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Stroke Prehospital Informed Decision-Making Using EEG Recordings (SPIDER)

  • Wayne Loudon (a1), Andrew Wong (a2) (a3), Simon Finnigan (a4) and Vivienne Tippett (a5)
  • Please note a correction has been issued for this article.

Abstract

Introduction:

The acute care of stroke involves the administration of a clot-dissolving drug (thrombolysis) and/or its removal using endovascular clot retrieval. Earlier intervention results in significantly improved patient outcomes. Clinical assessment scores have limitations, and studies have shown that even the most robust scores have a reported false-negative rate of >20% for large vessel occlusive strokes that may be eligible for clot retrieval, while inappropriate bypass may delay delivery of thrombolysis.1 Quantitative Electroencephalography (QEEG) has been shown to have a very high sensitivity and specificity in the identification of acute stroke versus matched controls in an in-hospital setting.(2,3)

Aim:

The SPIDER study commenced in Brisbane, Queensland on September 3, 2018, and is investigating the use of an EEG recorder to gather data on acute stroke patients presenting to a metropolitan ambulance service.

Discussion:

The data collected will guide the development of a simple numerical output reference to guide decision making. The data may aid in identifying large vessel occlusive stroke and patients eligible for endovascular intervention. The QEEG will provide a more accurate and cost-effective tool for the prehospital clinician over other imaging technologies and can guide early destination decisions. This presentation discusses the implementation of a pre-hospital research platform, integration with the clinical dispatch matrix, staff engagement, patient recruitment, and the success of the project so far.

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References

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1.Turc, G, Maier, B, Naggara, O, et al. Clinical scales do not reliably identify acute ischaemic stroke patients with large-artery occlusion. Stroke 2016;47:14661472.
2.Finnigan, S, van Putten, M. EEG in ischaemic stroke: quantitative EEG can uniquely inform (sub-)acute prognoses and clinical management. Clin Neurophysiol. 2013;124(1):1019.
3.Finnigan, S, Wong, A, Read, S. Defining abnormal slow EEG activity in acute ischaemic stroke: delta/alpha ratio as an optimal QEEG index. Clin Neurophysiol. 2016;127(2):14521459.

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A correction has been issued for this article: