected data. Patients with acute ischemic stroke and ICA occlusion treated with intravenous recombinant tissue-type plasminogen activator within 4.5 hours from symptom onset (cases) were compared to matched patients with acute stroke and ICA occlusion not treated with recombinant tissue-type plasminogen activator (controls). Cases and controls were matched for age, gender, and stroke severity. The efficacy outcome was disability at 90 days assessed by the modified Rankin Scale, dichotomized as favorable (score of 0-2) or unfavorable (score of 3-6). Safety outcomes were death and any intracranial bleeding. Results-: Included in the analysis were 253 cases and 253 controls. Seventy-three cases (28.9%) had a favorable outcome as compared with 52 controls (20.6%; adjusted odds ratio (OR), 1.80; 95% confidence interval [CI], 1.03-3.15; P=0.037). A total of 104 patients died, 65 cases (25.7%) and 39 controls (15.4%; adjusted OR, 2.28; 95% CI, 1.36-3.22; P=0.001). There were more fatal bleedings (2.8% versus 0.4%; OR, 7.17; 95% CI, 0.87-58.71; P=0.068) in the cases than in the controls. Conclusions-: In patients with stroke attributable to ICA occlusion, thrombolytic therapy Results in a significant reduction in the proportion of patients dependent in activities of daily living. Increases in death and any intracranial bleeding were the trade-offs for this clinical benefit.

BACKGROUND AND PURPOSE: "Home time" (HT) refers to the number of days over the first 90 after stroke onset that a patient spends residing in their own home or a relative's home versus any institutional care. It is an accessible and objective parameter, free from subjective bias, with potential as an outcome measure in acute stroke trials. We sought to validate HT and assess treatment responsiveness using independent data. METHODS: We estimated HT in the Stroke Acute Ischemic NXY Treatment (SAINT) I neuroprotection trial. We compared outcomes between thrombolyzed (T) and nonthrombolyzed comparators (C) using HT and the modified Rankin Scale. For our primary analysis, we adjusted for baseline covariates that significantly influence HT and in sensitivity analyses considered all variables that differed between groups at baseline. We report ordinal logistic regression and analysis of covariance with 95% CIs. We describe the relationship of HT with baseline National Institutes of Health Stroke Scale and its components and with Day 90 modified Rankin Scale and Barthel Index. RESULTS: SAINT I included 1699 patients from 23 countries, of whom 28.7% received alteplase. HT correlated with age, baseline severity, alteplase use, side of ischemic lesion, presence of diabetes, and country of patient enrollment (each P<0.05). We found an association between use of alteplase with better adjusted outcomes by either measure (OR for extended HT, 1.36; 95% CI, 1.08 to 1.72; P=0.009; analysis of covariance P=0.007 with a 5.5-day advantage; OR for more favorable modified Rankin Scale, 1.6; 95% CI, 1.28 to 2.00; P<0.0001; Cochran-Mantel-Haenszel P=0.046). HT was significantly associated with baseline National Institutes of Health Stroke Scale and each component of the National Institutes of Health Stroke Scale except level of consciousness, dysarthria, and ataxia. HT was significantly associated with Day 90 modified Rankin Scale and Barthel Index. CONCLUSIONS: HT is a responsive measure fo

A design study has been conducted to establish an engineering specification for an integrated inspection system that will be used to implement the Retirement for Cause (RFC) maintenance philosophy on gas turbine engine disks and spacers. The system specified by this study emphasizes equipment reliability, flexibility, component throughput and accountability required for 1985 overhaul facility implementation through an Air Force manufacturing technology program. NDE technology needs for far term (post-1985) overhaul implementation of optimal RFC inspections are discussed in terms of necessary research programs which should be conducted in parallel to the manufacturing technology effort. Keywords: Retirement for Cause, Nondestructive Evaluation, F100 Engine, Engine Maintenance, Eddy Current, Ultrasonic Test, Fluorescent Penetrant Inspection, Automated Facility.

A design study has been conducted to establish an engineering specification for an integrated inspection system that will be used to implement the Retirement for Cause (RFC) maintenance philosophy on gas turbine engine disks and spacers. The system specified by this study emphasizes equipment reliability, flexibility, component throughput and accountability required for 1985 overhaul facility implementation through an Air Force manufacturing technology program. NDE technology needs for far term (post 1985) overhaul implementation of optimal RFC inspections are discussed in terms of necessary research programs which should be conducted in parallel to the manufacturing technology effort. Keywords: Gas turbine engine components; Defect discrimination; Air Force overhaul centers; Turbofan engines; Nondestructive evaluation; F100 engine; Engine maintenance; Eddy current; Ultrasonic test; Fluorescent pentetrant inspection; and Automated test facility., See also Volume 2, AD-A167 022.