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Recent applications of quantitative electroencephalography in adult intensive care units: a comprehensive review
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Recent applications of quantitative electroencephalography in adult intensive care units: a comprehensive review
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Journal Article
Recent applications of quantitative electroencephalography in adult intensive care units: a comprehensive review
2022
Overview
Quantitative electroencephalography (qEEG) refers to the numerical analysis and/or visual transformations of raw electroencephalography (EEG) signals. Evaluation of qEEG in intensive care units (ICU) faces unique challenges that warrant investigation separate from those conducted in other settings. Additionally, the pathophysiology, management, and EEG patterns of critically ill conditions often significantly differ between adults and children. Thus, it is important to distinguish the literature on qEEGs specifically performed in adult ICUs. The aim of this review is to summarize the studies using qEEG for clinical evaluation of patients in adult ICUs performed over the past decade (since 2010), and to present the state of the art of these techniques. Overall, these studies have reported that qEEG can reveal important information faster than typically possible with traditional methods of reviewing the raw EEG only, with reasonable accuracy. However, it is crucial to emphasize that qEEG must be reviewed in conjunction with raw EEG and in context of understanding the patients’ clinical status. Because each qEEG panel only focuses on a few aspects of the entire EEG, different combinations of qEEG panels may be required for optimal analyses of each medical condition and individual patient. Currently in practical terms, qEEG can serve as a complementary, valuable tool for portions of the EEG that require more detailed review. Further multi-center collaborative studies are needed to ultimately develop standardized methods of employing qEEG that are generalizable across institutions. As qEEG techniques continue to advance, including those involving machine learning, qEEG will further benefit from algorithms specifically suited for ICUs.
Publisher
Springer Nature B.V
Subject
