BACKGROUND: Symptomatic intracranial hemorrhage (sICH) is a serious complication after endovascular treatment for ischemic stroke. We aimed to identify determinants of its occurrence and location... Show moreBACKGROUND: Symptomatic intracranial hemorrhage (sICH) is a serious complication after endovascular treatment for ischemic stroke. We aimed to identify determinants of its occurrence and location.METHODS: We retrospectively analyzed data from the Dutch MR CLEAN trial (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) and MR CLEAN registry. We included adult patients with a large vessel occlusion in the anterior circulation who underwent endovascular treatment within 6.5 hours of stroke onset. We used univariable and multivariable logistic regression analyses to identify determinants of overall sICH occurrence, sICH within infarcted brain tissue, and sICH outside infarcted brain tissue.RESULTS: SICH occurred in 203 (6%) of 3313 included patients and was located within infarcted brain tissue in 50 (25%), outside infarcted brain tissue in 23 (11%), and both within and outside infarcted brain tissue in 116 (57%) patients. In 14 patients (7%), data on location were missing. Prior antiplatelet use, baseline systolic blood pressure, baseline plasma glucose levels, post-endovascular treatment modified treatment in cerebral ischemia score, and duration of procedure were associated with all outcome parameters. In addition, determinants of sICH within infarcted brain tissue included history of myocardial infarction (adjusted odds ratio, 1.65 [95% CI, 1.06-2.56]) and poor collateral score (adjusted odds ratio, 1.42 [95% CI, 1.02-1.95]), whereas determinants of sICH outside infarcted brain tissue included level of occlusion on computed tomography angiography (internal carotid artery or internal carotid artery terminus compared with M1: adjusted odds ratio, 1.79 [95% CI 1.16-2.78]).CONCLUSIONS: Several factors, some potentially modifiable, are associated with sICH occurrence. Further studies should investigate whether modification of baseline systolic blood pressure or plasma glucose level could reduce the risk of sICH. In addition, determinants differ per location of sICH, supporting the hypothesis of varying underlying mechanisms.[GRAPHICS]. Show less
Steen, W. van der; Ende, N.A.M. van der; Kranendonk, K.R. van; Chalos, V.; Brouwer, J.; Oostenbrugge, R.J. van; ... ; MR Clean Registry Investigators 2022
Introduction: Little is known about the timing of occurrence of symptomatic intracranial hemorrhage (sICH) after endovascular therapy (EVT) for acute ischemic stroke. A better understanding could... Show moreIntroduction: Little is known about the timing of occurrence of symptomatic intracranial hemorrhage (sICH) after endovascular therapy (EVT) for acute ischemic stroke. A better understanding could optimize in-hospital surveillance time points and duration. The aim of this study was to delineate the probability of sICH over time and to identify factors associated with its timing. Patients and methods: We retrospectively analyzed data from the Dutch MR CLEAN trial and MR CLEAN Registry. We included adult patients who underwent EVT for an anterior circulation large vessel occlusion within 6.5 h of stroke onset. In patients with sICH (defined as ICH causing an increase of > 4 points on the National Institutes of Health Stroke Scale [NIHSS]), univariable and multivariable linear regression analysis was used to identify factors associated with the timing of sICH. This was defined as the time between end of EVT and the time of first CT-scan on which ICH was seen as a proxy. Results: SICH occurred in 205 (6%) of 3391 included patients. Median time from end of EVT procedure to sICH detection on NCCT was 9.0 [IQR 2.9-22.5] hours, with a rapidly decreasing incidence after 24 h. None of the analyzed factors, including baseline NIHSS, intravenous alteplase treatment, and poor reperfusion at the end of the procedure were associated with the timing of sICH. Conclusion: SICHs primarily occur in the first hours after EVT, and less frequently beyond 24 h. Guidelines that recommend to perform frequent neurological assessments for at least 24 h after intravenous alteplase treatment can be applied to ischemic stroke patients treated with EVT. Show less
Background The effects of thrombus imaging characteristics on procedural and clinical outcomes after ischemic stroke are increasingly being studied. These thrombus characteristics - for eg, size,... Show moreBackground The effects of thrombus imaging characteristics on procedural and clinical outcomes after ischemic stroke are increasingly being studied. These thrombus characteristics - for eg, size, location, and density - are commonly analyzed as separate entities. However, it is known that some of these thrombus characteristics are strongly related. Multicollinearity can lead to unreliable prediction models. We aimed to determine the distribution, correlation and clustering of thrombus imaging characteristics based on a large dataset of anterior-circulation acute ischemic stroke patients. Methods We measured thrombus imaging characteristics in the MR CLEAN Registry dataset, which included occlusion location, distance from the intracranial carotid artery to the thrombus (DT), thrombus length, density, perviousness, and clot burden score (CBS). We assessed intercorrelations with Spearman's coefficient (rho) and grouped thrombi based on 1) occlusion location and 2) thrombus length, density and perviousness using unsupervised clustering. Results We included 934 patients, of which 22% had an internal carotid artery (ICA) occlusion, 61% M1, 16% M2, and 1% another occlusion location. All thrombus characteristics were significantly correlated. Higher CBS was strongly correlated with longer DT (rho=0.67, p<0.01), and moderately correlated with shorter thrombus length (rho=-0.41, p<0.01). In more proximal occlusion locations, thrombi were significantly longer, denser, and less pervious. Unsupervised clustering analysis resulted in four thrombus groups; however, the cohesion within and distinction between the groups were weak. Conclusions Thrombus imaging characteristics are significantly intercorrelated - strong correlations should be considered in future predictive modeling studies. Clustering analysis showed there are no distinct thrombus archetypes - novel treatments should consider this thrombus variability. Show less
Despite the large overall beneficial effects of endovascular treatment in patients with acute ischemic stroke, severe disability or death still occurs in almost one-third of patients. These... Show moreDespite the large overall beneficial effects of endovascular treatment in patients with acute ischemic stroke, severe disability or death still occurs in almost one-third of patients. These patients, who might not benefit from treatment, have been previously identified with traditional logistic regression models, which may oversimplify relations between characteristics and outcome, or machine learning techniques, which may be difficult to interpret. We developed and evaluated a novel evolutionary algorithm for fuzzy decision trees to accurately identify patients with poor outcome after endovascular treatment, which was defined as having a modified Rankin Scale score (mRS) higher or equal to 5. The created decision trees have the benefit of being comprehensible, easily interpretable models, making its predictions easy to explain to patients and practitioners. Insights in the reason for the predicted outcome can encourage acceptance and adaptation in practice and help manage expectations after treatment. We compared our proposed method to CART, the benchmark decision tree algorithm, on classification accuracy and interpretability. The fuzzy decision tree significantly outperformed CART: using 5-fold cross-validation with on average 1090 patients in the training set and 273 patients in the test set, the fuzzy decision tree misclassified on average 77 (standard deviation of 7) patients compared to 83 (+/- 7) using CART. The mean number of nodes (decision and leaf nodes) in the fuzzy decision tree was 11 (+/- 2) compared to 26 (+/- 1) for CART decision trees. With an average accuracy of 72% and much fewer nodes than CART, the developed evolutionary algorithm for fuzzy decision trees might be used to gain insights into the predictive value of patient characteristics and can contribute to the development of more accurate medical outcome prediction methods with improved clarity for practitioners and patients. Show less
