Development of a prehospital assessment to identify stroke mimic conditions
dc.contributor.author | McClelland, Graham | |
dc.contributor.author | Rodgers, Helen | |
dc.contributor.author | Flynn, Darren | |
dc.contributor.author | Price, Christopher | |
dc.date.accessioned | 2019-09-23T13:55:54Z | |
dc.date.available | 2019-09-23T13:55:54Z | |
dc.date.issued | 2017-10 | |
dc.identifier.citation | McClelland, G. et al, 2017. Development of a prehospital assessment to identify stroke mimic conditions. Emergency Medicine Journal : EMJ, 34 (10), e5. | en_US |
dc.identifier.issn | 1472-0205 | |
dc.identifier.issn | 1472-0213 | |
dc.identifier.doi | 10.1136/emermed-2017-207114.14 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12417/273 | |
dc.description.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 | |
dc.language.iso | en | en_US |
dc.subject | Emergency Medical Services | en_US |
dc.subject | Pre-hospital | en_US |
dc.subject | Paramedics | en_US |
dc.subject | Symptom Assessment | en_US |
dc.subject | Stroke | en_US |
dc.title | Development of a prehospital assessment to identify stroke mimic conditions | en_US |
dc.type | Conference Paper/Proceeding/Abstract | |
dc.source.journaltitle | Emergency Medicine Journal | en_US |
dcterms.dateAccepted | 2019-08-21 | |
rioxxterms.version | NA | en_US |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_US |
rioxxterms.licenseref.startdate | 2019-08-21 | |
refterms.panel | Unspecified | en_US |
refterms.dateFirstOnline | 2017-10 | |
html.description.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 | en_US |