The following is a summary of “Subhairline Electroencephalography for the Detection of Large Vessel Occlusion Stroke,” published in the November 2023 issue of Cardiology by Groenendijk et al.

In the realm of stroke management, endovascular thrombectomy stands as the primary intervention for patients grappling with anterior circulation large vessel occlusion stroke (LVO‐a). Identifying such patients prior to hospitalization is critical in enabling their direct transfer to an endovascular thrombectomy-capable facility, consequently curtailing the time taken to undergo this intervention. While Electroencephalography (EEG) has shown promise in detecting LVO‐a strokes, ensuring swift and dependable electrode application remains a persistent challenge. Subhairline EEG emerges as a potential alternative in this scenario. Their study aimed to assess the diagnostic accuracy of subhairline EEG in detecting LVO‐a strokes.

For this investigation, the investigators enrolled adult patients suspected of having a stroke or confirmed with LVO‐a stroke, with symptom onset occurring within a 24-hour window. A single 3-minute EEG recording was conducted in the emergency department before endovascular thrombectomy, utilizing 9 self-adhesive electrodes placed on the forehead and behind the ears. Researchers scrutinized EEG features that quantified frequency band power and brain symmetry, particularly the pairwise derived Brain Symmetry Index, employing receiver operating characteristic analysis to ascertain their efficacy in detecting LVO‐a strokes. In their analysis, EEG data from 51 out of 52 patients (98%) were of sufficient quality for assessment. Among these patients, 16 (31%) presented with LVO‐a stroke, 16 (31%) with non‐LVO‐a ischemic stroke, 5 (10%) with transient ischemic attack, and 14 (27%) with a stroke mimic. The median duration from symptom onset to EEG recording was 266 minutes (interquartile range 130–709). Notably, the theta frequency band’s pairwise derived Brain Symmetry Index exhibited the highest diagnostic accuracy for identifying LVO‐a stroke (area under the receiver operating characteristic curve 0.90; sensitivity 86%; specificity 83%).

In conclusion, their findings underscore the potential of subhairline EEG in accurately detecting LVO‐a strokes, demonstrating robust data reliability. These results advocate for the consideration of subhairline EEG as a viable tool for prehospital stroke triage, facilitating more efficient and targeted interventions for LVO‐a stroke patients.

Source: ahajournals.org/doi/10.1161/JAHA.123.031929