Post resuscitation prognostication by EEG in 24 vs 48 h of targeted temperature management

Abstract

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.

Keywords: Cardiac arrest; Electroencephalography (EEG); Post-resuscitation care; Prognostication; Prolonged targeted temperature management; Targeted temperature management.