Development of a prehospital assessment to identify stroke mimic conditions
McClelland, Graham
Rodgers, Helen Flynn, Darren Price, Christopher
Rodgers, Helen
Flynn, Darren
Price, Christopher
Citations
Altmetric:
Journal Title
Book Title
Publication Volume
Publication Issue
Publication Begin Page
Publication End Page
Publication Number of Pages
Collections
Abstract
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.
https://emj.bmj.com/content/34/10/e5.1
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
http://dx.doi.org/10.1136/emermed-2017-207114.14