Potential EEG biomarkers of sedation doses in intensive care patients unveiled by using a machine learning approach.

OBJECTIVE: Sedation of neurocritically ill patients is one of the most challenging situation in ICUs. Quantitative knowledge on the sedation effect on brain activity in that complex scenario could help to uncover new markers for sedation assessment. Hence, we aim to evaluate the existence of changes of diverse EEG-derived measures in deeply-sedated (RASS-Richmond agitation-sedation scale -4 and -5) neurocritically ill patients, and also whether sedation doses are related with those eventual changes. APPROACH: We performed an observational prospective cohort study in the intensive care unit of the Hospital de la Princesa. Twenty-six adult patients suffered from traumatic brain injury and subarachnoid hemorrhage were included in the present study. Long-term continuous electroencephalographic (EEG) recordings (2141 h) and hourly annotated information were used to determine the relationship between intravenous sedation infusion doses and network and spectral EEG measures. To do that, two different strategies were followed: assessment of the statistical dependence between both variables using the Spearman correlation rank and by performing an automatic classification method based on a machine learning algorithm. MAIN RESULTS: More than 60% of patients presented a correlation greater than 0.5 in at least one of the calculated EEG measures with the sedation dose. The automatic classification method presented an accuracy of 84.3% in discriminating between different sedation doses. In both cases the nodes' degree was the most relevant measurement. SIGNIFICANCE: The results presented here provide evidences of brain activity changes during deep sedation linked to sedation doses. Particularly, the capability of network EEG-derived measures in discriminating between different sedation doses could be the framework for the development of accurate methods for sedation levels assessment.

Identifying causal relationships between EEG activity and intracranial pressure changes in neurocritical care patients.

OBJECTIVE: To explore and assess the relationship between electroencephalography (EEG) activity and intracranial pressure (ICP) in patients suffering from traumatic brain injury (TBI) and subarachnoid hemorrhage (SAH) during their stay in an intensive care unit. APPROACH: We performed an observational prospective cohort study of adult patients suffering from TBI or SAH. Continuous EEG-ECG was performed during ICP monitoring. In every patient, variables derived from the EEG were calculated and the Granger causality (GC) methodology was employed to assess whether, and in which direction, there is any relationship between EEG and ICP. MAIN RESULTS: One-thousand fifty-five hours of continuous multimodal monitoring were analyzed in 21 patients using the GC test. During 37.88% of the analyzed time, significant GC statistic was found in the direction from the EEG activity to the ICP, with typical lags of 25-50 s between them. When recordings were adjusted by sedation-perfusion and/or bolus-and handling, these percentages hardly changed. SIGNIFICANCE: Long-lasting, continuous and simultaneous EEG and ICP recordings from TBI and SAH patients provide highly rich and useful information, which has allowed for uncovering a strong relationship between both signals. The use of this relationship could lead to developing a medical device to measure ICP in a non-invasive way.