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PP14 Development of a prehospital assessment to identify stroke mimic conditions
  1. Graham McClelland1,
  2. Helen Rodgers2,
  3. Darren Flynn3,
  4. Chris Price2
  1. 1North East Ambulance Service NHS Foundation Trust and Newcastle University Stroke Research Group
  2. 2Newcastle University Stroke Research Group
  3. 3Newcastle University Institute of Health and Society


Background Despite 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.

Methods A 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.

Results 1650 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.

Table 1

Stroke mimic characteristics

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).

Conclusions Amongst 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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