There is an increased attention to stroke following SARS-CoV-2. The goal of this study was to better depict the short-term risk of stroke and its associated factors among SARS-CoV-2 hospitalized patients. This multicentre, multinational observational study includes hospitalized SARS-CoV-2 patients from North and South America (United States, Canada, and Brazil), Europe (Greece, Italy, Finland, and Turkey), Asia (Lebanon, Iran, and India), and Oceania (New Zealand). The outcome was the risk of subsequent stroke. Centres were included by non-probability sampling. The counts and clinical characteristics including laboratory findings and imaging of the patients with and without a subsequent stroke were recorded according to a predefined protocol. Quality, risk of bias, and heterogeneity assessments were conducted according to ROBINS-E and Cochrane Q-test. The risk of subsequent stroke was estimated through meta-analyses with random effect models. Bivariate logistic regression was used to determine the parameters with predictive outcome value. The study was reported according to the STROBE, MOOSE, and EQUATOR guidelines. We received data from 26,175 hospitalized SARS-CoV-2 patients from 99 tertiary centres in 65 regions of 11 countries until May 1st, 2020. A total of 17,799 patients were included in meta-analyses. Among them, 156(0.9%) patients had a stroke—123(79%) ischaemic stroke, 27(17%) intracerebral/subarachnoid hemorrhage, and 6(4%) cerebral sinus thrombosis. Subsequent stroke risks calculated with meta-analyses, under low to moderate heterogeneity, were 0.5% among all centres in all countries, and 0.7% among countries with higher health expenditures. The need for mechanical ventilation (OR: 1.9, 95% CI:1.1–3.5, p = 0.03) and the presence of ischaemic heart disease (OR: 2.5, 95% CI:1.4–4.7, p = 0.006) were predictive of stroke. The results of this multi-national study on hospitalized patients with SARS-CoV-2 infection indicated an overall stroke risk of 0.5%(pooled risk: 0.9%). The need for mechanical ventilation and the history of ischaemic heart disease are the independent predictors of stroke among SARS-CoV-2 patients. None.

Background: The long-term risk of recurrent ischemic stroke, estimated to be between 17% and 30%, cannot be reliably assessed at an individual level. Our goal was to study whether machine-learning can be trained to predict stroke recurrence and identify key clinical variables and assess whether performance metrics can be optimized. Methods: We used patient-level data from electronic health records, six interpretable algorithms (Logistic Regression, Extreme Gradient Boosting, Gradient Boosting Machine, Random Forest, Support Vector Machine, Decision Tree), four feature selection strategies, five prediction windows, and two sampling strategies to develop 288 models for up to 5-year stroke recurrence prediction. We further identified important clinical features and different optimization strategies. Results: We included 2091 ischemic stroke patients. Model area under the receiver operating characteristic (AUROC) curve was stable for prediction windows of 1, 2, 3, 4, and 5 years, with the highest score for the 1-year (0.79) and the lowest score for the 5-year prediction window (0.69). A total of 21 (7%) models reached an AUROC above 0.73 while 110 (38%) models reached an AUROC greater than 0.7. Among the 53 features analyzed, age, body mass index, and laboratory-based features (such as high-density lipoprotein, hemoglobin A1c, and creatinine) had the highest overall importance scores. The balance between specificity and sensitivity improved through sampling strategies. Conclusion: All of the selected six algorithms could be trained to predict the long-term stroke recurrence and laboratory-based variables were highly associated with stroke recurrence. The latter could be targeted for personalized interventions. Model performance metrics could be optimized, and models can be implemented in the same healthcare system as intelligent decision support for targeted intervention.

Background and Purpose: Stroke is reported as a consequence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in several reports. However, data are sparse regarding the details of these patients in a multinational and large scale. Methods: We conducted a multinational observational study on features of consecutive acute ischemic stroke, intracranial hemorrhage, and cerebral venous or sinus thrombosis among SARS-CoV-2–infected patients. We further investigated the risk of large vessel occlusion, stroke severity as measured by the National Institutes of Health Stroke Scale, and stroke subtype as measured by the TOAST (Trial of ORG 10172 in Acute Stroke Treatment) criteria among patients with acute ischemic stroke. In addition, we explored the neuroimaging findings, features of patients who were asymptomatic for SARS-CoV-2 infection at stroke onset, and the impact of geographic regions and countries’ health expenditure on outcomes. Results: Among the 136 tertiary centers of 32 countries who participated in this study, 71 centers from 17 countries had at least 1 eligible stroke patient. Of 432 patients included, 323 (74.8%) had acute ischemic stroke, 91 (21.1%) intracranial hemorrhage, and 18 (4.2%) cerebral venous or sinus thrombosis. A total of 183 (42.4%) patients were women, 104 (24.1%) patients were <55 years of age, and 105 (24.4%) patients had no identifiable vascular risk factors. Among acute ischemic stroke patients, 44.5% (126 of 283 patients) had large vessel occlusion; 10% had small artery occlusion according to the TOAST criteria. We observed a lower median National Institutes of Health Stroke Scale (8 [3–17] versus 11 [5–17]; P =0.02) and higher rate of mechanical thrombectomy (12.4% versus 2%; P <0.001) in countries with middle-to-high health expenditure when compared with countries with lower health expenditure. Among 380 patients who had known interval onset of the SARS-CoV-2 and stroke, 144 (37.8%) were asymptomatic at the time of admission for SARS-CoV-2 infection. Conclusions: We observed a considerably higher rate of large vessel occlusions, a much lower rate of small vessel occlusion and lacunar infarction, and a considerable number of young stroke when compared with the population studies before the pandemic. The rate of mechanical thrombectomy was significantly lower in countries with lower health expenditures.

Traumatic brain injury (TBI) is a major health concern. The purpose of this study is to identify the diagnostic accuracy of ubiquitin C-terminal hydrolase-L1 (UCH-L1)—a protein biomarker—in comparison with CT-scan findings post-TBI. Accordingly, we conducted a systematic review of eligible studies and assessed the risk of bias according to the QUADAS-2 checklist. A total of 13 reports from 10 original studies were included. Based on our analysis, serum UCH-L1 has a high accuracy in predicting CT findings in mild to moderate TBI. Based on the QUADAS-2 checklist, this result has a high risk of bias affecting its applicability. The plasma level of UCH-L1 has moderate accuracy in predicting CT findings when assessed in all GCS levels. This result has a low risk of bias and low concerns regarding applicability. Pooled analysis suggests that the plasma/serum UCH-L1 level has high accuracy in predicting CT findings in a wide range of GCS in patients with TBI. This result has a high risk of bias and high concern about its applicability. The heterogeneity in approaching TBI biomarker interferes with drawing a definitive conclusion. Therefore, although UCH-L1 is a promising blood-based diagnostic biomarker for TBI, but due to differences in reported diagnostic accuracy, further studies are needed to recommend UCH-L1 as an alternative to CT scanning.

Background and Purpose: We systematically evaluated the impact of the coronavirus 2019 (COVID-19) pandemic on stroke care across the world. Methods: Observational studies comparing characteristics, acute treatment delivery, or hospitalization outcomes between patients with stroke admitted during the COVID-19 pandemic and those admitted before the pandemic were identified by Medline, Scopus, and Embase databases search. Random-effects meta-analyses were conducted for all outcomes. Results: We identified 46 studies including 129 491 patients. Patients admitted with stroke during the COVID-19 pandemic were found to be younger (mean difference, −1.19 [95% CI, −2.05 to −0.32]; I ² =70%) and more frequently male (odds ratio, 1.11 [95% CI, 1.01–1.22]; I ² =54%) compared with patients admitted with stroke in the prepandemic era. Patients admitted with stroke during the COVID-19 pandemic, also, had higher baseline National Institutes of Health Stroke Scale scores (mean difference, 0.55 [95% CI, 0.12–0.98]; I ² =90%), higher probability for large vessel occlusion presence (odds ratio, 1.63 [95% CI, 1.07–2.48]; I ² =49%) and higher risk for in-hospital mortality (odds ratio, 1.26 [95% CI, 1.05–1.52]; I ² =55%). Patients with acute ischemic stroke admitted during the COVID-19 pandemic had higher probability of receiving endovascular thrombectomy treatment (odds ratio, 1.24 [95% CI, 1.05–1.47]; I ² =40%). No difference in the rates of intravenous thrombolysis administration or difference in time metrics regarding onset to treatment time for intravenous thrombolysis and onset to groin puncture time for endovascular thrombectomy were detected. Conclusions: The present systematic review and meta-analysis indicates an increased prevalence of younger patients, more severe strokes attributed to large vessel occlusion, and higher endovascular treatment rates during the COVID-19 pandemic. Patients admitted with stroke during the COVID-19 pandemic had higher in-hospital mortality. These findings need to be interpreted with caution in view of discrepant reports and heterogeneity being present across studies.