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Published in: BMC Neurology 1/2020

01-12-2020 | Migraine | Research article

External validation of stroke mimic prediction scales in the emergency department

Authors: Tian Ming Tu, Guan Zhong Tan, Seyed Ehsan Saffari, Chee Keong Wee, David Jeremiah Ming Siang Chee, Camlyn Tan, Hoon Chin Lim

Published in: BMC Neurology | Issue 1/2020

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Abstract

Background

Acute ischemic stroke is a time-sensitive emergency where accurate diagnosis is required promptly. Due to time pressures, stroke mimics who present with similar signs and symptoms as acute ischemic stroke, pose a diagnostic challenge to the emergency physician. With limited access to investigative tools, clinical prediction, tools based only on clinical features, may be useful to identify stroke mimics. We aim to externally validate the performance of 4 stroke mimic prediction scales, and derive a novel decision tree, to improve identification of stroke mimics.

Methods

We performed a retrospective cross-sectional study at a primary stroke centre, served by a telestroke hub. We included consecutive patients who were administered intravenous thrombolysis for suspected acute ischemic stroke from January 2015 to October 2017. Four stroke mimic prediction tools (FABS, simplified FABS, Telestroke Mimic Score and Khan Score) were rated simultaneously, using only clinical information prior to administration of thrombolysis. The final diagnosis was ascertained by an independent stroke neurologist. Area under receiver operating curve (AUROC) analysis was performed. A classification tree analysis was also conducted using variables which were found to be significant in the univariate analysis.

Results

Telestroke Mimic Score had the highest discrimination for stroke mimics among the 4 scores tested (AUROC = 0.75, 95% CI = 0.63–0.87). However, all 4 scores performed similarly (DeLong p > 0.05). Telestroke Mimic Score had the highest sensitivity (91.3%), while Khan score had the highest specificity (88.2%). All 4 scores had high positive predictive value (88.1 to 97.5%) and low negative predictive values (4.7 to 32.3%). A novel decision tree, using only age, presence of migraine and psychiatric history, had a higher prediction performance (AUROC = 0.80).

Conclusion

Four tested stroke mimic prediction scales performed similarly to identify stroke mimics in the emergency setting. A novel decision tree may improve the identification of stroke mimics.
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Metadata
Title
External validation of stroke mimic prediction scales in the emergency department
Authors
Tian Ming Tu
Guan Zhong Tan
Seyed Ehsan Saffari
Chee Keong Wee
David Jeremiah Ming Siang Chee
Camlyn Tan
Hoon Chin Lim
Publication date
01-12-2020
Publisher
BioMed Central
Keywords
Migraine
Stroke
Published in
BMC Neurology / Issue 1/2020
Electronic ISSN: 1471-2377
DOI
https://doi.org/10.1186/s12883-020-01846-6

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