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Research outputs from the Stroke team at the RD&E.


Recent Submissions

Now showing 1 - 5 of 54
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    Presence of mediastinal lymphadenopathy in hospitalized Covid-19 patients in a tertiary care hospital in Pakistan-A cross-sectional study
    (PLoS One, 2023-05-25) Bhatti, F. S.; Malik, A. A.; Malik, A. A.
    BACKGROUND: The aim of this study was to investigate the presence of mediastinal lymphadenopathy in hospitalized Covid-19 patients in a tertiary care hospital in the metropolitan city of Lahore, Pakistan from September 2020 till July 2021. METHODS: We retrospectively collected data of Covid-19 patients hospitalized from September 2020 till July 2021. Only those patients who tested PCR positive through a nasopharyngeal swab, were enrolled in the study. Patients' whose data were missing were excluded from this study. Our exclusion criteria included patients who tested negative on Covid-19 PCR, patients with comorbidities that may cause enlarged mediastinal lymphadenopathies such as haemophagocytic lymphohistiocytosis, neoplasia, tuberculosis, sarcoidosis or a systemic disease. The extent of lung involvement in Covid-19 patients was quantified by using a 25-point visual quantitative assessment called the Chest Computed Tomography Score. This score was then correlated with the presence of mediastinal lymphadenopathy. FINDINGS: Of the 210 hospitalized patients included in the study, 131 (62.4%) had mediastinal lymphadenopathy. The mean and median Severity Score of Covid-19 patients with mediastinal lymphadenopathy (mean: 17.1, SD:5.7; median: 17, IQR: 13-23) were higher as compared to those without mediastinal lymphadenopathy (mean: 12.3, SD:5.4; median: 12, IQR:9-16). INTERPRETATION: Our study documents a high prevalence of mediastinal lymphadenopathy in hospitalized patients with Covid-19 with the severity score being higher in its presence representing a more severe course of disease.
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    What would other emergency stroke teams do? Using explainable machine learning to understand variation in thrombolysis practice
    (Sage, 2023-07-01) Pearn, K.; Allen, M.; Laws, A.; Monks, T.; Everson, R.; James, M.
    INTRODUCTION: The aim of this work was to understand between-hospital variation in thrombolysis use among emergency stroke admissions in England and Wales. PATIENTS: A total of 88,928 patients who arrived at all 132 emergency stroke hospitals in England Wales within 4 h of stroke onset, from 2016 to 2018. METHODS: Machine learning was applied to the Sentinel Stroke National Audit Programme (SSNAP) data set, to learn which patients in each hospital would likely receive thrombolysis. We used XGBoost machine learning models, coupled with a SHAP model for explainability; Shapley (SHAP) values, providing estimates of how patient features, and hospital identity, influence the odds of receiving thrombolysis. RESULTS: Thrombolysis use in patients arriving within 4 h of known or estimated stroke onset ranged 7% -49% between hospitals. The odds of receiving thrombolysis reduced 9-fold over the first 120 min of arrival-to-scan time, varied 30-fold with stroke severity, reduced 3-fold with estimated rather than precise stroke onset time, fell 6-fold with increasing pre-stroke disability, fell 4-fold with onset during sleep, fell 5-fold with use of anticoagulants, fell 2-fold between 80 and 110 years of age, reduced 3-fold between 120 and 240 min of onset-to-arrival time and varied 13-fold between hospitals. The majority of between-hospital variance was explained by the hospital, rather than the differences in local patient populations. CONCLUSIONS: Using explainable machine learning, we identified that the majority of the between-hospital variation in thrombolysis use in England and Wales may be explained by differences in in-hospital processes and differences in attitudes to judging suitability for thrombolysis.
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    Use of Clinical Pathway Simulation and Machine Learning to Identify Key Levers for Maximizing the Benefit of Intravenous Thrombolysis in Acute Stroke
    (American Heart Association, 2022-07-22) Allen, M.; James, C.; Frost, J.; Liabo, K.; Pearn, K.; Monks, T.; Everson, R.; Stein, K.; James, M.
    BACKGROUND: Expert opinion is that about 20% of emergency stroke patients should receive thrombolysis. Currently, 11% to 12% of patients in England and Wales receive thrombolysis, ranging from 2% to 24% between hospitals. The aim of this study was to assess how much variation is due to differences in local patient populations, and how much is due to differences in clinical decision-making and stroke pathway performance, while estimating a realistic target thrombolysis use. METHODS: Anonymised data for 246 676 emergency stroke admissions to 132 acute hospitals in England and Wales between 2016 and 2018 was obtained from the Sentinel Stroke National Audit Programme data. We used machine learning to learn decisions on who to give thrombolysis to at each hospital. We used clinical pathway simulation to model effects of changing pathway performance. Qualitative research was used to assess clinician attitudes to these methods. Three changes were modeled: (1) arrival-to-treatment in 30 minutes, (2) proportion of patients with determined stroke onset times set to at least the national upper quartile, (3) thrombolysis decisions made based on majority vote of a benchmark set of hospitals. RESULTS: Of the modeled changes, any single change was predicted to increase national thrombolysis use from 11.6% to between 12.3% to 14.5% (clinical decision-making having the most effect). Combined, these changes would be expected to increase thrombolysis to 18.3%, but there would still be significant variation between hospitals depending on local patient population. Clinicians engaged well with the modeling, but those from hospitals with lower thrombolysis use were most cautious about the methods. CONCLUSIONS: Machine learning and clinical pathway simulation may be applied at scale to national stroke audit data, allowing extended use and analysis of audit data. Stroke thrombolysis rates of at least 18% look achievable in England and Wales, but each hospital should have its own target.
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    Perfusion Imaging for Endovascular Thrombectomy in Acute Ischemic Stroke Is Associated With Improved Functional Outcomes in the Early and Late Time Windows
    (American Heart Association, 2022-05-05) Dhillon, P. S.; Butt, W.; Podlasek, A.; McConachie, N.; Lenthall, R.; Nair, S.; Malik, L.; Booth, T. C.; Bhogal, P.; Makalanda, H. L. D.; Spooner, O.; Mortimer, A.; Lamin, S.; Chavda, S.; Chew, H. S.; Nader, K.; Al-Ali, S.; Butler, B.; Rajapakse, D.; Appleton, J. P.; Krishnan, K.; Sprigg, N.; Smith, A.; Lobotesis, K.; White, P.; James, M. A.; Bath, P. M.; Dineen, R. A.; England, T. J.
    BACKGROUND: The impact on clinical outcomes of patient selection using perfusion imaging for endovascular thrombectomy (EVT) in patients with acute ischemic stroke presenting beyond 6 hours from onset remains undetermined in routine clinical practice. METHODS: Patients from a national stroke registry that underwent EVT selected with or without perfusion imaging (noncontrast computed tomography/computed tomography angiography) in the early (<6 hours) and late (6-24 hours) time windows, between October 2015 and March 2020, were compared. The primary outcome was the ordinal shift in the modified Rankin Scale score at hospital discharge. Other outcomes included functional independence (modified Rankin Scale score ≤2) and in-hospital mortality, symptomatic intracerebral hemorrhage, successful reperfusion (Thrombolysis in Cerebral Infarction score 2b-3), early neurological deterioration, futile recanalization (modified Rankin Scale score 4-6 despite successful reperfusion) and procedural time metrics. Multivariable analyses were performed, adjusted for age, sex, baseline stroke severity, prestroke disability, intravenous thrombolysis, mode of anesthesia (Model 1) and including EVT technique, balloon guide catheter, and center (Model 2). RESULTS: We included 4249 patients, 3203 in the early window (593 with perfusion versus 2610 without perfusion) and 1046 in the late window (378 with perfusion versus 668 without perfusion). Within the late window, patients with perfusion imaging had a shift towards better functional outcome at discharge compared with those without perfusion imaging (adjusted common odds ratio [OR], 1.45 [95% CI, 1.16-1.83]; P=0.001). There was no significant difference in functional independence (29.3% with perfusion versus 24.8% without; P=0.210) or in the safety outcome measures of symptomatic intracerebral hemorrhage (P=0.53) and in-hospital mortality (10.6% with perfusion versus 14.3% without; P=0.053). In the early time window, patients with perfusion imaging had significantly improved odds of functional outcome (adjusted common OR, 1.51 [95% CI, 1.28-1.78]; P=0.0001) and functional independence (41.6% versus 33.6%, adjusted OR, 1.31 [95% CI, 1.08-1.59]; P=0.006). Perfusion imaging was associated with lower odds of futile recanalization in both time windows (late: adjusted OR, 0.70 [95% CI, 0.50-0.97]; P=0.034; early: adjusted OR, 0.80 [95% CI, 0.65-0.99]; P=0.047). CONCLUSIONS: In this real-world study, acquisition of perfusion imaging for EVT was associated with improvement in functional disability in the early and late time windows compared with nonperfusion neuroimaging. These indirect comparisons should be interpreted with caution while awaiting confirmatory data from prospective randomized trials.
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    An Undergraduate Interprofessional Experience with Self-Learning Methodology in Simulation Environment (MAES©): A Qualitative Study
    (MDPI, 2022-06-23) Fenzi, G.; Díaz-Agea, J. L.; Pethick, D.; Bertolín-Delgado, R.; Hernández-Donoso, N.; Lorente-Corral, L.
    This article describes the impact that a Self-learning Methodology in Simulated Environments can have on Interprofessional Education within a Crisis Resource Management simulated scenario. We used a qualitative approach. It is divided into three phases: study and design, plan of action, and analysis and evaluation. During the first phase of the study, there emerged a poor use of Interprofessional Education in the nursing and medical degrees, and it became apparent that there was a need for an implementation. Due to the possibility for better training for both technical and non-technical skills within Crisis Resource Management, a simulation scenario within this setting has been established as a learning baseline objective. The technique used to develop the scenario in the second phase of the study was the Self-learning Methodology in Simulated Environments. Its structure, comprising six items, was previously demonstrated in the literature as appropriate for healthcare degree students. The main result of the third phase shows an overall acceptance of an Interprofessional Education within Self-learning Methodology in Simulated Environments during the practice of a Crisis Resource Management scenario. The integrated application of a Self-learning Methodology in Simulated Environments, Interprofessional Education, and Crisis Resource Management result in a synergistic combination that allows students to share knowledge, technical, and non-technical skills using an innovative learning method.