Prehospital Detection of Large Vessel Occlusion Stroke With Electroencephalography: Results of the ELECTRA-STROKE Study

四分位间距 医学 冲程(发动机) 脑电图 闭塞 接收机工作特性 心脏病学 内科学 机械工程 精神科 工程类
作者
Maritta N. van Stigt,Eva A. Groenendijk,Laura C. C. van Meenen,Anita van de Munckhof,Monique Theunissen,Gaby Franschman,Martin Smeekes,Joffry A van Grondelle,Geertje Geuzebroek,Arjen Siegers,Marieke C. Visser,Sander M. Van Schaik,Patricia H.A. Halkes,Charles B. L. M. Majoie,Yvo B.W.E.M. Roos,Johannes H.M.T. Koelman,Miou S Koopman,Henk A. Marquering,Wouter V. Potters,Jonathan M. Coutinho
出处
期刊:Neurology [Ovid Technologies (Wolters Kluwer)]
卷期号:101 (24): e2522-e2532 被引量:3
标识
DOI:10.1212/wnl.0000000000207831
摘要

Background and Objectives Endovascular thrombectomy (EVT) is standard treatment for anterior large vessel occlusion stroke (LVO-a stroke). Prehospital diagnosis of LVO-a stroke would reduce time to EVT by allowing direct transportation to an EVT-capable hospital. We aim to evaluate the diagnostic accuracy of dry electrode EEG for the detection of LVO-a stroke in the prehospital setting. Methods ELECTRA-STROKE was an investigator-initiated, prospective, multicenter, diagnostic study, performed in the prehospital setting. Adult patients were eligible if they had suspected stroke (as assessed by the attending ambulance nurse) and symptom onset <24 hours. A single dry electrode EEG recording (8 electrodes) was performed by ambulance personnel. Primary endpoint was the diagnostic accuracy of the theta/alpha frequency ratio for LVO-a stroke (intracranial ICA, A1, M1, or proximal M2 occlusion) detection among patients with EEG data of sufficient quality, expressed as the area under the receiver operating characteristic curve (AUC). Secondary endpoints were diagnostic accuracies of other EEG features quantifying frequency band power and the pairwise derived Brain Symmetry Index. Neuroimaging was assessed by a neuroradiologist blinded to EEG results. Results Between August 2020 and September 2022, 311 patients were included. The median EEG duration time was 151 (interquartile range [IQR] 151–152) seconds. For 212/311 (68%) patients, EEG data were of sufficient quality for analysis. The median age was 74 (IQR 66–81) years, 90/212 (42%) were women, and the median baseline NIH Stroke Scale was 1 (IQR 0–4). Six (3%) patients had an LVO-a stroke, 109/212 (51%) had a non–LVO-a ischemic stroke, 32/212 (15%) had a transient ischemic attack, 8/212 (4%) had a hemorrhagic stroke, and 57/212 (27%) had a stroke mimic. AUC of the theta/alpha ratio was 0.80 (95% CI 0.58–1.00). Of the secondary endpoints, the pairwise derived Brain Symmetry Index in the delta frequency band had the highest diagnostic accuracy (AUC 0.91 [95% CI 0.73–1.00], sensitivity 80% [95% CI 38%–96%], specificity 93% [95% CI 88%–96%], positive likelihood ratio 11.0 [95% CI 5.5–21.7]). Discussion The data from this study suggest that dry electrode EEG has the potential to detect LVO-a stroke among patients with suspected stroke in the prehospital setting. Toward future implementation of EEG in prehospital stroke care, EEG data quality needs to be improved. Trial Registration Information ClinicalTrials.gov identifier: NCT03699397. Classification of Evidence This study provides Class II evidence that prehospital dry electrode scalp EEG accurately detects LVO-a stroke among patients with suspected acute stroke.
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