Outcome-Blind EEG Microstate Topography After Cardiac Arrest: Spatial Expression of a Lateralized Microstate and Association with Neurological Outcome
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Updated: Nov 1, 2026

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
1Department of Clinical Neurophysiology, Institute of Neurology and Neurosurgery, 29 y D, Vedado, Havana, 10400, Cuba. cmachado_2000@yahoo.com.
Abstract:
Electroencephalography (EEG) is central to neurological assessment after cardiac arrest, yet conventional approaches predominantly characterize amplitude, frequency content, continuity, suppression, reactivity, or predefined pathological patterns. EEG microstates provide a complementary framework by describing quasi-stable configurations of the global scalp electric field. We investigated whether an outcome-blind microstate decomposition of EEG from comatose survivors of cardiac arrest identifies reproducible spatial states associated with neurological outcome. We performed a secondary analysis of the multicenter I-CARE/PhysioNet database. Following prespecified EEG screening requiring continuous 19-channel recordings of at least 300 s, 567 subjects were included (34 excluded at preflight). Microstate reconstruction was performed outcome-blind using a fixed 300-s continuous baseline analysis window, GFP-peak sampling capped at 500 peaks per patient, and polarity-invariant clustering across K = 2-10. After model-order evaluation, the K = 4 solution was frozen and backfitted at the patient level. Associations between microstate metrics and neurological outcome were evaluated using unadjusted, multivariable, dose-response, ROC discrimination, and extensive resampling analyses. The primary outcome analysis included 567 patients: 209 with favorable (CPC 1-2) and 358 with unfavorable (CPC 3-5) neurological outcomes. M2 global explained variance (GEV) was higher in patients with favorable outcome (median 0.0852 vs. 0.0564; rank-biserial correlation = 0.185; p = 0.000243; false-discovery-rate [FDR]-adjusted p = 0.000568 within the four-state GEV family). M2 GEV was inversely associated with CPC severity (Spearman rho = -0.144; p = 0.000583; FDR-adjusted p = 0.001419). Standalone ROC analysis yielded an AUC of 0.59 (95% CI 0.54-0.64). After adjustment for age, sex, and shockable rhythm in the extended cohort without return-of-spontaneous-circulation (ROSC) time (N = 535), each 1-SD increase in M2 GEV was associated with greater odds of favorable outcome (OR 1.30, 95% CI 1.07-1.58; p = 0.0092). In the complete-case model additionally adjusted for ROSC time (N = 292), the association remained significant (OR 1.47, 95% CI 1.10-1.97; p = 0.0087). A graded association was observed across M2 GEV quartiles without evidence of nonlinearity. Results remained directionally stable under winsorization, exclusion of distributional extremes, heteroscedasticity-consistent standard errors, bootstrap resampling, leave-one-out analysis, repeated leave-five-out perturbations, and accounting for recording-center clustering. By contrast, M2 coverage, mean duration, and occurrence were not significantly associated with outcome after multiplicity correction. An outcome-blind decomposition of EEG after cardiac arrest identified a frozen microstate, M2, whose GEV was reproducibly associated with neurological outcome. The prognostic information associated with M2 was related primarily to the degree to which this spatial configuration explained the global EEG field rather than to its conventional temporal parameters. EEG microstate architecture may provide a complementary description of residual large-scale electrophysiological organization after hypoxic-ischemic brain injury. Rather than functioning as a standalone prognostic test, M2 GEV reflects residual spatial organization that complements established clinical and background EEG markers.
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