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Observational Study
. 2019 Jan;130(1):55-60.
doi: 10.1016/j.clinph.2018.11.003. Epub 2018 Nov 16.

Electroencephalogram dynamics during general anesthesia predict the later incidence and duration of burst-suppression during cardiopulmonary bypass

Affiliations
Observational Study

Electroencephalogram dynamics during general anesthesia predict the later incidence and duration of burst-suppression during cardiopulmonary bypass

George S Plummer et al. Clin Neurophysiol. 2019 Jan.

Abstract

Objective: Electroencephalogram burst-suppression during general anesthesia is associated with post-operative delirium (POD). Whether burst-suppression causes POD or merely reflects susceptibility to POD is unclear. We hypothesized decreased intraoperative alpha (8-12 Hz) and beta (13-33 Hz) power prior to the occurrence of burst-suppression in susceptible patients.

Methods: We analyzed intraoperative electroencephalogram data of cardiac surgical patients undergoing cardiopulmonary bypass (CPB). We detected the incidence and duration of CPB burst-suppression with an automated burst-suppression detection algorithm. We analyzed EEG data with multitaper spectral estimation methods. We assessed associations between patient characteristics and burst-suppression using Binomial and Zero-inflated Poisson Regression Models.

Results: We found significantly decreased alpha and beta power (7.8-22.95 Hz) in the CPB burst-suppression cohort. The odds ratio for the association between point estimates for alpha and beta power (7.8-22.95 Hz) and the incidence of burst-suppression was 0.88 (95% CI: 0.79-0.98). The incidence rate ratio for the association between point estimates for power between the alpha and beta range and the duration of burst-suppression was 0.89 (95% CI: 0.84-0.93).

Conclusion: Decreased intra-operative power within the alpha and beta range was associated with susceptibility to burst-suppression during CPB.

Significance: This dynamic may be used to develop principled neurophysiological-based approaches to aid the preemptive identification and targeted care of POD vulnerable patients.

Keywords: Burst-suppression; EEG oscillations, alpha and beta oscillations; General anesthesia; Post-operative delirium.

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Conflict of interest statement

Conflict of Interest Statement

OA has received speaker’s honoraria from Masimo Corporation, and is listed as an inventor on pending patents on EEG monitoring that are assigned to Massachusetts General Hospital, some of which are assigned to Masimo Corporation. OA has received institutionally distributed royalties for these licensed patents. All other authors declare that no competing interests exist.

Figures

Figure 1.
Figure 1.
Spectral comparison of EEG obtained prior to the onset of CPB in the CPB Burst suppression versus CPB No Burst suppression cohorts. (A, B) Median frontal spectrograms of Burst suppression (n = 27) and No Burst suppression (n = 27) patient cohorts. (C) Overlay of median Burst suppression (red) and median No Burst suppression (black) frontal spectra. Bootstrapped median spectra are presented, and the shaded regions represent the 95% confidence interval for the uncertainty around each bootstrapped median spectrum. We observed differences in power between the spectra (No Burst suppression > Burst suppression: 7.8–22.95 Hz). Black line represents significantly different regions.

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