Background Concerns regarding potential neurological complications of COVID-19 are being increasingly reported, primarily in small series. Larger studies have been limited by both geography and specialty. Comprehensive characterisation of clinical syndromes is crucial to allow rational selection and evaluation of potential therapies. The aim of this study was to investigate the breadth of complications of COVID-19 across the UK that affected the brain. Methods During the exponential phase of the pandemic, we developed an online network of secure rapid-response case report notification portals across the spectrum of major UK neuroscience bodies, comprising the Association of British Neurologists (ABN), the British Association of Stroke Physicians (BASP), and the Royal College of Psychiatrists (RCPsych), and representing neurology, stroke, psychiatry, and intensive care. Broad clinical syndromes associated with COVID-19 were classified as a cerebrovascular event (defined as an acute ischaemic, haemorrhagic, or thrombotic vascular event involving the brain parenchyma or subarachnoid space), altered mental status (defined as an acute alteration in personality, behaviour, cognition, or consciousness), peripheral neurology (defined as involving nerve roots, peripheral nerves, neuromuscular junction, or muscle), or other (with free text boxes for those not meeting these syndromic presentations). Physicians were encouraged to report cases prospectively and we permitted recent cases to be notified retrospectively when assigned a confirmed date of admission or initial clinical assessment, allowing identification of cases that occurred before notification portals were available. Data collected were compared with the geographical, demographic, and temporal presentation of overall cases of COVID-19 as reported by UK Government public health bodies.

SummaryBackgroundResults of small trials indicate that fluoxetine might improve functional outcomes after stroke. The FOCUS trial aimed to provide a precise estimate of these effects.MethodsFOCUS was a pragmatic, multicentre, parallel group, double-blind, randomised, placebo-controlled trial done at 103 hospitals in the UK. Patients were eligible if they were aged 18 years or older, had a clinical stroke diagnosis, were enrolled and randomly assigned between 2 days and 15 days after onset, and had focal neurological deficits. Patients were randomly allocated fluoxetine 20 mg or matching placebo orally once daily for 6 months via a web-based system by use of a minimisation algorithm. The primary outcome was functional status, measured with the modified Rankin Scale (mRS), at 6 months. Patients, carers, health-care staff, and the trial team were masked to treatment allocation. Functional status was assessed at 6 months and 12 months after randomisation. Patients were analysed according to their treatment allocation. This trial is registered with the ISRCTN registry, number ISRCTN83290762.FindingsBetween Sept 10, 2012, and March 31, 2017, 3127 patients were recruited. 1564 patients were allocated fluoxetine and 1563 allocated placebo. mRS data at 6 months were available for 1553 (99·3%) patients in each treatment group. The distribution across mRS categories at 6 months was similar in the fluoxetine and placebo groups (common odds ratio adjusted for minimisation variables 0·951 [95% CI 0·839–1·079]; p=0·439). Patients allocated fluoxetine were less likely than those allocated placebo to develop new depression by 6 months (210 [13·43%] patients vs 269 [17·21%]; difference 3·78% [95% CI 1·26–6·30]; p=0·0033), but they had more bone fractures (45 [2·88%] vs 23 [1·47%]; difference 1·41% [95% CI 0·38–2·43]; p=0·0070). There were no significant differences in any other event at 6 or 12 months.InterpretationFluoxetine 20 mg given daily for 6 months after acute stroke does not seem to improve functional outcomes. Although the treatment reduced the occurrence of depression, it increased the frequency of bone fractures. These results do not support the routine use of fluoxetine either for the prevention of post-stroke depression or to promote recovery of function.FundingUK Stroke Association and NIHR Health Technology Assessment Programme.

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Background: Acute stroke patients are usually transported to the nearest hospital regardless of their required level of care. This can lead to increased pressure on emergency departments and treatment delay. Objective: The aim of the study was to explore the benefit of a mobile stroke unit (MSU) in the UK National Health Service (NHS) for reduction of hospital admissions. Methods: Prospective cohort audit observation with dispatch of the MSU in the East of England Ambulance Service area in Southend-on-Sea was conducted. Emergency patients categorized as code stroke and headache were included from June 5, 2018, to December 18, 2018. Rate of avoided admission to the accident and emergency (A&E) department, rate of admission directly to target ward, and stroke management metrics were assessed. Results: In 116 MSU-treated patients, the following diagnoses were made: acute stroke, n = 33 (28.4%); transient ischaemic attacks, n = 13 (11.2%); stroke mimics, n = 32 (27.6%); and other conditions, n = 38 (32.8%). Pre-hospital thrombolysis was administered to 8 of 28 (28.6%) ischaemic stroke patients. Pre-hospital diagnosis avoided hospital admission for 29 (25.0%) patients. As hospital treatment was indicated, 35 (30.2%) patients were directly triaged to the stroke unit, 1 patient (0.9%) even directly to the catheter laboratory. Thus, only 50 (43.1%) patients required transfer to the A&E department. Moreover, the MSU enabled thrombolysis with a median dispatch-to-needle time of 42 min (interquartile range, 40–60). Conclusion: This first deployment of an MSU in the UK NHS demonstrated improved triage decision-making for or against hospital admission and admission to the appropriate target ward, thereby reducing pressure on strained A&E departments.

Background: ASPECTS (Alberta Stroke Program Early CT Score) is a validated scoring system for assessment of early ischemic change (EIC) on CT head scans, which can be used to guide patient management and improve diagnostic accuracy. Detection of EIC can be challenging particularly for less experienced clinicians. e-ASPECTS software uses machine learning algorithms to support physicians in detecting EIC, which can be quantified using the ASPECTS score. Hypothesis: e-ASPECTS shortens time for CT scan assessment and improves agreement with reference standard ASPECTS when compared to blinded assessment. Methods: 26 clinicians (including 11 radiologists, 6 junior and 7 consultant stroke physicians, and 2 non-specialist physicians) independently scored 2560 ASPECTS regions from 64 patients for signs of EIC on non-contrast CT brain scans. These were acquired within 4.5 hours of stroke onset. A familiarization training set of 5 patients was used prior to scoring. Images were randomized to manual or software assistance. After two weeks images were rescored using the alternative method. Scorers were blinded to clinical symptoms. Reference standard scores were defined by an independent neuroradiologist with information on clinical symptoms, access to 24h follow-up, and with CT perfusion or MRI scans when available. Results: Mean NIHSS was 11. Mean time to score scans fell by 34% (45s, 2:12 to 1:27, mm:ss) using e-ASPECTS assistance. Rater agreement with ground truth was greatest in the radiologist cohort, but performance improved across all clinician categories using e-APSECTS assistance (radiology kappa: 0.26 to 0.38). Sensitivity to EIC improved by a factor of two across all clinician groups using e-ASPECTS assistance, and this was most marked for less experienced physicians. Conclusion: In acute ischemic stroke e-ASPECTS assisted analysis increased accuracy and reduced time for detection of EIC. Routine assistance of non-contrast CT interpretation has the potential to reduce treatment times and improve accuracy across clinicians and sites.