Surface EEG to identify cognitive motor dissociation after acute brain injury
Egawa, S.; Casson, N.; Neves Briard, J.; Shen, Q.; Kansara, V.; Niesvizky-Kogan, I.; Carroll, E.; Carmona, J. C.; Song, Y. L.; Klein, A. J.; Velazquez, A.; Andres, W.; Ghoshal, S.; Roh, D.; Agarwal, S.; Park, S.; Connolly, E. S.; Claassen, J.
Show abstract
ObjectiveCognitive 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. MethodsIn 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. ResultsWe 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. InterpretationSurface EEG findings are not reliable to screen for CMD or to identify patterns conferring higher CMD pretest probability.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Cerebral microbleeds in critically ill patients with respiratory failure or sepsis: a scoping review 92%
- Clinical Consequences of Occult Free Valproate Toxicity in Critically Ill Adult Patients: A Multicenter Retrospective Cohort Study 91%
- Numerical Simulation of Concussive-generated Cortical Spreading Depolarization to Optimize DC-EEG Electrode Spacing for Non-invasive Visual Detection 90%
Similar papers in this journal
- Central and peripheral nervous system complications of COVID-19: A prospective tertiary center cohort with 3-month follow-up 93%
- Neural correlates of β-lactam exposure in intensive care unit patients: an observational, prospective cohort study 93%
- Predictors of acute ischemic cerebral lesions in immune-mediated thrombotic thrombocytopenic purpura and hemolytic uremic syndrome 89%
Similar papers in this journal
- Wavelet Phase Coherence of Ictal Scalp EEG-Extracted Muscle Activity (SMA) as a Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) 93%
- Alternating Hemiplegia Of Childhood: An Electroclinical Study Of Sleep And Hemiplegia 92%
- The use of carbogen for interruption of febrile seizures - the randomized controlled CARDIF trial 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.