Coma after cardiac arrest (CA) is an important cause of admission to the ICU. Prognosis of post-CA coma has significantly improved over the past decade, particularly because of aggressive postresuscitation care and the use of therapeutic targeted temperature management (TTM). TTM and sedatives used to maintain controlled cooling might delay neurologic reflexes and reduce the accuracy of clinical examination. In the early ICU phase, patients' good recovery may often be indistinguishable (based on neurologic examination alone) from patients who eventually will have a poor prognosis. Prognostication of post-CA coma, therefore, has evolved toward a multimodal approach that combines neurologic examination with EEG and evoked potentials. Blood biomarkers (eg, neuron-specific enolase [NSE] and soluble 100-β protein) are useful complements for coma prognostication; however, results vary among commercial laboratory assays, and applying one single cutoff level (eg, > 33 μg/L for NSE) for poor prognostication is not recommended. Neuroimaging, mainly diffusion MRI, is emerging as a promising tool for prognostication, but its precise role needs further study before it can be widely used. This multimodal approach might reduce false-positive rates of poor prognosis, thereby providing optimal prognostication of comatose CA survivors. The aim of this review is to summarize studies and the principal tools presently available for outcome prediction and to describe a practical approach to the multimodal prognostication of coma after CA, with a particular focus on neuromonitoring tools. We also propose an algorithm for the optimal use of such multimodal tools during the early ICU phase of post-CA coma.
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