External validation of stroke mimic prediction scales in the emergency department
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 inv...
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sg-ntu-dr.10356-1463082023-03-05T16:42:58Z External validation of stroke mimic prediction scales in the emergency department Tu, Tian Ming Tan, Guan Zhong Saffari, Seyed Ehsan Wee, Chee Keong Chee, David Jeremiah Ming Siang Tan, Camlyn Lim, Hoon Chin Lee Kong Chian School of Medicine (LKCMedicine) Science::Medicine Thrombolytic Therapy Clinical Decision-making 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. Published version 2021-02-08T08:58:44Z 2021-02-08T08:58:44Z 2020 Journal Article Tu, T. M., Tan, G. Z., Saffari, S. E., Wee, C. K., Chee, D. J. M. S., Tan, C., & Lim, H. C. (2020). External validation of stroke mimic prediction scales in the emergency department. BMC Neurology, 20(1), 269-. doi:10.1186/s12883-020-01846-6 1471-2377 0000-0002-7175-0357 https://hdl.handle.net/10356/146308 10.1186/s12883-020-01846-6 32635897 2-s2.0-85087675180 1 20 en BMC Neurology © 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. application/pdf |
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Science::Medicine Thrombolytic Therapy Clinical Decision-making Tu, Tian Ming Tan, Guan Zhong Saffari, Seyed Ehsan Wee, Chee Keong Chee, David Jeremiah Ming Siang Tan, Camlyn Lim, Hoon Chin External validation of stroke mimic prediction scales in the emergency department |
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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. |
author2 |
Lee Kong Chian School of Medicine (LKCMedicine) |
author_facet |
Lee Kong Chian School of Medicine (LKCMedicine) Tu, Tian Ming Tan, Guan Zhong Saffari, Seyed Ehsan Wee, Chee Keong Chee, David Jeremiah Ming Siang Tan, Camlyn Lim, Hoon Chin |
format |
Article |
author |
Tu, Tian Ming Tan, Guan Zhong Saffari, Seyed Ehsan Wee, Chee Keong Chee, David Jeremiah Ming Siang Tan, Camlyn Lim, Hoon Chin |
author_sort |
Tu, Tian Ming |
title |
External validation of stroke mimic prediction scales in the emergency department |
title_short |
External validation of stroke mimic prediction scales in the emergency department |
title_full |
External validation of stroke mimic prediction scales in the emergency department |
title_fullStr |
External validation of stroke mimic prediction scales in the emergency department |
title_full_unstemmed |
External validation of stroke mimic prediction scales in the emergency department |
title_sort |
external validation of stroke mimic prediction scales in the emergency department |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/146308 |
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1759853804230017024 |