University of Twente Student Theses
Subhairline Electroencephalography for the Detection of Large Vessel Occlusion Stroke
Groenendijk, E.A. (2022) Subhairline Electroencephalography for the Detection of Large Vessel Occlusion Stroke.
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| Full Text Status: | Access to this publication is restricted |
| Embargo date: | 1 January 2024 |
| Abstract: | Introduction: Endovascular thrombectomy for large vessel occlusion stroke of the anterior circulation (LVO-a) can only be performed in selected hospitals. A prehospital triage instrument which can reliably identify patients with an LVO-a stroke would enable direct routing of these patients to the right hospital and improve patient outcome. In this study, the diagnostic accuracy of subhairline electroencephalography (EEG) for LVO-a stroke was evaluated. Methods: An EEG recording was performed in 37 patients who were presented to the emergency department with a suspected stroke or known LVO-a stroke. Recordings were performed using 9 self-adhesive electrodes placed on the forehead and behind the ears. We evaluated the diagnostic accuracy of several EEG features for LVO-a stroke using receiver operating characteristic analysis. Optimal cut-off points were determined as the maximum sensitivity at a specificity of ≥ 80% for LVO-a stroke. Results: In total, 13/37 (35%) patients had an LVO-a stroke. Median onset-to-EEG-time was 250 (IQR 127–528) minutes. Highest diagnostic accuracy was obtained by the pairwise derived Brain Symmetry Index in the theta frequency band (AUC=0.88; sensitivity=85%; specificity=83%). Conclusion: Subhairline EEG is a promising method for detection of LVO-a stroke, but validation in a larger study population and the prehospital setting is necessary. |
| Item Type: | Essay (Master) |
| Faculty: | TNW: Science and Technology |
| Subject: | 44 medicine |
| Programme: | Technical Medicine MSc (60033) |
| Link to this item: | https://purl.utwente.nl/essays/93472 |
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