Effect of topographic comparison of electroencephalographic microstates on the diagnosis and prognosis prediction of patients with prolonged disorders of consciousness

AimsThe electroencephalography (EEG) microstates are indicative of fundamental information processing mechanisms, which are severely damaged in patients with prolonged disorders of consciousness (pDoC). We aimed to improve the topographic analysis of EEG microstates and explore indicators available for diagnosis and prognosis prediction of patients with pDoC, which were still lacking.MethodsWe conducted EEG recordings on 59 patients with pDoC and 32 healthy controls. We refined the microstate method to accurately estimate topographical differences, and then classify and forecast the prognosis of patients with pDoC. An independent dataset was used to validate the conclusion.ResultsThrough optimized topographic analysis, the global explained variance (GEV) of microstate E increased significantly in groups with reduced levels of consciousness. However, its ability to classify the VS/UWS group was poor. In addition, the optimized GEV of microstate E exhibited a statistically significant decrease in the good prognosis group as opposed to the group with a poor prognosis. Furthermore, the optimized GEV of microstate E strongly predicted a patient's prognosis.ConclusionThis technique harmonizes with the existing microstate analysis and exhibits precise and comprehensive differences in microstate topography between groups. Furthermore, this method has significant potential for evaluating the clinical prognosis of pDoC patients. We improved the microstate method for measuring global explained variance (GEV), and the optimized GEV of microstate E strongly predicted the prognosis of patients with prolonged disorders of consciousness (pDoC).image