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Prehospital technologies for early stroke detection - A review.
Agrawal, Deepsha; Dhillon, Permesh; Siow, Isabel; Lee, Keng Siang; Spooner, Oliver; Yeo, Leonard; Bhogal, Pervinder.
Afiliação
  • Agrawal D; Department of Radiology, 6397Oxford University Hospitals NHS Trust, Oxford, UK.
  • Dhillon P; Department of Interventional Neuroradiology, 105590Queens Medical Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK.
  • Siow I; Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Lee KS; 152331Bristol Medical School, University of Bristol, UK.
  • Spooner O; Department of Stroke Medicine, 112001The Royal London Hospital, Barts NHS Trust, London, UK.
  • Yeo L; Division of Neurology, Department of Medicine, National University Health System, Singapore.
  • Bhogal P; Department of Interventional Neuroradiology, 112001The Royal London Hospital, Barts NHS Trust, London, UK.
Interv Neuroradiol ; : 15910199231152372, 2023 Jan 18.
Article em En | MEDLINE | ID: mdl-36654460
The rate of neural circuitry loss in a typical large vessel occlusion well emphasizes that 'Time is Brain'. Every untreated minute in a large vessel ischaemic stroke results in loss of 1.9 million neurons and 13.8 billion synapses. As such, it is essential to optimize the flow-limiting steps in delivering the current standard of care. The current diagnostic model involves recognition of symptoms by patients, followed by access to Emergency Medical Services and subsequent physical examination and neuroimaging in the Emergency Department. With more than 50% of stroke patients using Emergency Medical Services as the first point of care contact, it can be deduced that the outcome of the 'stroke chain of survival' can be improved by addressing the bottleneck of prehospital stroke diagnosis. Here we present a review of the existing technologies.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article