Literature DB >> 30964558

Prehospital stroke scales as screening tools for early identification of stroke and transient ischemic attack.

Zhivko Zhelev1, Greg Walker, Nicholas Henschke, Jonathan Fridhandler, Samuel Yip.   

Abstract

BACKGROUND: Rapid and accurate detection of stroke by paramedics or other emergency clinicians at the time of first contact is crucial for timely initiation of appropriate treatment. Several stroke recognition scales have been developed to support the initial triage. However, their accuracy remains uncertain and there is no agreement which of the scales perform better.
OBJECTIVES: To systematically identify and review the evidence pertaining to the test accuracy of validated stroke recognition scales, as used in a prehospital or emergency room (ER) setting to screen people suspected of having stroke. SEARCH
METHODS: We searched CENTRAL, MEDLINE (Ovid), Embase (Ovid) and the Science Citation Index to 30 January 2018. We handsearched the reference lists of all included studies and other relevant publications and contacted experts in the field to identify additional studies or unpublished data. SELECTION CRITERIA: We included studies evaluating the accuracy of stroke recognition scales used in a prehospital or ER setting to identify stroke and transient Ischemic attack (TIA) in people suspected of stroke. The scales had to be applied to actual people and the results compared to a final diagnosis of stroke or TIA. We excluded studies that applied scales to patient records; enrolled only screen-positive participants and without complete 2 × 2 data. DATA COLLECTION AND ANALYSIS: Two review authors independently conducted a two-stage screening of all publications identified by the searches, extracted data and assessed the methodologic quality of the included studies using a tailored version of QUADAS-2. A third review author acted as an arbiter. We recalculated study-level sensitivity and specificity with 95% confidence intervals (CI), and presented them in forest plots and in the receiver operating characteristics (ROC) space. When a sufficient number of studies reported the accuracy of the test in the same setting (prehospital or ER) and the level of heterogeneity was relatively low, we pooled the results using the bivariate random-effects model. We plotted the results in the summary ROC (SROC) space presenting an estimate point (mean sensitivity and specificity) with 95% CI and prediction regions. Because of the small number of studies, we did not conduct meta-regression to investigate between-study heterogeneity and the relative accuracy of the scales. Instead, we summarized the results in tables and diagrams, and presented our findings narratively. MAIN
RESULTS: We selected 23 studies for inclusion (22 journal articles and one conference abstract). We evaluated the following scales: Cincinnati Prehospital Stroke Scale (CPSS; 11 studies), Recognition of Stroke in the Emergency Room (ROSIER; eight studies), Face Arm Speech Time (FAST; five studies), Los Angeles Prehospital Stroke Scale (LAPSS; five studies), Melbourne Ambulance Stroke Scale (MASS; three studies), Ontario Prehospital Stroke Screening Tool (OPSST; one study), Medic Prehospital Assessment for Code Stroke (MedPACS; one study) and PreHospital Ambulance Stroke Test (PreHAST; one study). Nine studies compared the accuracy of two or more scales. We considered 12 studies at high risk of bias and one with applicability concerns in the patient selection domain; 14 at unclear risk of bias and one with applicability concerns in the reference standard domain; and the risk of bias in the flow and timing domain was high in one study and unclear in another 16.We pooled the results from five studies evaluating ROSIER in the ER and five studies evaluating LAPSS in a prehospital setting. The studies included in the meta-analysis of ROSIER were of relatively good methodologic quality and produced a summary sensitivity of 0.88 (95% CI 0.84 to 0.91), with the prediction interval ranging from approximately 0.75 to 0.95. This means that the test will miss on average 12% of people with stroke/TIA which, depending on the circumstances, could range from 5% to 25%. We could not obtain a reliable summary estimate of specificity due to extreme heterogeneity in study-level results. The summary sensitivity of LAPSS was 0.83 (95% CI 0.75 to 0.89) and summary specificity 0.93 (95% CI 0.88 to 0.96). However, we were uncertain in the validity of these results as four of the studies were at high and one at uncertain risk of bias. We did not report summary estimates for the rest of the scales, as the number of studies per test per setting was small, the risk of bias was high or uncertain, the results were highly heterogenous, or a combination of these.Studies comparing two or more scales in the same participants reported that ROSIER and FAST had similar accuracy when used in the ER. In the field, CPSS was more sensitive than MedPACS and LAPSS, but had similar sensitivity to that of MASS; and MASS was more sensitive than LAPSS. In contrast, MASS, ROSIER and MedPACS were more specific than CPSS; and the difference in the specificities of MASS and LAPSS was not statistically significant. AUTHORS'
CONCLUSIONS: In the field, CPSS had consistently the highest sensitivity and, therefore, should be preferred to other scales. Further evidence is needed to determine its absolute accuracy and whether alternatives scales, such as MASS and ROSIER, which might have comparable sensitivity but higher specificity, should be used instead, to achieve better overall accuracy. In the ER, ROSIER should be the test of choice, as it was evaluated in more studies than FAST and showed consistently high sensitivity. In a cohort of 100 people of whom 62 have stroke/TIA, the test will miss on average seven people with stroke/TIA (ranging from three to 16). We were unable to obtain an estimate of its summary specificity. Because of the small number of studies per test per setting, high risk of bias, substantial differences in study characteristics and large between-study heterogeneity, these findings should be treated as provisional hypotheses that need further verification in better-designed studies.

Entities:  

Mesh:

Year:  2019        PMID: 30964558      PMCID: PMC6455894          DOI: 10.1002/14651858.CD011427.pub2

Source DB:  PubMed          Journal:  Cochrane Database Syst Rev        ISSN: 1361-6137


  128 in total

1.  Rapid ambulance protocol for acute stroke.

Authors:  J Harbison; A Massey; L Barnett; D Hodge; G A Ford
Journal:  Lancet       Date:  1999-06-05       Impact factor: 79.321

Review 2.  Prehospital stroke scales in urban environments: a systematic review.

Authors:  Ethan S Brandler; Mohit Sharma; Richard H Sinert; Steven R Levine
Journal:  Neurology       Date:  2014-05-21       Impact factor: 9.910

3.  Predictive value of the Cincinnati Prehospital Stroke Scale for identifying thrombolytic candidates in acute ischemic stroke.

Authors:  Je Sung You; Sung Phil Chung; Hyun Soo Chung; Hye Sun Lee; Jong Woo Park; Hyun Jong Kim; Shin Ho Lee; Incheol Park; Hahn Shick Lee
Journal:  Am J Emerg Med       Date:  2013-09-20       Impact factor: 2.469

4.  Does use of the recognition of stroke in the emergency room stroke assessment tool enhance stroke recognition by ambulance clinicians?

Authors:  Rachael T Fothergill; Julia Williams; Melanie J Edwards; Ian T Russell; Patrick Gompertz
Journal:  Stroke       Date:  2013-09-26       Impact factor: 7.914

5.  Accuracy of stroke recognition by emergency medical dispatchers and paramedics--San Diego experience.

Authors:  Prasanthi Ramanujam; Kama Z Guluma; Edward M Castillo; Marcus Chacon; Matt B Jensen; Ekta Patel; William Linnick; James V Dunford
Journal:  Prehosp Emerg Care       Date:  2008 Jul-Sep       Impact factor: 3.077

6.  Dispatcher recognition of stroke using the National Academy Medical Priority Dispatch System.

Authors:  Brian H Buck; Sidney Starkman; Marc Eckstein; Chelsea S Kidwell; Jill Haines; Rainy Huang; Daniel Colby; Jeffrey L Saver
Journal:  Stroke       Date:  2009-04-23       Impact factor: 7.914

7.  Allen score in clinical diagnosis of intracranial hemorrhage.

Authors:  J A Huang; P Y Wang; M C Chang; L G Chia; D Y Yang; T C Wu
Journal:  Zhonghua Yi Xue Za Zhi (Taipei)       Date:  1994-12

8.  Accuracy of paramedic identification of stroke and transient ischemic attack in the field.

Authors:  W S Smith; M Isaacs; M D Corry
Journal:  Prehosp Emerg Care       Date:  1998 Jul-Sep       Impact factor: 3.077

9.  Validation of the use of the ROSIER scale in prehospital assessment of stroke.

Authors:  He Mingfeng; Wu Zhixin; Guo Qihong; Li Lianda; Yang Yanbin; Feng Jinfang
Journal:  Ann Indian Acad Neurol       Date:  2012-07       Impact factor: 1.383

10.  Prehospital stroke diagnostics based on neurological examination and transcranial ultrasound.

Authors:  Moriz Herzberg; Sandra Boy; Thilo Hölscher; Michael Ertl; Markus Zimmermann; Karl-Peter Ittner; Josef Pemmerl; Hendrik Pels; Ulrich Bogdahn; Felix Schlachetzki
Journal:  Crit Ultrasound J       Date:  2014-02-27
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  16 in total

1.  Prehospital stroke scales as screening tools for early identification of stroke and transient ischemic attack.

Authors:  Zhivko Zhelev; Greg Walker; Nicholas Henschke; Jonathan Fridhandler; Samuel Yip
Journal:  Cochrane Database Syst Rev       Date:  2019-04-09

Review 2.  Mobile Stroke Units: Bringing Treatment to the Patient.

Authors:  Mikel S Ehntholt; Melvin Parasram; Saad A Mir; Mackenzie P Lerario
Journal:  Curr Treat Options Neurol       Date:  2020-02-06       Impact factor: 3.598

3.  Machine Learning-Based Text Analysis to Predict Severely Injured Patients in Emergency Medical Dispatch: Model Development and Validation.

Authors:  Kuan-Chen Chin; Yu-Chia Cheng; Wen-Chu Chiang; Albert Y Chen; Jen-Tang Sun; Chih-Yen Ou; Chun-Hua Hu; Ming-Chi Tsai; Matthew Huei-Ming Ma
Journal:  J Med Internet Res       Date:  2022-06-10       Impact factor: 7.076

4.  Large-scale informatic analysis to algorithmically identify blood biomarkers of neurological damage.

Authors:  Grant C O'Connell; Megan L Alder; Christine G Smothers; Julia H C Chang
Journal:  Proc Natl Acad Sci U S A       Date:  2020-08-06       Impact factor: 11.205

5.  The role of the Cincinnati Prehospital Stroke Scale in the emergency department: evidence from a systematic review and meta-analysis.

Authors:  A De Luca; M Mariani; M T Riccardi; G Damiani
Journal:  Open Access Emerg Med       Date:  2019-07-17

6.  Differences in Characteristics and Ambulance Pathway Adherence Between Strokes and Mimics Presenting to a Large UK Centralized Hyper Acute Stroke Unit (HASU).

Authors:  Camilla Sammut-Powell; Christopher Ashton; Kyriaki Paroutoglou; Adrian Parry-Jones
Journal:  Front Neurol       Date:  2021-05-10       Impact factor: 4.003

7.  Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study.

Authors:  Sung Eun Lee; Mun Hee Choi; Hyo Jung Kang; Seong-Joon Lee; Jin Soo Lee; Yunhwan Lee; Ji Man Hong
Journal:  PLoS One       Date:  2020-04-15       Impact factor: 3.240

8.  Large Vessel Occlusion Identification Through Prehospital Administration of Stroke Scales: A County-wide Emergency Medical Services Prospective Research Protocol.

Authors:  Tej G Stead; Paul R Banerjee; Latha Ganti
Journal:  Cureus       Date:  2019-10-17

Review 9.  Extracellular Vesicles in Acute Stroke Diagnostics.

Authors:  Katrine Tang Stenz; Jesper Just; Rolf Ankerlund Blauenfeldt; Kim Ryun Drasbek
Journal:  Biomedicines       Date:  2020-07-28

10.  Predicting stroke severity with a 3-min recording from the Muse portable EEG system for rapid diagnosis of stroke.

Authors:  Cassandra M Wilkinson; Jennifer I Burrell; Jonathan W P Kuziek; Sibi Thirunavukkarasu; Brian H Buck; Kyle E Mathewson
Journal:  Sci Rep       Date:  2020-10-28       Impact factor: 4.379

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