External validation of stroke mimic prediction scales in the emergency department

• Published in: BMC neurology Vol. 20; no. 1; pp. 1 - 269
• Main Authors: Tu, Tian Ming, Tan, Guan Zhong, Saffari, Seyed Ehsan, Wee, Chee Keong, Chee, David Jeremiah Ming Siang, Tan, Camlyn, Lim, Hoon Chin
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 07.07.2020; BioMed Central; BMC
• Subjects: Adults; Age; Clinical decision making; Decision making; Decision trees; Diagnosis; Emergency medical care; Headache; Hospital emergency services; Humans; Hypertension; Intravenous administration; Ischemia; Magnetic resonance imaging; Mental disorders; Migraine; Patients; Predictions; Predictive value of tests; Regression analysis; Stroke; Stroke/etiology; Thrombolysis; Thrombolytic therapy; Transient ischemic attack; Variables
• ISSN: 1471-2377; 1471-2377
• DOI: 10.1186/s12883-020-01846-6

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. Keywords: Thrombolytic therapy, Clinical decision-making, Predictive value of tests, Humans, Adults, Stroke/etiology, Tissue plasminogen activator