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

Journal: Journal of neural engineering

PMID: 30703765

Abstract

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.

Authors

Ancor Sanz-García

Instituto de Investigación Sanitaria, Hospital de la Princesa, Madrid, España.
Miriam Pérez-Romero
Jesús Pastor
Rafael G Sola
Lorena Vega-Zelaya
Gema Vega
Fernando Monasterio
Carmen Torrecilla
Paloma Pulido
Guillermo J Ortega

Keywords

Adult Brain Injuries Cohort Studies Critical Care Dose-Response Relationship, Drug Electroencephalography Female Humans Hypnotics and Sedatives Infusions, Intravenous Intraoperative Neurophysiological Monitoring Machine Learning Male Midazolam Middle Aged Propofol Prospective Studies

External Resources

View on PubMed Access via DOI PubMed (30703765)

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

Abstract

Authors

Keywords

External Resources

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