Background: Endovascular treatment was shown to drastically improve stroke patient outcomes but earlier identification of eligible patients is crucial. First responders are instrumental to the rapid identification and transportation of stroke patients to the nearest appropriate facility for acute stroke care especially when endovascular intervention is an option.
Purpose: To develop and evaluate the effectiveness of an algorithm for first responders to use to differentiate which stroke patients should be transported to the closest Interventional Stroke Center for treatment.
Method: We revised the County-Level Emergency Medical Services (EMS) protocol and algorithm to include the Rapid Arterial oCclusion Evaluation (RACE) scale in addition to the Cincinnati Prehospital Stroke Scale (CPPS). Together these simple in-the-field scales assess stroke severity and identify patients with acute stroke and large artery occlusion in a prehospital setting. Lucas County EMS staff received a four hour block of continuing education with credit on acute stroke, the updated protocol and algorithm, and use of the new RACE scale in addition to the CPPS. Effectiveness of the training and use of the RACE alert was measured by the percent of patients accurately identified with and without large artery occlusion.
Results: Training was provided to 450 EMS staff in several in-person sessions in June 2015. The RACE protocol went citywide on July first. Of the 18 patients brought in to our hospital by EMS in July using the RACE protocol, 72% were identified correctly using the tool. Of these, 6 were identified correctly as having large vessel occlusions and 7 were correctly identified as not having large vessel occlusions. The remaining 5 patients transported by EMS were identified as large vessel occlusions, but were not found to have strokes (seizures, intoxication, and conversion disorders).
Conclusion: Our data suggests that first responders can accurately differentiate between which stroke patients could benefit from endovascular treatment using a simple algorithm. Future evaluation could measure the relationship between accurate pre-hospital identification and treatment rates.