Abstract TP255: Designing a Pre-Arrival Stroke Notification System

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Abstract

Introduction: Acute stroke pre-arrival notification by emergency medical services (EMS) allows hospital personnel to mobilize resources in advance, thereby improving treatment times and outcomes. However, criteria for pre-arrival notification vary by institution. In developing our own pre-arrival notification system, we aimed to determine whether objective measures, EMS clinical impression, or a combination of both best predicted accurate stroke team activation.

Methods: Retrospective review of consecutive patients presenting to our institution via EMS with suspicion of acute stroke from 2014-2015. Data recorded included age, gender, time of symptom onset, glucose, Cincinnati Prehospital Stroke Scale (CPSS), Glasgow Coma Scale (GCS), and EMS impression. Univariate logistic regression was performed with acute stroke team activation in the emergency department (ED) as the endpoint.

Results: 130 patients met inclusion criteria. Of these, 88 prompted the ED provider to activate the acute stroke team. Of variables analyzed, CPSS was clinically and statistically significant (OR. 1.7, 95% CI 1.2-2.5, p=0.0035) on univariate analysis, with arm weakness being the most predictive component (OR 2.9, 95% CI 1.04-8.1, p=0.04). EMS impression was not statistically significant (p>0.05). We then performed sensitivity and specificity analyses of CPSS, EMS impression, and CPSS combined with EMS impression (Table). A CPSS score of 3 had the highest specificity, and CPSS score of 1 combined with EMS impression the highest sensitivity.

Conclusion: CPSS was the key significant predictor of ED acute stroke team activation, and more specific than EMS clinical impression. By combining CPSS and EMS impression, sensitivity improved, but at the expense of specificity. This suggests that reproducible measurements and scores, such as CPSS, should be the main driver for stroke pre-notification systems and should be integrated systematically into EMS education programs.

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