Abstract
OBJECTIVE: Cognitive motor dissociation (CMD) is associated with long-term recovery in acute brain injury, but CMD testing is only available in few centers. Our objective was to identify surface EEG patterns with high sensitivity or positive predictive value (PPV) for CMD in patients with acute disorders of consciousness to refine allocation of this resource-intensive test. METHODS: In this observational cohort study, we enrolled clinically unresponsive, acutely brain injured patients who underwent continuous surface EEG and CMD assessments. CMD was detected by applying a machine learning algorithm to EEG acquired during a motor command paradigm presentation.Electroencephalographers blinded to CMD test results applied standardized ACNS criteria to the EEGs acquired during CMD assessments. We calculated accuracy measures of surface EEG findings for CMD test results using generalized estimating equations, with an exchangeable matrix and accounting for repeated measures per patient. RESULTS: We included 185 patients (mean age: 62 ± 17; 85 [46%] female) and 282 CMD assessments. CMD testing was positive in 39 (14%) assessments. Sensitivity and PPV of normal background voltage, symmetry and continuity were respectively 77% (95%-CI: 60-88%) and 19% (95%-CI: 13-26%), 74% (95%-CI: 58-86%) and 14% (95%-CI: 10-20%), and 74% (95%-CI: 58-86%) and 14% (95%-CI: 9-19%). All EEGs with burst suppression, suppression, sporadic epileptiform discharges, lateralized periodic discharges, bilateral independent periodic discharges, electrographic seizures and brief potentially ictal rhythmic discharges had negative CMD tests. INTERPRETATION: Surface EEG findings are not reliable to screen for CMD or to identify patterns conferring higher CMD pretest probability.