Prehospital Detection of Large Vessel Occlusion Stroke With EEG

van Stigt, Maritta N.; Groenendijk, Eva A.; van Meenen, Laura C.C.; van de Munckhof, Anita A.G.A.; Theunissen, Monique; Franschman, Gaby; Smeekes, Martin D.; van Grondelle, Joffry A.F.; Geuzebroek, Geertje; Siegers, Arjen; Visser, Marieke C.; van Schaik, Sander M.; Halkes, Patricia H.A.; Majoie, Charles B.L.M.; Roos, Yvo B.W.E.M.; Koelman, Johannes H.T.M.; Koopman, Miou S.; Marquering, Henk A.; Potters, Wouter V.; Coutinho, Jonathan M.

doi:10.1212/wnl.0000000000207831

Cited by 14 publications

(7 citation statements)

References 38 publications

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“…The ELECTRA-STROKE study 8 has enhanced our understanding of the feasibility and potential clinical utility of dry electrode EEG as a prehospital triage tool for identifying LVO in the anterior circulation in patients with suspected stroke.…”

Section: Discussionmentioning

confidence: 99%

“…ELECTRA-STROKE is a prospective, multicenter, nonrandomized, single-arm diagnostic Dutch study with blinded outcome assessment. 8-11 It is based on the concept that EEG is good in depicting neuronal changes caused by brain ischemia. 12 Previous studies have identified EEG patterns in stroke patients, emphasizing an increase in slow waves (theta, delta) and a decrease in fast waves (alpha, beta).…”

Section: Hypothesis and Study Designmentioning

confidence: 99%

“…This Journal Club article discusses the ELECTRA-STROKE study, 8 which assessed the diagnostic accuracy and feasibility of EEG as a potential simple prehospital tool for detecting anterior circulation LVO.…”

Section: Introductionmentioning

confidence: 99%

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Journal Club: Prehospital Detection of Large Vessel Occlusion Stroke With Electroencephalography

Peycheva,

Seiler,

Wagner

et al. 2024

Neurology

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The ELECTRA-STROKE study investigated the potential of EEG for prehospital triage of patients with ischemic stroke due to large vessel occlusion (LVO), in which fast triage to stroke centers for endovascular treatment is crucial. The study was conducted in 4 phases, and this Journal Club article focuses on the fourth phase in the prehospital setting with suspected stroke patients. An EEG cap with dry electrodes was used to measure brain activity. The main focus was on the diagnostic accuracy of the theta/alpha ratio, which yielded an area under the receiver operator characteristic curve (AUC) of 0.80. Secondary endpoints, particularly the Brain Symmetry Index (a quantified EEG interhemispheric cortical power asymmetry index) in the delta frequency band, showed an AUC of 0.91. Despite the convenient study design and userfriendly EEG device, limitations include a single-arm design, a relatively small sample size, and exclusions due to data quality issues. The usefulness of EEG in the detection of neuronal changes based on brain ischemia was highlighted, but uncertainties remain regarding its use in certain patient groups. The improvements in the Brain Symmetry Index from phase 3 to 4 of the study indicate the potential for further refinement and investigation of combined methods to improve diagnostic accuracy. The study provides insight into the role of EEG in prehospital stroke detection, recognizing both the strengths and limitations. Overall, the study contributes to understanding the promise of EEG in optimizing LVO stroke triage and urges further refinement and exploration of complementary diagnostic approaches.

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Section: Discussionmentioning

confidence: 99%

Section: Hypothesis and Study Designmentioning

confidence: 99%

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Journal Club: Prehospital Detection of Large Vessel Occlusion Stroke With Electroencephalography

Peycheva,

Seiler,

Wagner

et al. 2024

Neurology

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“…Both of these are attractive options due to their inherent portability, low-cost, and potential discriminatory ability to differentiate stroke syndromes. One study demonstrated an EEG cap during ambulance transportation can accurately differentiate LVO stroke, reporting a diagnostic accuracy of 91% and a positive likelihood ratio of 11.0 ( 41 ). Another study investigating a portable, automated TCD device and found the overall accuracy of LVO detection was 91% when combining two biomarkers.…”

Section: Future State: Artificial Intelligence To Enhance Prehospital...mentioning

confidence: 99%

Artificial intelligence to enhance prehospital stroke diagnosis and triage: a perspective

Wolcott,

English

2024

Front. Neurol.

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As health systems organize to deliver the highest quality stroke care to their patients, there is increasing emphasis being placed on prehospital stroke recognition, accurate diagnosis, and efficient triage to improve outcomes after stroke. Emergency medical services (EMS) personnel currently rely heavily on dispatch accuracy, stroke screening tools, bypass protocols and prehospital notification to care for patients with suspected stroke, but novel tools including mobile stroke units and telemedicine-enabled ambulances are already changing the landscape of prehospital stroke care. Herein, the authors provide our perspective on the current state of prehospital stroke diagnosis and triage including several of these emerging trends. Then, we provide commentary to highlight potential artificial intelligence (AI) applications to improve stroke detection, improve accurate and timely dispatch, enhance EMS training and performance, and develop novel stroke diagnostic tools for prehospital use.

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“…16,17 Transcranial Doppler, volumetric impedance phase shift spectroscopy (VIPS), and electroencephalography (EEG) have been studied to this end with varying degrees of diagnostic accuracy. 18–21 Lastly, in addition to performance metrics, it is important to consider cost, size, efficiency, and ease of use in the pre-hospital setting. 22…”

Section: Introductionmentioning

confidence: 99%

Portable Cerebral Blood Flow Monitor to Detect Large Vessel Occlusion in Suspected Stroke Patients

Favilla,

Baird,

Grama

et al. 2023

Preprint

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BackgroundEarly detection of large vessel occlusion (LVO) facilitates triage to a comprehensive or thrombectomy-capable stroke center to reduce treatment times and improve outcomes. Prehospital stroke scales, however, are not sufficiently sensitive, so here we investigate the ability of the portable Openwater optical blood flow monitor to detect LVO in patients undergoing acute stroke evaluation.MethodsPatients were prospectively enrolled at two comprehensive stroke centers during acute stroke evaluation within 24 hours of symptom onset with NIHSS ≥2. Each patient underwent a 60-second bedside optical blood flow evaluation with the Openwater instrument. The Openwater instrument generates cerebral blood flow waveforms based on relative changes in speckle contrast. Anterior circulation LVO was deteremined based on CT angiographic imaging and defined as occlusion of the ICA, or first/second segment of the MCA. A deep learning model, based on a transformer architecture trained on all patient data using fivefold cross-validation and learned discriminative representations from the raw speckle contrast waveform data. ROC analysis compared the Openwater diagnostic performance (i.e., LVO detection) with performance of prehospital stroke scales.ResultsAmongst 135 patients, the median NIHSS was 8 (IQR: 4-14), and 52 (39%) had an anterior circulation LVO based on CT angiogram. The Openwater instrument had 79% sensitivity and 84% specificity for the detection of LVO. The RACE scale had 60% sensitivity and 81% specificity. LAMS had 50% sensitivity and 81% specificity. In the ROC analysis, the binary Openwater classification (high-likelihood vs low-likelihood) had an AUC of 0.82 (95%CI: 0.75-0.88), which outperformed RACE (AUC: 0.70; 95%CI: 0.62-0.78; p=0.04) and LAMS (AUC: 0.65; 95% CI: 0.57-0.73; p=0.002).ConclusionsThe Openwater optical blood flow monitor outperformed prehospital stroke scales for the detection of LVO in patients who presented to the Emergency Department for acute stroke evaluation. These encouraging findings need to be validated in the prehospital environment.

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Prehospital Detection of Large Vessel Occlusion Stroke With EEG

Cited by 14 publications

References 38 publications

Journal Club: Prehospital Detection of Large Vessel Occlusion Stroke With Electroencephalography

Journal Club: Prehospital Detection of Large Vessel Occlusion Stroke With Electroencephalography

Artificial intelligence to enhance prehospital stroke diagnosis and triage: a perspective

Portable Cerebral Blood Flow Monitor to Detect Large Vessel Occlusion in Suspected Stroke Patients

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