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Titel:

Always Assess the Raw Electroencephalogram: Why Automated Burst Suppression Detection May Not Detect All Episodes.

Dokumenttyp:
Article; Journal Article; Research Support, Non-U.S. Gov't
Autor(en):
Fleischmann, Antonia; Georgii, Marie-Therese; Schuessler, Jule; Schneider, Gerhard; Pilge, Stefanie; Kreuzer, Matthias
Abstract:
BACKGROUND: Electroencephalogram (EEG)-based monitors of anesthesia are used to assess patients' level of sedation and hypnosis as well as to detect burst suppression during surgery. One of these monitors, the Entropy module, uses an algorithm to calculate the burst suppression ratio (BSR) that reflects the percentage of suppressed EEG. Automated burst suppression detection monitors may not reliably detect this EEG pattern. Hence, we evaluated the detection accuracy of BSR and investigated the E...     »
Zeitschriftentitel:
Anesth Analg
Jahr:
2023
Band / Volume:
136
Heft / Issue:
2
Seitenangaben Beitrag:
346-354
Volltext / DOI:
doi:10.1213/ANE.0000000000006098
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/35653440
Print-ISSN:
0003-2999
TUM Einrichtung:
Klinik für Anästhesiologie (DHM)
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