Background and Objectives Declines in stroke admission, IV thrombolysis (IVT), and mechanical thrombectomy volumes were reported during the first wave of the COVID-19 pandemic. There is a paucity of data on the longer-term effect of the pandemic on stroke volumes over the course of a year and through the second wave of the pandemic. We sought to measure the effect of the COVID-19 pandemic on the volumes of stroke admissions, intracranial hemorrhage (ICH), IVT, and mechanical thrombectomy over a 1-year period at the onset of the pandemic (March 1, 2020, to February 28, 2021) compared with the immediately preceding year (March 1, 2019, to February 29, 2020). Methods We conducted a longitudinal retrospective study across 6 continents, 56 countries, and 275 stroke centers. We collected volume data for COVID-19 admissions and 4 stroke metrics: ischemic stroke admissions, ICH admissions, IVT treatments, and mechanical thrombectomy procedures. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases. Results There were 148,895 stroke admissions in the 1 year immediately before compared with 138,453 admissions during the 1-year pandemic, representing a 7% decline (95% CI [95% CI 7.1–6.9]; p < 0.0001). ICH volumes declined from 29,585 to 28,156 (4.8% [5.1–4.6]; p < 0.0001) and IVT volume from 24,584 to 23,077 (6.1% [6.4–5.8]; p < 0.0001). Larger declines were observed at high-volume compared with low-volume centers (all p < 0.0001). There was no significant change in mechanical thrombectomy volumes (0.7% [0.6–0.9]; p = 0.49). Stroke was diagnosed in 1.3% [1.31–1.38] of 406,792 COVID-19 hospitalizations. SARS-CoV-2 infection was present in 2.9% ([2.82–2.97], 5,656/195,539) of all stroke hospitalizations. Discussion There was a global decline and shift to lower-volume centers of stroke admission volumes, ICH volumes, and IVT volumes during the 1st year of the COVID-19 pandemic compared with the prior year. Mechanical thrombectomy volumes were preserved. These results suggest preservation in the stroke care of higher severity of disease through the first pandemic year. Trial Registration Information This study is registered under NCT04934020.

To meet the requirements imposed by the time-dependency of acute stroke therapies, it is necessary 1) to initiate structural and cultural changes in the breadth of stroke-ready hospitals and 2) to find new ways to train the personnel treating patients with acute stroke. We aimed to implement and validate a composite intervention of a stroke team algorithm and simulation-based stroke team training as an effective quality initiative in our regional interdisciplinary neurovascular network consisting of 7 stroke units. We recorded door-to-needle times of all consecutive stroke patients receiving thrombolysis at seven stroke units for 3 months before and after a 2 month intervention which included setting up a team-based stroke workflow at each stroke unit, a train-the-trainer seminar for stroke team simulation training and a stroke team simulation training session at each hospital as well as a recommendation to take up regular stroke team trainings. The intervention reduced the network-wide median door-to-needle time by 12 minutes from 43,0 (IQR 29,8–60,0, n = 122) to 31,0 (IQR 24,0–42,0, n = 112) minutes (p < 0.001) and substantially increased the share of patients receiving thrombolysis within 30 minutes of hospital arrival from 41.5% to 59.6% (p < 0.001). Stroke team training participants stated a significant increase in knowledge on the topic of acute stroke care and in the perception of patient safety. The overall course concept was regarded as highly useful by most participants from different professional backgrounds. The composite intervention of a binding team-based algorithm and stroke team simulation training showed to be well-transferable in our regional stroke network. We provide suggestions and materials for similar campaigns in other stroke networks.

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak.

(Background): Effective prevention strategies and acute therapies have been established and distributed in recent years to reduce the global burden of stroke. However, beyond randomized clinical trials, limited data exist on the real-world impact of these measures. Our goal was to analyze whether the stroke-associated disability in the population decreased over time based on a state-wide stroke registry analysis. (Methods): Consecutive data from a state-wide inpatient stroke registry covering the entire federal state of Hesse, Germany, were obtained. The clinical data of 141,287 patients with ischemic stroke (ICD-10: I63) admitted between 2010 and 2019 were included. The primary outcome was the odds ratio for a change of modified Ranking Scale (mRS) at discharge over time, estimated by ordinary logistic regression and adjusted for age and sex. The secondary outcome was the odds ratio for a lower National Institutes of Health Stroke Scale (NIHSS) score at hospital admission. (Results): The absolute number of severely disabled (mRS 4–5) stroke patients at discharge decreased over time (2010: 3223 (equivalent to 53/100,000 population); 2019: 2429 [39/100,000 population]). The odds at hospital admission for a higher mRS at discharge decreased significantly by 3.7% per year (OR 0.963 (95% CI 0.960–0.966), p < 0.001). The absolute number of severely affected stroke patients (NIHSS > 15) at admission declined over time (2010: 1589 [26/100,000]; 2019: 1185 [19/100,000]; p < 0.001). The odds for a higher NIHSS score at admission to hospital decreased by 3.8% per year (OR 0.962 (95% CI 0.959–0.965), p < 0.001). Trends were most prominent for patients aged 80 years and older and for patients with atrial fibrillation but absent in patients <60 years. (Conclusions): Stroke-associated disability in the population steadily decreased between 2010 and 2019. The improved prevention of severe strokes in elderly patients may be a major driver of this observation.

Introduction: Antiplatelet and anticoagulant therapies complicate the management and outcomes of traumatic brain injury (TBI) patients. This study evaluates clinical profiles and short-term outcomes focusing on prior antihemostatic therapy and tranexamic acid (TXA) use.Patients and methods: We analyzed TBI patients admitted to University Hospital Frankfurt (2018–2021), assessing demographics, injury characteristics, clinical course, and short-term outcomes. The primary endpoint was hemorrhage progression; secondary endpoints included the modified Rankin Scale (mRS) at discharge, mortality and thromboembolic complications. Regression models identified predictors of functional outcome and mortality.Results: Among 218 patients (median age 70 years, 35% female, median GCS at admission 7), 44% had prior antiplatelet or anticoagulation therapy. These patients were older, had higher pre-injury mRS scores, and more often sustained TBIs from falls. While hemorrhage progression was similar, they had worse mRS scores (p = 0.02) and higher mortality (p = 0.002). Coagulopathy (OR 1.11, CI 1.07–1.16, p < 0.001), injury severity (OR 2.25, CI 1.51–3.41, p < 0.001), and bleeding progression (OR 2.23, CI 1.48–3.41, p < 0.001) predicted poor functional outcomes. TXA was more often given to younger, severely injured patients but did not impact outcome.Conclusion: This study underscores the need for tailored therapeutic approaches to improve survival and functional recovery in patients with pre-injury antiplatelet and anticoagulant therapies.

(1) Intravenous thrombolysis with recombinant tissue plasminogen activator (rt-PA) in patients with acute ischemic stroke is limited because of several contraindications. In routine clinical practice, patients with a recent stroke are typically not treated with rt-PA in case of a recurrent ischemic event. The same applies to its use in the context of pulmonary artery embolism and myocardial infarction with a recent stroke. In this translational study, we evaluated whether rt-PA treatment after experimental ischemic stroke with or without additional hyperglycemia increases the risk for hemorrhagic transformation (HT) and worsens functional outcome regarding the old infarct area. (2) In total, 72 male C57BL/6N mice were used. Ischemic stroke (index stroke) was induced by transient middle cerebral artery occlusion (tMCAO). Mice received either rt-PA or saline 24 h or 14 days after index stroke to determine whether a recent ischemic stroke predisposes to HT. In addition to otherwise healthy mice, hyperglycemic mice were analyzed to evaluate diabetes as a second risk factor for HT. Mice designated to develop hyperglycemia were pre-treated with streptozotocin. (3) The neurological outcome in rt-PA and saline-treated normoglycemic mice did not differ significantly, either at 24 h or at 14 days. In contrast, hyperglycemic mice treated with rt-PA had a significantly worse neurological outcome (at 24 h, p = 0.02; at 14 days, p = 0.03). At 24 h after rt-PA or saline treatment, HT scores differed significantly (p = 0.02) with the highest scores within hyperglycemic mice treated with rt-PA, where notably only small petechial hemorrhages could be detected. (4) Thrombolysis after recent ischemic stroke does not increase the risk for HT or worsen the functional outcome in otherwise healthy mice. However, hyperglycemia as a second risk factor leads to neurological deterioration after rt-PA treatment, which cannot be explained by an increase of HT alone. Direct neurotoxic effects of rt-PA may play a role.