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Evaluating the prognosis of comatose patients after cardiac arrest (CA) in the intensive care unit (ICU) remains challenging. It requires a multimodal approach combining standardized clinical examination, serum biomarkers, imaging and classically electrophysiological examinations, (among them auditive evoked potentials or AEP) but none has a sufficient sensitivity/specificity. In a preliminary study, the investigators developed an algorithm from the signal collected with AEP, and generated a probability map to visually classify the participants after the algorithm processing. Participants could be classified either with a good neurological prognosis or with bad neurological prognosis or death. The investigators hypothesize that the "PRECOM" tool, applied blindly to a large prospective multicenter cohort of patients admitted to intensive care for coma in the aftermath of CA will predict
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