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Objective: To test if prognostic performance is affected by prolonged targeted temperature management (TTM) in comatose out-of-hospital cardiac arrest patients using two recently proposed EEG pattern classification models., Methods: In this sub-study of the "Target Temperature Management for 48 vs. 24 hand Neurologic Outcome after Out-of-Hospital Cardiac Arrest: A Randomized Clinical Trial", EEGs of 20-30 min duration were collected 24 h and 48 h after reaching the target temperature of 33 ± 1 °C. We classified EEGs according to two EEG classification models by Westhall et al. ("highly malignant", "malignant" and "benign") and Hofmeijer et al. ("unfavorable", "intermediate" and "favorable"). We tested prognostic ability against 6 months functional outcome using the Cerebral Performance Category score., Results: We recorded EEGs in 120 patients at 24 h and in 44 patients at 48 h. We found no difference in specificities or sensitivities of the two models between the two TTM groups (all p-values >0.19) or in prognostication at 24 h compared to 48 h (all p-values >0.13), except for the presence of EEG reactivity favoring prognostication at 24 h (p < 0.001). Being classified in the "benign" or "favorable" category was strongly associated with good outcome with specificities of 100% (90-100) and 97% (85-100) for the Westhall and Hofmeijer models respectively., Conclusions: We found no difference in the prognostic performance of the two studied EEG classification models during prolonged TTM for 48 h compared to standard duration, nor between EEG classification performed at 24 h versus 48 h after reaching target temperature. The two models performed best in good outcome prediction., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objective: To assess inter-rater agreement on EEG-reactivity (EEG-R) in comatose patients and compare it with a quantitative method (QEEG-R)., Methods: Six 30-s stimulation epochs (noxious, visual and auditory) were performed during EEG on 19 neurosurgical and 11 cardiac arrest patients. Six experts analysed EEGs for reactivity using their habitual methods. QEEG-R was defined as present if ≥2/6 epochs were reactive (stimulation/rest power ratio exceeding noise level). Three-months patient outcome was assessed by the Cerebral Performance Category Score (CPC) dichotomized in good (1-2) or poor (3-5)., Results: Agreement among experts on overall EEG-R varied from 53% to 83% (κ: 0.05-0.64) and reached 100% (κ: 1) between two QEEG-R calculators. For the experts, absence of EEG-R yielded sensitivities for poor outcome between 40-85% and specificities between 20-90%, for QEEG-R sensitivity was 40% (CI: 23-68%) and specificity 100% (CI: 69-100%)., Conclusions: There is a large inter-rater variation among experts on EEG-R assessment in comatose patients. QEEG-R is a promising objective prognostic parameter with low inter-rater variation and a high specificity for prediction of poor outcome., Significance: Clinicians should be cautious when using the traditional, qualitative method, in particular in end-of-life decisions. Implementation of the quantitative method in clinical practice may improve reliability of reactivity assessments., (Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

EEG reactivity (EEG-R) is regarded as an important parameter in coma prognosis but knowledge is sparse on the nature of EEG changes due to different kinds of stimulation and their prognostic significance. EEG-R was quantified in a study of 39 comatose neurosurgical patients. Six 30-second standardized visual, auditory, and painful stimulations were applied. EEG-R in the delta, theta, alpha, and beta band was normalized in z-scores as the power of a stimulation epoch relative to average power of 6 resting epochs. Outcome measure was 3 months Glasgow Outcome Scale. Increase in EEG activity was related to poor outcome, was more common (13.4% of tests), and grew continuously during the 30-second stimulation epoch. Decrease in EEG activity was related to good outcome, was rarer (2.5%), and peaked around 15 seconds. Pain was the most provocative stimulation (20.4%) followed by sound (8.7%) and eye-opening (6.7%). Discrimination between good (n = 6) and poor (n = 33) outcome was best in the theta and alpha bands for pain stimulation in the first 10-20 seconds and for sound stimulation in the first 5 to 10 seconds, eye-opening did not discriminate. Increase in activity predicted poor outcome with a high specificity 100% (CI = 52%-100%) and a modest sensitivity of 39% (CI = 23%-58%). Decrease in activity predicted good outcome with a high specificity of 100% (CI = 87%-100%) and a modest sensitivity of 33% (CI = 6%-76%). This quantitative study reveals new knowledge about the nature of EEG-R, which contribute to the development of more reliable and objective clinical procedures for outcome prediction.