An updated review and meta-analysis of screening tools for stroke in the emergency room and prehospital setting

Published:September 26, 2022DOI:



      Stroke screening tools should have good diagnostic performance for early diagnosis and a proper therapeutic plan. This paper describes and compares various diagnostic tools used to identify stroke in emergency departments and prehospital setting.


      The meta-analysis was conducted according to the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines. The PubMed and Scopus databases were searched until December 31, 2021, for studies published on stroke screening tools. These tools' diagnostic performance (sensitivity and specificity) was pooled using a bivariate random-effects model whenever appropriate.


      Eleven screening tools for stroke were identified in 29 different studies. The various tools had a wide range of sensitivity and specificity in different studies. In the meta-analysis, the Cincinnati Pre-hospital Stroke Scale, Face Arm Speech Test, and Recognition of Stroke in the Emergency Room (ROSIER) had sensitivity (between 83 and 91%) but poor specificity (all below 64%). When comparing all the tools, ROSIER had the highest sensitivity 90.5%. Los Angeles Pre-hospital Stroke Screen performed best in terms of specificity 88.7% but had low sensitivity (73.9%). Melbourne Ambulance Stroke Screen had a balanced performance in terms of sensitivity (86%) and specificity (76%). Sensitivity analysis consisting of only prospective studies showed a similar range of sensitivity and specificity.


      All the stroke screening tools included in the review were comparable, but no clear superior screening tool could be identified. Simple screening tools like Cincinnati prehospital stroke scale (CPSS) have similar performance compared to more complex tools.


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        • Feigin V.L.
        • Norrving B.
        • Mensah G.A.
        Global burden of stroke.
        Circ. Res. 2017; 120: 439-448
        • Gorelick P.B.
        The global burden of stroke: persistent and disabling.
        Lancet Neurol. 2019; 18: 417-418
        • Kim J.T.
        • Fonarow G.C.
        • Smith E.E.
        • et al.
        Treatment with tissue plasminogen activator in the Golden hour and the shape of the 4.5-hour time-benefit curve in the National United States get with the Guidelines-Stroke Population.
        Circulation. 2017; 135: 128-139
        • Hand P.J.
        • Kwan J.
        • Lindley R.I.
        • Dennis M.S.
        • Wardlaw J.M.
        Distinguishing between stroke and mimic at the bedside: the brain attack study.
        Stroke. 2006; 37: 769-775
        • Kim S.J.
        • Kim D.W.
        • Kim H.Y.
        • Roh H.G.
        • Park J.J.
        Seizure in code stroke: stroke mimic and initial manifestation of stroke.
        Am. J. Emerg. Med. 2019; 37: 1871-1875
        • Bray J.E.
        • Martin J.
        • Cooper G.
        • Barger B.
        • Bernard S.
        • Bladin C.
        Paramedic identification of stroke: community validation of the Melbourne ambulance stroke screen.
        Cerebrovasc. Dis. 2005; 20: 28-33
        • Kothari R.
        • Hall K.
        • Brott T.
        • Broderick J.
        Early stroke recognition: developing an out-of-hospital NIH stroke scale.
        Acad. Emerg. Med. 1997; 4: 986-990
        • Kidwell C.S.
        • Saver J.L.
        • Schubert G.B.
        • Eckstein M.
        • Starkman S.
        Design and retrospective analysis of the Los Angeles prehospital stroke screen (LAPSS).
        Prehosp Emerg Care. 1998; 2: 267-273
        • R Development Core Team 3.0.1
        A Language and Environment for Statistical Computing.
        2. R Foundation for Statistical Computing, 2013
        • Freeman S.C.
        • Kerby C.R.
        • Patel A.
        • Cooper N.J.
        • Quinn T.
        • Sutton A.J.
        Development of an interactive web-based tool to conduct and interrogate meta-analysis of diagnostic test accuracy studies: MetaDTA.
        BMC Med. Res. Methodol. 2019; 19: 1-11
        • Patel A.
        • Cooper N.
        • Freeman S.
        • Sutton A.
        Graphical enhancements to summary receiver operating characteristic plots to facilitate the analysis and reporting of meta-analysis of diagnostic test accuracy data.
        Res. Synth. Methods. 2021; 12: 34-44
        • Asimos A.W.
        • Ward S.
        • Brice J.H.
        • Rosamond W.D.
        • Goldstein L.B.
        • Studnek J.
        Out-of-hospital stroke screen accuracy in a state with an emergency medical services protocol for routing patients to acute stroke centers.
        Ann. Emerg. Med. 2014; 64: 509-515
        • Bergs J.
        • Sabbe M.
        • Moons P.
        Prehospital stroke scales in a Belgian prehospital setting: a pilot study.
        Eur J Emerg Med. 2010; 17: 2-6
        • Bray J.E.
        • Coughlan K.
        • Barger B.
        • Bladin C.
        Paramedic diagnosis of stroke: examining long-term use of the Melbourne ambulance stroke screen (MASS) in the field.
        Stroke. 2010; 41: 1363-1366
        • English S.W.
        • Rabinstein A.A.
        • Mandrekar J.
        • Klaas J.P.
        Rethinking prehospital stroke notification: assessing utility of emergency medical services impression and Cincinnati prehospital stroke scale.
        J. Stroke Cerebrovasc. Dis. 2018; 27: 919-925
        • Frendl D.M.
        • Strauss D.G.
        • Underhill B.K.
        • Goldstein L.B.
        Lack of impact of paramedic training and use of the Cincinnati prehospital stroke scale on stroke patient identification and on-scene time.
        Stroke. 2009; 40: 754-756
        • Maddali A.
        • Razack F.A.
        • Cattamanchi S.
        • Ramakrishnan T.V.
        Validation of the Cincinnati prehospital stroke scale.
        J Emerg Trauma Shock. 2018; 11: 111-114
        • He M.
        • Wu Z.
        • Guo Q.
        • et al.
        Validation of the use of the ROSIER scale in prehospital assessment of stroke.
        Ann. Indian Acad. Neurol. 2012; 15: 191-195
        • He M.
        • Wu Z.
        • Zhou J.
        • et al.
        ROSIER scale is useful in an emergency medical service transfer protocol for acute stroke patients in primary care center: a southern China study.
        Neurol Asia. 2017; 22: 93-98
        • Purrucker J.C.
        • Hametner C.
        • Engelbrecht A.
        • Bruckner T.
        • Popp E.
        • Poli S.
        Comparison of stroke recognition and stroke severity scores for stroke detection in a single cohort.
        J. Neurol. Neurosurg. Psychiatry. 2015; 86: 1021-1028
        • Ramanujam P.
        • Guluma K.Z.
        • Castillo E.M.
        • et al.
        Accuracy of stroke recognition by emergency medical dispatchers and paramedics--San Diego experience.
        Prehosp Emerg Care. 2008; 12: 307-313
        • Saberian P.
        • Rafiemanesh H.
        • Heydari F.
        • Mirbaha S.
        • Karimi S.
        • Baratloo A.
        A multicenter diagnostic accuracy study on prehospital stroke screening scales.
        Arch Iran Med. 2021; 24: 453-460
        • Studnek J.R.
        • Asimos A.
        • Dodds J.
        • Swanson D.
        Assessing the validity of the Cincinnati prehospital stroke scale and the medic prehospital assessment for code stroke in an urban emergency medical services agency.
        Prehosp Emerg Care. 2013; 17: 348-353
        • Vanni S.
        • Polidori G.
        • Pepe G.
        • et al.
        Use of biomarkers in triage of patients with suspected stroke.
        J Emerg Med. 2011; 40: 499-505
        • Berglund A.
        • Svensson L.
        • Wahlgren N.
        • Von Euler M.
        Face arm speech time test use in the prehospital setting, better in the ambulance than in the emergency medical communication center.
        Cerebrovasc. Dis. 2014; 37: 212-216
        • Fothergill R.T.
        • Williams J.
        • Edwards M.J.
        • Russell I.T.
        • Gompertz P.
        Does use of the recognition of stroke in the emergency room stroke assessment tool enhance stroke recognition by ambulance clinicians?.
        Stroke. 2013; 44: 3007-3012
        • Lee S.
        • Seo J.S.
        • Lee S.C.
        • Lee J.H.
        • Doh H.H.
        Prospective evaluation of the recognition of stroke in the emergency room (ROSIER) scale in emergency department.
        Journal of the Korean society of emergency medicine. 2015; 26: 466-473
        • Whiteley W.N.
        • Wardlaw J.M.
        • Dennis M.S.
        • Sandercock P.A.G.
        Clinical scores for the identification of stroke and transient ischaemic attack in the emergency department: a cross-sectional study.
        J. Neurol. Neurosurg. Psychiatry. 2011; 82: 1006-1010
        • Kidwell C.S.
        • Saver J.L.
        • Schubert G.B.
        • Eckstein M.
        • Starkman S.
        Design and retrospective analysis of the Los Angeles prehospital stroke screen (LAPSS).
        Prehosp Emerg Care. 1998; 2: 267-273
        • Asimos A.W.
        • Johnson A.M.
        • Rosamond W.D.
        • et al.
        A multicenter evaluation of the ABCD2 Score’s accuracy for predicting early ischemic stroke in admitted patients with transient ischemic attack.
        Ann. Emerg. Med. 2010; 55: 201-210.e5
        • Chen S.
        • Sun H.
        • Lei Y.
        • et al.
        Validation of the Los Angeles pre-hospital stroke screen (LAPSS) in a Chinese urban emergency medical service population.
        PLoS One. 2013; 8e70742
        • Kidwell C.S.
        • Starkman S.
        • Eckstein M.
        • Weems K.
        • Saver J.L.
        Identifying stroke in the field. Prospective validation of the Los Angeles prehospital stroke screen (LAPSS).
        Stroke. 2000; 31: 71-76
        • Nor A.M.
        • Davis J.
        • Sen B.
        • et al.
        The recognition of stroke in the emergency room (ROSIER) scale: development and validation of a stroke recognition instrument.
        Lancet Neurol. 2005; 4: 727-734
        • Byrne B.
        • O’Halloran P.
        • Cardwell C.
        Accuracy of stroke diagnosis by registered nurses using the ROSIER tool compared to doctors using neurological assessment on a stroke unit: a prospective audit.
        Int. J. Nurs. Stud. 2011; 48: 979-985
        • Jackson A.
        • Deasy C.
        • Geary U.M.
        • Plunkett P.K.
        • Harbison J.
        Validation of the use of the ROSIER stroke recognition instrument in an Irish emergency department.
        Ir. J. Med. Sci. 2008; 177: 189-192
        • Jiang H.L.
        • Chan C.P.Y.
        • Leung Y.K.
        • Li Y.M.
        • Graham C.A.
        • Rainer T.H.
        Evaluation of the recognition of stroke in the emergency room (ROSIER) scale in Chinese patients in Hong Kong.
        PLoS One. 2014; 9e109762
        • Pickham D.
        • Valdez A.
        • Demeestere J.
        • et al.
        Prognostic value of BEFAST vs. FAST to identify stroke in a prehospital setting.
        Prehosp Emerg Care. 2019; 23: 195-200
        • Mao H.
        • Lin P.
        • Mo J.
        • et al.
        Development of a new stroke scale in an emergency setting.
        BMC Neurol. 2016; 16: 168
        • Dalvandi A.
        • Khankeh H.
        • Bahrampouri S.
        • et al.
        Designing Iranian pre-hospital stroke scale.
        Med. J. Islam Repub. Iran. 2014; 28: 118
        • Chenkin J.
        • Gladstone D.J.
        • Verbeek P.R.
        • et al.
        Predictive value of the Ontario prehospital stroke screening tool for the identification of patients with acute stroke.
        Prehospital Emergency Care. 2009; 13: 153-159
        • Andsberg G.
        • Esbjörnsson M.
        • Olofsson A.
        • Lindgren A.
        • Norrving B.
        • von Euler M.
        PreHospital ambulance stroke test - pilot study of a novel stroke test.
        Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine. 2017; 25: 37
        • Tarnutzer A.A.
        • Lee S.H.
        • Robinson K.A.
        • Wang Z.
        • Edlow J.A.
        • Newman-Toker D.E.
        ED misdiagnosis of cerebrovascular events in the era of modern neuroimaging: a meta-analysis.
        Neurology. 2017; 88: 1468-1477
        • Calic Z.
        • Cappelen-Smith C.
        • Anderson C.S.
        • Xuan W.
        • Cordato D.J.
        Cerebellar infarction and factors associated with delayed presentation and misdiagnosis.
        Cerebrovasc. Dis. 2016; 42: 476-484
        • Powers W.J.
        • Rabinstein A.A.
        • Ackerson T.
        • et al.
        2018 guidelines for the early Management of Patients with Acute Ischemic Stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association.
        Stroke. 2018; 49: e46-e110
        • Abedi V.
        • Khan A.
        • Chaudhary D.
        • et al.
        Using Artificial Intelligence for Improving Stroke Diagnosis in Emergency Departments: A Practical Framework.
        13. 2020: 1-8
        • Abedi V.
        • Goyal N.
        • Tsivgoulis G.
        • et al.
        Novel screening tool for stroke using artificial neural network.
        Stroke. 2017; 48: 1678-1681
        • Abedi V.
        • Misra D.
        • Chaudhary D.
        • et al.
        Abstract 27: predicting ischemic stroke in emergency departments: development and validation of machine learning models.
        Stroke. 2022; 53
        • Noorbakhsh-Sabet N.
        • Zand R.
        • Zhang Y.
        • Abedi V.
        Artificial intelligence transforms the future of health care.
        Am. J. Med. 2019; 132: 795-801