PP14 Development of a prehospital assessment to identify stroke mimic conditions

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BackgroundDespite routine use of pre-hospital identification instruments, approximately 30% of suspected stroke admissions are stroke mimics (SM). Early identification may allow “false positive” SM patients to be directed to appropriate care and improve healthcare resource utilisation.MethodsA retrospective database of ambulance records containing a paramedic impression of stroke was linked to hospital specialist diagnosis data from 01/06/13 to 31/05/16. Logistic regression identified clinical features predictive of SM. An assessment score was constructed prioritising specificity over sensitivity.Results1650 patients (mean age 75.3, 47% male, 40% SM) were included. 1520 (92%) were Face Arm Speech Test (FAST) positive. Table 1 describes the characteristics in the SM assessment. Each characteristic scores 1 point if present.86% (66/77) of suspected stroke patients scoring 1 were SM. 100% (6/6) of patients scoring >1 characteristic were SM. A score ≥1 identified SM with 11% (95% CI, 8–13) sensitivity, 99% (95% CI, 98–99) specificity, positive predictive value of 87% (95% CI, 79–94), negative predictive value of 62% (95% CI, 60–64) and a diagnostic odds ratio of 11 (95% CI, 6–20, p<0.0001).ConclusionsAmongst ambulance patients with suspected stroke, a small number of SM can be identified with a high degree of certainty. This simple tool needs further validation, prospective testing in the pre-hospital environment with characteristics systematically recorded and consideration of potential clinical impact.

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