Poster Presentation Smart Strokes Annual Scientific Meeting 2025

Predictors of Hyperacute Intervention for Acute Stroke (#116)

Jordan Lee 1 , Jess Pyman 1 , Donna Rowley 1 , Rohan Grimley 1
  1. Sunshine Coast Hospital and Health Service, Brisbane, QUEENSLAND, Australia

Introduction: Code stroke alert systems are designed to facilitate efficient hyperacute interventions for acute stroke, but use significant resources. We aimed to determine signs and symptoms identified during emergency department (ED) code strokes at an Australian primary stroke centre which predict hyperacute intervention for ischaemic and haemorrhagic stroke.

Methods: All code stroke alerts for patients presenting to the ED between 19 September and 2 December 2024 were identified prospectively, using the ED tracking platform. Clinical data was extracted from medical records.

Result: Among 211 code stroke alerts, 90 had a final stroke diagnosis (73 ischaemic, 17 haemorrhagic). Twenty-four received reperfusion therapy and 7 received hyperacute antihypertensive management (positive predictive value of a code stroke for stroke was 42.6%; hyperacute intervention was 14.7%). Patients presenting with ipsilateral upper and lower limb weakness were more likely to undergo thrombolysis and/or endovascular clot retrieval (RR 3.07; 95%CI 1.17-8.04). The strongest predictors of urgent interventions were inattention (RR 5.58; 95%CI 2.83-11.02), aphasia (RR 5.46; 95%CI 2.49-12.00) and gaze deviation (RR 4.94; 95%CI 2.48-9.87). Predictors of haemorrhagic stroke were impaired ability to follow commands (RR 6.16; 95%CI 2.68-14.14), altered level of consciousness (RR 4.75; 95%CI 2.079-10.866) and disorientation (RR 4.12; 95%CI 1.70-10.00). Headache was correlated with stroke mimic (RR 0.87; 95%CI 0.63-1.19).

Conclusion: Identification of a select few clinical factors which predict need for hyperacute therapies will enable development of screening tools to improve the accuracy of code stroke calls.

Relevance to clinical practice or patient experience: Recognition of the clinical signs that are most weighted in the decision making process for hyperacute therapies can make initial assessment more succinct and targeted, ultimately reducing treatment delays.