Data about the coronavirus disease 2019 (COVID-19) pandemic’s collateral damage on ischemic stroke (IS) care during the second epidemic wave in Central Europe are limited. We sought to evaluate the impact of the COVID-19 outbreak on Hungarian IS care during the two epidemic waves. This retrospective observational study was based on a nationwide reimbursement database that encompasses all IS admissions and all reperfusion interventions, i.e., intravenous thrombolysis (IVT) and endovascular therapy (EVT) from 2 January 2017 to 31 December 2020 in Hungary. COVID-19 pandemic’s effect on the number of IS admissions and reperfusion interventions were analyzed using different statistics: means, medians, trends, relative rates, and linear relationships. The mean and median values of IS admissions and reperfusion interventions decreased only in some measure during the COVID-periods. However, trend analysis demonstrated a significant decline from the trends. The decline’s dynamic and amplitude have differed for each variable. In contrast to IVT, the number of IS admissions and EVTs negatively correlated with the epidemic waves’ amplitude. Besides, the decrease in the number of IS admissions was more pronounced than the decrease in the number of reperfusion interventions. Our study demonstrated a significant disruption in IS care during the COVID-19 epidemic in Hungary, in which multiple different factors might play a role. The disproportionate reduction of IS admission numbers could partially be explained by the effect of health emergency operative measures and changes in patients’ social behavior. Further studies are needed to evaluate the causes of our observations.

Background and purpose: Brain arteriovenous malformations (AVM) are uncommon vascular lesions with the risk of hemorrhage, epileptic seizures, neurological deficits, and headache. Comparing the risks of the natural history and that of preventive treatment, a recent study has found observation more beneficial than treatment for unruptured AVMs. This study, however, did not consider the long-term impact of carrying a brain AVM on everyday activities. In this study we analyzed the Quality Of Life (QOL) of patients with untreated AVMs, a measure increasingly used in clinical trials to asses this kind of impact.Methods: We enrolled 36 patients with unruptured, untreated brain AVM from our hospital database and measured their QOL retrospectively using the EQ-5D-5L questionnaire. As a control group we used the results of the Research Report, a nationwide study based on the quality of life of 5534 healthy Hungarians in 2002. Due to the low number of cases, statistical analysis could not be made.Results: Headache proved to be the most common AVM-related sign in our cohort (40%, n = 17), with a female predominance; neurological deficit was detected in 33% (n = 14), while epileptic seizures occurred in 26% (n = 11), more commonly affecting male subjects. Anxiety and discomfort seemed to be the most prevalent influencing factors on QOL, especially in the youngest age group (18–34 years). Female subjects showed a greater dependence than men in all age groups, though males had a more significant impairment in their usual activities. Older patients were affected more significantly in their self-care and usual activities compared with the younger population.Conclusions: Untreated AVMs have a significant negative impact on patients carrying unruptured brain AVMs, as proved by QOL assessment. Beside neurological deficits, this impact should also be considered in the therapeutic decision.

Purpose New guidelines recommend thrombectomy up to 24 h in selected patients; however, the workload and benefit of extending time window are not known. We conducted a prospective single-centre study to determine the caseload, imaging and interventional need of extended time window. Methods All consecutive ischemic stroke patients within 24 h from onset in an 11-month period were included. Thrombectomy eligibility in the 0–6 h time window was based on current guidelines; in the 6–24 h time window, it was based on a combination of DEFUSE 3 and DAWN study criteria using MRI to identify target mismatch. Clinical outcome in treated patients was assessed at 3 months. Results Within 24 h of onset, 437 patients were admitted. In the 0–6 h time window, 238 patients (54.5%) arrived of whom 221 (92.9%) underwent CTA or MRA, 82 (34.5%) had large vessel occlusion (LVO), 30 (12.6%) had thrombectomy and 11 (36.6%) became independent (mRS ≤ 2). In the extended 6–24 h time window, 199 patients (45.5%) arrived of whom 127 (63.8%) underwent CTA or MRA, 44 (22.1%) had LVO, 8 (4%) had thrombectomy and 4 (50%) became independent. Conclusion Extending the time window from 6 to 24 h results in a 26.7% increase in patients receiving thrombectomy and a 36.4% increase of independent clinical outcome in treated patients at the price of a significantly increased burden of clinical and imaging screening due to the similar caseload but a smaller proportion of treatment eligible patients in the extended as compared with the standard time window.

Background Patient selection for reperfusion therapies requires significant expertise in neuroimaging. Increasingly, machine learning based analysis is used for faster and standardized patient selection. However, there is little information on how such software influences real-world patient management. Aims We evaluated changes in thrombolysis and thrombectomy delivery following implementation of automated analysis at a high volume primary stroke centre. Methods We retrospectively collected data on consecutive stroke patients admitted to a large university stroke centre from two identical seven-month periods in 2017 and 2018 between which the e-Stroke Suite (Brainomix, Oxford, UK) was implemented to analyse non-contrast CT and CT angiography results. Delivery of stroke care was otherwise unchanged. Patients were transferred to a hub for thrombectomy. We collected the number of patients receiving intravenous thrombolysis and/or thrombectomy, the time to treatment; and outcome at 90 days for thrombectomy. Results 399 patients from 2017 and 398 from 2018 were included in the study. From 2017 to 2018 thrombolysis rates increased from 11.5% to 18.1% with a similar trend for thrombectomy (2.8% to 4.8%). There was a trend towards shorter door-to-needle times (44 to 42 minutes) and CT-to-groin puncture times (174 to 145 minutes). There was a non-significant trend towards improved outcomes with thrombectomy. Qualitatively, physician feedback suggested that e-Stroke Suite increased decision-making confidence and improved patient flow. Conclusions Use of artificial intelligence decision support in a hyperacute stroke pathway facilitates decision-making and can improve rate and time of reperfusion therapies in a hub-and-spoke system of care.

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