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A Dynamic Nomogram to Predict the Risk of Stroke in Emergency Department Patients With Acute Dizziness

OBJECTIVE: To develop a risk prediction tool for acute ischemic stroke (AIS) for patients presenting to the emergency department (ED) with acute dizziness/vertigo or imbalance. METHOD: A prospective, multicenter cohort study was designed, and adult patients presenting with dizziness/vertigo or imbal...

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Autores principales: Bi, Ying, Cao, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896851/
https://www.ncbi.nlm.nih.gov/pubmed/35250839
http://dx.doi.org/10.3389/fneur.2022.839042
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author Bi, Ying
Cao, Fei
author_facet Bi, Ying
Cao, Fei
author_sort Bi, Ying
collection PubMed
description OBJECTIVE: To develop a risk prediction tool for acute ischemic stroke (AIS) for patients presenting to the emergency department (ED) with acute dizziness/vertigo or imbalance. METHOD: A prospective, multicenter cohort study was designed, and adult patients presenting with dizziness/vertigo or imbalance within 14 days were consecutively enrolled from the EDs of 4 tertiary hospitals between August 10, 2020, and June 10, 2021. Stroke was diagnosed by CT or MRI performed within 14 days of symptom onset. Participants were followed-up for 30 days. The least absolute shrinkage and selection operator (LASSO) logistic regression analysis was conducted to extract predictive factors that best identified patients at high risk of stroke to establish a prediction model. Model discrimination and calibration were assessed and its prediction performance was compared with the age, blood pressure, clinical features, duration, and diabetes (ABCD2) score, nystagmus scheme, and finger to nose test. RESULTS: In this study, 790 out of 2,360 patients were enrolled {median age, 60.0 years [interquartile range (IQR), 51–68 years]; 354 (44.8%) men}, with complete follow-up data available. AIS was identified in 80 patients. An online web service tool (https://neuroby.shinyapps.io/dynnomapp/) was developed for stroke risk prediction, including the variables of sex, trigger, isolated symptom, nausea, history of brief dizziness, high blood pressure, finger to nose test, and tandem gait test. The model exhibited excellent discrimination with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.889 (95% CI: 0.855–0.923), compared with the ABCD2 score, nystagmus scheme, and finger to nose test [0.712 (95% CI, 0.652–0.771), 0.602 (95% CI, 0.556–0.648), and 61.7 (95% CI, 0.568–0.666) respectively]. CONCLUSION: Our new prediction model exhibited good performance and could be useful for stroke identification in patients presenting with dizziness, vertigo, or imbalance. Further externally validation study is needed to increase the strength of our findings.
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spelling pubmed-88968512022-03-05 A Dynamic Nomogram to Predict the Risk of Stroke in Emergency Department Patients With Acute Dizziness Bi, Ying Cao, Fei Front Neurol Neurology OBJECTIVE: To develop a risk prediction tool for acute ischemic stroke (AIS) for patients presenting to the emergency department (ED) with acute dizziness/vertigo or imbalance. METHOD: A prospective, multicenter cohort study was designed, and adult patients presenting with dizziness/vertigo or imbalance within 14 days were consecutively enrolled from the EDs of 4 tertiary hospitals between August 10, 2020, and June 10, 2021. Stroke was diagnosed by CT or MRI performed within 14 days of symptom onset. Participants were followed-up for 30 days. The least absolute shrinkage and selection operator (LASSO) logistic regression analysis was conducted to extract predictive factors that best identified patients at high risk of stroke to establish a prediction model. Model discrimination and calibration were assessed and its prediction performance was compared with the age, blood pressure, clinical features, duration, and diabetes (ABCD2) score, nystagmus scheme, and finger to nose test. RESULTS: In this study, 790 out of 2,360 patients were enrolled {median age, 60.0 years [interquartile range (IQR), 51–68 years]; 354 (44.8%) men}, with complete follow-up data available. AIS was identified in 80 patients. An online web service tool (https://neuroby.shinyapps.io/dynnomapp/) was developed for stroke risk prediction, including the variables of sex, trigger, isolated symptom, nausea, history of brief dizziness, high blood pressure, finger to nose test, and tandem gait test. The model exhibited excellent discrimination with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.889 (95% CI: 0.855–0.923), compared with the ABCD2 score, nystagmus scheme, and finger to nose test [0.712 (95% CI, 0.652–0.771), 0.602 (95% CI, 0.556–0.648), and 61.7 (95% CI, 0.568–0.666) respectively]. CONCLUSION: Our new prediction model exhibited good performance and could be useful for stroke identification in patients presenting with dizziness, vertigo, or imbalance. Further externally validation study is needed to increase the strength of our findings. Frontiers Media S.A. 2022-02-18 /pmc/articles/PMC8896851/ /pubmed/35250839 http://dx.doi.org/10.3389/fneur.2022.839042 Text en Copyright © 2022 Bi and Cao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Bi, Ying
Cao, Fei
A Dynamic Nomogram to Predict the Risk of Stroke in Emergency Department Patients With Acute Dizziness
title A Dynamic Nomogram to Predict the Risk of Stroke in Emergency Department Patients With Acute Dizziness
title_full A Dynamic Nomogram to Predict the Risk of Stroke in Emergency Department Patients With Acute Dizziness
title_fullStr A Dynamic Nomogram to Predict the Risk of Stroke in Emergency Department Patients With Acute Dizziness
title_full_unstemmed A Dynamic Nomogram to Predict the Risk of Stroke in Emergency Department Patients With Acute Dizziness
title_short A Dynamic Nomogram to Predict the Risk of Stroke in Emergency Department Patients With Acute Dizziness
title_sort dynamic nomogram to predict the risk of stroke in emergency department patients with acute dizziness
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896851/
https://www.ncbi.nlm.nih.gov/pubmed/35250839
http://dx.doi.org/10.3389/fneur.2022.839042
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