Evaluating the prognosis of comatose participants after cardiac arrest (CA) in the intensive care unit remains challenging. It requires a multimodal approach combining standardized clinical examination, serum biomarkers, imaging and classically electrophysiological examinations: 1 / the electroencephalogram, bad prognosis assessed when the electroencephalogram (EEG) is discontinuous, areactive, monotone,…), 2 / somesthetic evoked potentials, the absence of the N20 cortical wave has a specificity of poor prognosis of 68-100% and 3 / auditory evoked potentials (AEP), the presence of mismatchnegativity (MMN) would be of good prognosis with a specificity up to 90% but rarely performed in current practice. Routinely, these examinations are sometimes difficult to interpret in sedated participants, in an intensive care unit environment that generates numerous artefacts. Above all, all these techniques require the presence of a neurophysiology unit, with few experts available.~In a preliminary study, in collaboration with the applied mathematics laboratory of the ENS (Ecole Normale Supérieure), an algorithm was developed from the signal extracted from AEP. A probability map was generated with a software allowing to visually classify the participants after processing signal by the algorithm in a cluster of points with a high specificity into good neurological prognosis and bad neurological prognosis. Neither artifacts or sedation prevented data analysis.~The investigators hypothesize that the PRECOM tool, applied blindly to a large prospective multicenter cohort of participants admitted to intensive care for coma in the aftermath of a caridiac arrest will predict the neurological prognosis of participants with high sensitivity and specificity. This tool, carried out during the first week of the coma, will be compared to a standardized procedure used routinely by the participating resuscitators.
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 neurological prognosis at 3 months with high sensitivity and specificity.