Predictors of Low Risk for Delirium during Anesthesia Emergence

Abstract

Background Processed EEG is used to monitor the level of anesthesia and it has shown the potential to predict the occurrence of delirium. While emergence trajectories of relative eeg band power identified post-hoc show promising results in predicting a risk for a delirium, they are not easily transferable into an online predictive application. In this article we describe a low-resource and easily applicable method to differentiate between patients at high risk and low risk for delirium, with patients at low risk expected to show decreasing eeg power during emergence. Methods We included data from 169 patients (median age: 61 [49, 73]), who underwent surgery with general anesthesia, maintained either with propofol, sevoflurane, or desflurane. The data were derived from a previously published study. We chose a single frontal channel and calculated the total and spectral band power from the EEG and calculated a linear regression model to observe the parameters’ change during anesthesia emergence, described as slope. The slope of total power and single band power was correlated with the occurrence of delirium. Results Of 169 patients, 32 (19%) showed delirium. We observed that patients whose total EEG power diminished the most during emergence were less likely to screen positive for delirium in the PACU. A positive slope in total power and band power evaluated by using a regression model was associated with a higher risk-ratio (total: RR 2.83 (95%CI: 1.46 to 5.51) alpha/beta band: RR 7.79 (95%CI: 2.24 to 27.09)) for delirium. Furthermore, a negative slope in multiple bands during emergence was specific for patients without delirium and allowed to define a test for patients at low risk. Conclusion In this study we developed an easily applicable exploratory method to analyze a single frontal EEG channel and to identify patterns specific for patients at low risk for delirium.

Intraoperative electroencephalogram patterns as predictors of postoperative delirium in older patients: a systematic review and meta-analysis

“…After careful reading of the full-text articles, 32 studies were excluded ( Supplementary Table S3 ). Ultimately, this systematic review included 19 studies published between 2015 and 2023 (Soehle et al, 2015 ; Fritz et al, 2016 ; Hesse et al, 2019 ; Momeni et al, 2019 ; Pedemonte et al, 2020 ; Jung et al, 2021 ; Koch et al, 2021 , 2023 ; Lele et al, 2022 ; Li et al, 2022 ; Lutz et al, 2022 ; Röhr et al, 2022 ; Windmann et al, 2022 ; Baron Shahaf et al, 2023 ; Dragovic et al, 2023 ; Khalifa et al, 2023 ; Kinoshita et al, 2023 ; Reese et al, 2023 ; Ostertag et al, 2024 ). Additionally, 10 of these articles were included in the meta-analysis (Soehle et al, 2015 ; Hesse et al, 2019 ; Pedemonte et al, 2020 ; Jung et al, 2021 ; Koch et al, 2021 , 2023 ; Lele et al, 2022 ; Lutz et al, 2022 ; Röhr et al, 2022 ; Ostertag et al, 2024 ).…”

Modulating delirium through stimulation (MoDeSt): study protocol for a randomized, double-blind, sham-controlled trial assessing the effect of postoperative transcranial electrical stimulation on delirium incidence

“…Research in the neuroanaesthetic field has extensively shown the critical association between POD and pre- (48), intra- (11,49) and postoperative (50-52) EEG power in the alpha band. Low intraoperative alpha power seems to reflect the EEG phenotype of a "vulnerable brain" (52,53).…”

Patient-centered precision care in anaesthesia – the PC-square (PC)2 approach

“…While specific EEG features are not directly linked to intraoperative awareness, certain observations are strongly associated with cognitive outcomes [ 31 , 32 ]. Notably, a robust alpha band power in the EEG positively correlates with adequate anaesthesia levels [ 31 , 33 ]. This alpha band power is also related to improved preoperative cognitive function and a decreased risk of postoperative delirium [ 32 ].…”