Does Use of the Recognition Of Stroke In the Emergency Room stroke assessment tool enhance stroke recognition by ambulance clinicians

Rachael Fothergill, Julia Williams, Melanie Edwards, Ian Russell, Patrick Gompertz

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

Abstract

Background and Purpose—UK ambulance services assess patients with suspected stroke using the Face Arm Speech Test (FAST). The Recognition Of Stroke In the Emergency Room (ROSIER) tool has been shown superior to the FAST in identifying strokes in emergency departments but has not previously been tested in the ambulance setting. We investigated whether ROSIER use by ambulance clinicians can improve stroke recognition.
Methods—Ambulance clinicians used the ROSIER in place of the FAST to assess patients with suspected stroke. As the ROSIER includes all FAST elements, we calculated a FAST score from the ROSIER to enable comparisons between the two tools. Ambulance clinicians’ provisional stroke diagnoses using the ROSIER and calculated FAST were compared with stroke consultants’ diagnosis. We used stepwise logistic regression to compare the contribution of individual ROSIER and FAST items and patient demographics to the prediction of consultants’ diagnoses.
Results—Sixty-four percent of strokes and 78% of non strokes identified by ambulance clinicians using the ROSIER were subsequently confirmed by a stroke consultant. There was no difference in the proportion of strokes correctly detected by the ROSIER or FAST with both displaying excellent levels of sensitivity. The ROSIER detected marginally more non stroke cases than the FAST, but both demonstrated poor specificity. Facial weakness, arm weakness, seizure activity, age, and sex predicted consultants’ diagnosis of stroke.
Conclusions—The ROSIER was not better than the FAST for prehospital recognition of stroke. A revised version of the FAST incorporating assessment of seizure activity may improve stroke identification and decision making by ambulance clinicians.
Original languageEnglish
Pages (from-to)3007-3012
JournalStroke
Volume44
Issue number11
Early online date26 Sept 2013
DOIs
Publication statusPublished - Nov 2013

Keywords

  • Stroke
  • recognition
  • Ambulance Service

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