Prehospital triage of patients with suspected stroke symptoms (PRESTO): Protocol of a prospective observational study

Introduction: The efficacy of both intravenous treatment (IVT) and endovascular treatment (EVT) for patients with acute ischaemic stroke strongly declines over time. Only a subset of patients with ischaemic stroke caused by an intracranial large vessel occlusion (LVO) in the anterior circulation can benefit from EVT. Several prehospital stroke scales were developed to identify patients that are likely to have an LVO, which could allow for direct transportation of EVT eligible patients to an endovascular-capable centre without delaying IVT for the other patients. We aim to prospectively validate these prehospital stroke scales simultaneously to assess their accuracy in predicting LVO in the prehospital setting. Methods and analysis: Prehospital triage of patients with suspected stroke symptoms (PRESTO) is a prospective multicentre observational cohort study in the southwest of the Netherlands including adult patients with suspected stroke in the ambulance. The paramedic will assess a combination of items from five prehospital stroke scales, without changing the normal workflow. Primary outcome is the clinical diagnosis of an acute ischaemic stroke with an intracranial LVO in the anterior circulation. Additional hospital data concerning the diagnosis and provided treatment will be collected by chart review. Logistic regression analysis will be performed, and performance of the prehospital stroke scales will be expressed as sensitivity, specificity and area under the receiver operator curve. Ethics and dissemination: The Institutional Review Board of the Erasmus MC University Medical Centre has reviewed the study protocol and confirmed that the Dutch Medical Research Involving Human Subjects Act (WMO) is not applicable. The findings of this study will be disseminated widely through peer-reviewed publications and conference presentations. The best performing scale, or the simplest scale in case of clinical equipoise, will be integrated in a decision model with other clinical characteristics and real-life driving times to improve prehospital triage of suspected stroke patients.

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