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Acta Neurol Scand ; 136(1): 17-23, 2017 Jul.
Article in English | MEDLINE | ID: mdl-27642014

ABSTRACT

OBJECTIVES: Blood-based biomarkers could enable early and cost-effective diagnostics for acute stroke patients in the prehospital setting to support early initiation of treatments. To facilitate development of ultra-acute biomarkers, we set out to implement large-scale prehospital blood sampling and determine feasibility and diagnostic timesavings of this approach. MATERIALS AND METHODS: Emergency medical services (EMS) personnel of the Helsinki metropolitan area were trained to collect prehospital blood samples from thrombolysis candidates using a cannula adapter technique. Time delays, sample quality, and logistics were investigated between May 20, 2013 and May 19, 2014. RESULTS: Prehospital blood sampling and study recruiting were successfully performed for 430 thrombolysis candidates, of which 50% had ischemic stroke, 14.4% TIA, 13.5% hemorrhagic stroke, and 22.1% stroke mimics. A total of 66.3% of all samples were collected during non-office hours. The median (interquartile range) emergency call to prehospital sample time was 33 minutes (25-41), and the median time from reported symptom onset or wake-up to prehospital sample was 53 minutes (38-85; n=394). Prehospital sampling was performed 31 minutes (25-42) earlier than hospital admission blood sampling and 37 minutes (30-47) earlier than admission neuroimaging. Hemolysis rate in serum and plasma samples was 6.5% and 9.3% for EMS samples, and 0.7% and 1.6% for admission samples. CONCLUSIONS: Prehospital biomarker sampling can be implemented in all EMS units and provides a median timesaving of more than 30 minutes to first blood sample. Large prehospital sample sets will enable development of novel ambulance biomarkers to improve early differential diagnosis and treatment of thrombolysis candidates.


Subject(s)
Emergency Medical Services/methods , Stroke/blood , Aged , Biomarkers/blood , Early Diagnosis , Female , Hemolysis , Humans , Male , Middle Aged , Stroke/pathology , Time Factors
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