A prospective study of MRI biomarkers in the brain and lower limb muscles for prediction of lower limb motor recovery following stroke.

The aim of this prospective observational longitudinal study was to explore and decipher the predictive value of prospective MRI biomarkers in the brain and lower limb muscles for 3-month lower limb motor recovery following stroke. In the brain, we measured the integrity of the corticospinal tract (fractional anisotropy/"FA"). In the muscles, we measured volume, fatty replacement (fat fraction analysis and proton spectroscopy) and oedema. Measurements were taken at two time points: (1) within 4 weeks of stroke (baseline measurement, clinical and imaging) and (2) 3 months following stroke (follow up measurement, clinical only). Clinical measurements consisted of assessments of functional ability and strength (Fugl-Meyer score, motor NIHSS, Functional Ambulation Category/"FAC", and muscle dynamometry). Twenty-three patients completed imaging and clinical assessments at baseline and follow-up; five patients had partial imaging assessment. The results provided some evidence that damage to the corticospinal tract would result in less motor recovery: recovery of the Fugl-Meyer score and dynamometric ankle plantarflexion, ankle dorsiflexion, and knee extension correlated positively and significantly with fractional anisotropy (0.406-0.457; p = 0.034-p = 0.016). However, fractional anisotropy demonstrated a negative correlation with recovery of the Functional Ambulation Category (-0.359, p = 0.046). For the muscle imaging, significant inverse correlation was observed between vastus lateralis fat fraction vs. NIHSS recovery (-0.401, p = 0.04), and a strong positive correlation was observed between ratio of intra- to extra-myocellular lipid concentrations and the recovery of knee flexion (0.709, p = 0.007). This study supports previous literature indicating a positive correlation between the integrity of the corticospinal tract and motor recovery post-stroke, expanding the limited available literature describing this relationship specifically for the lower limb. However, recovery of functional ambulation behaved differently to other clinical recovery markers by demonstrating an inverse relationship with corticospinal tract integrity. The study also introduces some muscle imaging biomarkers as potentially valuable in the prediction of 3-month lower limb motor recovery following stroke.

Surface electroencephalography (EEG) during the acute phase of stroke to assist with diagnosis and prediction of prognosis: a scoping review.

BACKGROUND: Stroke is a common medical emergency responsible for significant mortality and disability. Early identification improves outcomes by promoting access to time-critical treatments such as thrombectomy for large vessel occlusion (LVO), whilst accurate prognosis could inform many acute management decisions. Surface electroencephalography (EEG) shows promise for stroke identification and outcome prediction, but evaluations have varied in technology, setting, population and purpose. This scoping review aimed to summarise published literature addressing the following questions: 1. Can EEG during acute clinical assessment identify: a) Stroke versus non-stroke mimic conditions. b) Ischaemic versus haemorrhagic stroke. c) Ischaemic stroke due to LVO. 2. Can these states be identified if EEG is applied < 6 h since onset. 3. Does EEG during acute assessment predict clinical recovery following confirmed stroke. METHODS: We performed a systematic search of five bibliographic databases ending 19/10/2020. Two reviewers assessed eligibility of articles describing diagnostic and/or prognostic EEG application < 72 h since suspected or confirmed stroke. RESULTS: From 5892 abstracts, 210 full text articles were screened and 39 retained. Studies were small and heterogeneous. Amongst 21 reports of diagnostic data, consistent associations were reported between stroke, greater delta power, reduced alpha/beta power, corresponding ratios and greater brain asymmetry. When reported, the area under the curve (AUC) was at least good (0.81-1.00). Only one study combined clinical and EEG data (AUC 0.88). There was little data found describing whether EEG could identify ischaemic versus haemorrhagic stroke. Radiological changes suggestive of LVO were also associated with increased slow and decreased fast waves. The only study with angiographic proof of LVO reported AUC 0.86 for detection < 24 h since onset. Amongst 26 reports of prognostic data, increased slow and reduced fast wave EEG changes were associated with future dependency, neurological impairment, mortality and poor cognition, but there was little evidence that EEG enhanced outcome prediction relative to clinical and/or radiological variables. Only one study focussed solely on patients < 6 h since onset for predicting neurological prognosis post-thrombolysis, with more favourable outcomes associated with greater hemispheric symmetry and a greater ratio of fast to slow waves. CONCLUSIONS: Although studies report important associations with EEG biomarkers, further technological development and adequately powered real-world studies are required before recommendations can be made regarding application during acute stroke assessment.

Secondary transfer of emergency stroke patients eligible for mechanical thrombectomy by air in rural England: economic evaluation and considerations.

BACKGROUND: Mechanical thrombectomy (MT) is a time-sensitive emergency procedure for patients who had ischaemic stroke leading to improved health outcomes. Health systems need to ensure that MT is delivered to as many patients as quickly as possible. Using decision modelling, we aimed to evaluate the cost-effectiveness of secondary transfer by helicopter emergency medical services (HEMS) compared with ground emergency medical services (GEMS) of rural patients eligible for MT in England. METHODS: The model consisted of (1) a short-run decision tree with two branches, representing secondary transfer transportation strategies and (2) a long-run Markov model for a theoretical population of rural patients with a confirmed ischaemic stroke. Strategies were compared by lifetime costs: quality-adjusted life years (QALYs), incremental cost per QALY gained and net monetary benefit. Sensitivity and scenario analyses explored uncertainty around parameter values. RESULTS: We used the base case of early-presenting (<6 hours to arterial puncture) patient aged 75 years who had stroke to compare HEMS and GEMS. This produced an incremental cost-effectiveness ratio (ICER) of £28 027 when a 60 min reduction in travel time was assumed. Scenario analyses showed the importance of the reduction in travel time and futile transfers in lowering ICERs. For late presenting (>6 hours to arterial puncture), ground transportation is the dominant strategy. CONCLUSION: Our model indicates that using HEMS to transfer patients who had stroke eligible for MT from remote hospitals in England may be cost-effective when: travel time is reduced by at least 60 min compared with GEMS, and a £30 000/QALY threshold is used for decision-making. However, several other logistic considerations may impact on the use of air transportation.

The cost of providing mechanical thrombectomy in the UK NHS: a micro-costing study.

INTRODUCTION: The clinical efficacy and cost-effectiveness of mechanical thrombectomy (MT) for the treatment of large vessel occlusion stroke is well established, but uncertainty remains around the true cost of delivering this treatment within the NHS. The aim of this study was to establish the cost of providing MT within the hyperacute phase of care and to explore differences in resources used and costs across different neuroscience centres in the UK. METHOD: This was a multicentre retrospective study using micro-costing methods to enable a precise assessment of the costs of MT from an NHS perspective. Data on resources used and their costs were collected from five UK neuroscience centres between 2015 and 2018. RESULTS: Data were collected on 310 patients with acute ischaemic stroke treated with MT. The mean total cost of providing MT and inpatient care within 24 hours was £10,846 (95% confidence interval (CI) 10,527-11,165) per patient. The main driver of cost was MT procedure costs, accounting for 73% (£7,943; 95% CI 7,649-8,237) of the total 24-hour cost. Costs were higher for patients treated under general anaesthesia (£11,048; standard deviation (SD) 2,654) than for local anaesthesia (£9,978; SD 2,654), mean difference £1,070 (95% CI 381-1,759; p=0.003); admission to an intensive care unit (ICU; £12,212; SD 3,028) against for admission elsewhere (£10,179; SD 2,415), mean difference £2,032 (95% CI 1,345-2,719; p<0001).The mean cost within 72 hours was £12,440 (95% CI 10,628-14,252). The total costs for the duration of inpatient care before discharge from a thrombectomy centre was £14,362 (95% CI 13,603-15,122). CONCLUSIONS: Major factors contributing to costs of MT for stroke include consumables and staff for intervention, use of general anaesthesia and ICU admissions. These findings can inform the reimbursement, provision and strategic planning of stroke services and aid future economic evaluations.

A scoping review of pre-hospital technology to assist ambulance personnel with patient diagnosis or stratification during the emergency assessment of suspected stroke.

BACKGROUND: Pre-hospital identification of key subgroups within the suspected stroke population could reduce delays to emergency treatment. We aimed to identify and describe technology with existing proof of concept for diagnosis or stratification of patients in the pre-hospital setting. METHODS: A systematic electronic search of published literature (from 01/01/2000 to 06/06/2019) was conducted in five bibliographic databases. Two reviewers independently assessed eligibility of studies or study protocols describing diagnostic/stratification tests (portable imaging/biomarkers) or technology facilitating diagnosis/stratification (telemedicine) used by ambulance personnel during the assessment of suspected stroke. Eligible descriptions required use of tests or technology during the actual assessment of suspected stroke to provide information directly to ambulance personnel in the pre-hospital setting. Due to study, intervention and setting heterogeneity there was no attempt at meta-analysis. RESULTS: 2887 articles were screened for eligibility, 19 of which were retained. Blood biomarker studies (n = 2) were protocols of prospective diagnostic accuracy studies, one examining purines and the other a panel of known and novel biomarkers for identifying stroke sub-types (versus mimic). No data were yet available on diagnostic accuracy or patient health outcomes. Portable imaging studies (n = 2) reported that an infrared screening device for detecting haemorrhages yielded moderate sensitivity and poor specificity in a small study, whilst a dry-EEG study to detect large vessel occlusion in ischaemic stroke has not yet reported results. Fifteen evaluations of pre-hospital telemedicine were identified (12 observational and 3 controlled comparisons) which all involved transmission of stroke assessment data from the pre-hospital setting to the hospital. Diagnosis was generally comparable with hospital diagnosis and most telemedicine systems reduced time-to-treatment; however, it is unknown whether this time saving translated into more favourable clinical outcomes. Telemedicine systems were deemed acceptable by clinicians. CONCLUSIONS: Pre-hospital technologies to identify clinically important subgroups amongst the suspected stroke population are in development but insufficient evidence precludes recommendations about routine use in the pre-hospital setting. Multi-centre diagnostic accuracy studies and clinical utility trials combining promising technologies are warranted.

Estimating the effectiveness and cost-effectiveness of establishing additional endovascular Thrombectomy stroke Centres in England: a discrete event simulation.

BACKGROUND: We have previously modelled that the optimal number of comprehensive stroke centres (CSC) providing endovascular thrombectomy (EVT) in England would be 30 (net 6 new centres). We now estimate the relative effectiveness and cost-effectiveness of increasing the number of centres from 24 to 30. METHODS: We constructed a discrete event simulation (DES) to estimate the effectiveness and lifetime cost-effectiveness (from a payer perspective) using 1 year's incidence of stroke in England. 2000 iterations of the simulation were performed comparing baseline 24 centres to 30. RESULTS: Of 80,800 patients admitted to hospital with acute stroke/year, 21,740 would be affected by the service reconfiguration. The median time to treatment for eligible early presenters (< 270 min since onset) would reduce from 195 (IQR 155-249) to 165 (IQR 105-224) minutes. Our model predicts reconfiguration would mean an additional 33 independent patients (modified Rankin scale [mRS] 0-1) and 30 fewer dependent/dead patients (mRS 3-6) per year. The net addition of 6 centres generates 190 QALYs (95%CI - 6 to 399) and results in net savings to the healthcare system of £1,864,000/year (95% CI -1,204,000 to £5,017,000). The estimated budget impact was a saving of £980,000 in year 1 and £7.07 million in years 2 to 5. CONCLUSION: Changes in acute stroke service configuration will produce clinical and cost benefits when the time taken for patients to receive treatment is reduced. Benefits are highly likely to be cost saving over 5 years before any capital investment above £8 million is required.