Brain monitoring after cardiac arrest

Purpose of reviewTo describe the available neuromonitoring tools in patients who are comatose after resuscitation from cardiac arrest because of hypoxic-ischemic brain injury (HIBI).Recent findingsElectroencephalogram (EEG) is useful for detecting seizures and guiding antiepileptic treatment. Moreover, specific EEG patterns accurately identify patients with irreversible HIBI. Cerebral blood flow (CBF) decreases in HIBI, and a greater decrease with no CBF recovery indicates poor outcome. The CBF autoregulation curve is narrowed and right-shifted in some HIBI patients, most of whom have poor outcome. Parameters derived from near-infrared spectroscopy (NIRS), intracranial pressure (ICP) and transcranial Doppler (TCD), together with brain tissue oxygenation, are under investigation as tools to optimize CBF in patients with HIBI and altered autoregulation. Blood levels of brain biomarkers and their trend over time are used to assess the severity of HIBI in both the research and clinical setting, and to predict the outcome of postcardiac arrest coma. Neuron-specific enolase (NSE) is recommended as a prognostic tool for HIBI in the current postresuscitation guidelines, but other potentially more accurate biomarkers, such as neurofilament light chain (NfL) are under investigation.Neuromonitoring provides essential information to detect complications, individualize treatment and predict prognosis in patients with HIBI.

Automated summary

The purpose of this review is to summarize the available neuromonitoring tools for comatose patients after resuscitation from hypoxic-ischemic brain injury (HIBI). Recent findings suggest that EEG is useful for detecting seizures and identifying irreversible HIBI. Cerebral blood flow (CBF) alterations, as well as near-infrared spectroscopy (NIRS), intracranial pressure (ICP), transcranial Doppler (TCD), and brain biomarkers, are being investigated to optimize CBF and assess the severity and prognosis of HIBI. Neuromonitoring plays a crucial role in detecting complications, personalizing treatment, and predicting outcomes in HIBI patients.