Background: Large vessel occlusive (LVO) stroke causes severe disabilities and occurs in more than 37% of strokes. Reperfusion therapy is the gold standard of treatment. Studies proved that endovascular thrombectomy (EVT) is more beneficial and decreases mortality. This study aimed to evaluate the factor associated with LVO stroke in an Asian population and to develop the scores to predict LVO in a prehospital setting. The score will hugely contribute to the future of stroke care in prehospital settings in the aspect of transferal suspected LVO stroke patients to appropriate EVT-capable stroke centers.
Methods: This study was a retrospective cohort study using an exploratory model at the emergency department of Ramathibodi Hospital, Bangkok, Thailand, between January 2018 and December 2020. We included the stroke patients aged >18 who visit ED and an available radiologic report representing LVO. Those whose stroke onset was >24 hours and no radiologic report were excluded. Multivariable logistic regression analysis developed the prediction model and score for LVO stroke.
Results: A total of 252 patients met the inclusion criteria; 61 cases (24%) had LVO stroke. Six independent factors were significantly predictive: comorbidity with atrial fibrillation, clinical hemineglect, gaze deviation, facial palsy, aphasia, and cerebellar sign abnormality. The predicted score had an accuracy of 92.5%. The LVO risk score was categorized into three groups: low risk (LVO score <3), moderate risk (LVO score 3-6), and high risk (LVO score >6). The positive likelihood ratio to predicting LVO stroke were 0.12 (95% CI 0.06-0.26), 2.33 (95% CI 1.53-3.53) and 45.40 (95% CI 11.16-184.78), respectively.
Conclusion: The Large Vessel Occlusion (LVO) Risk Score provides a screening tool for predicting LVO stroke. A clinical predictive score of ≥3 appears to be associated with LVO stroke.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925388 | PMC |
http://dx.doi.org/10.2147/OAEM.S398061 | DOI Listing |
Rev Neurol (Paris)
January 2025
Unité neurovasculaire, Centre Hospitalier Métropole Savoie, Chambéry, France. Electronic address:
Introduction: Prehospital identification of stroke patients with large vessel occlusion (LVO) is crucial to optimize transport to an endovascular thrombectomy (EVT)-capable center. Existing scores require medical or paramedical expertise and specific teachings. We aimed to validate a simple prehospital phone-based score for LVO identification.
View Article and Find Full Text PDFJ Neurointerv Surg
January 2025
Department of Neurology, UTHealth Houston McGovern Medical School, Houston, Texas, USA
Background: Automated machine learning (ML)-based large vessel occlusion (LVO) detection algorithms have been shown to improve in-hospital workflow metrics including door-to-groin time (DTG). The degree to which care team engagement and interaction are required for these benefits remains incompletely characterized.
Methods: This analysis was conducted as a pre-planned post-hoc analysis of a randomized prospective clinical trial.
AJNR Am J Neuroradiol
January 2025
From the University of Miami Department of Neurology (H.B.F., I.R., R.Y., A.A., M.S., Y.H., A.A., C.M.G., V.J.D.B., R.M.S., T.R., H.G., J.G.R., N.A.), Miami, FL, USA; University of South Florida Department of Neurology (D.Z.R. A.J.), Tampa, FL, USA.
Background And Purpose: Endovascular thrombectomy outcomes are impacted by changes in stroke systems of care. During the pandemic, SARS-CoV2 positive status had major implications on hospital arrival and treatment models of non-COVID related hospital admissions. Using the Florida Stroke Registry, we compared the rates of in-hospital death and discharge outcomes of patients treated with endovascular thrombectomy who tested positive for SARS-CoV2 infection during their hospitalization.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Neurology, Virginia Commonwealth University, Richmond, VA 23298, USA.
Acute ischemic stroke with large vessel occlusion (LVO) continues to present a considerable challenge to global health, marked by substantial morbidity and mortality rates. Although definitive diagnostic markers exist in the form of neuroimaging, their expense, limited availability, and potential for diagnostic delay can often result in missed opportunities for life-saving interventions. Despite several past attempts, research efforts to date have been fraught with challenges likely due to multiple factors, such as the inclusion of diverse stroke types, variable onset intervals, differing pathobiologies, and a range of infarct sizes, all contributing to inconsistent circulating biomarker levels.
View Article and Find Full Text PDFJ Neurointerv Surg
January 2025
Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan
Background: Timely treatment within the therapeutic window is critical for patients with stroke. This study adopts a risk-averse optimization approach to maximize the likelihood of receiving treatment within this window.
Methods: We developed an optimization model using data from a citywide stroke registry (July 1, 2019 to December 31, 2020).
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!