Interrater Variability for the Identification of Anesthetic-induced Burst Suppression EEG

Burst suppression describes a specific EEG pattern that can generally indicate a too deep general anesthesia. The pathophysiology of anesthetic-induced Burst Suppression may be distinctly different from the pathophysiology of Burst Suppression from other medical causes (e.g., coma, hypothermia, intoxication). Definition criteria of neurologic societies cannot be applied to the classification of Burst Suppression during general anesthesia without adaptation. The lack of a clear definition complicates structured research on anesthetic-induced Burst Suppression EEG in the perioperative setting because of subjective bias. Therefore, a unified agreement on what anesthesia-induced Burst Suppression looks like is crucial to conduct the best possible research. The aim of this study is to formulate the basis for a clear definition of burst suppression EEG that may help to truly understand the significance of this EEG pattern and its relationship to proposed postoperative outcomes such as postoperative delirium, longterm postoperative neurocognitive disorders (PNDs) or increased mortality.

Intraoperative neuromonitoring is recommended to assess the level of general anesthesia. Additionally, specific intraoperative EEG patterns seem to be associated with PNDs. One of these EEG patterns is the burst suppression EEG. The pattern of waxing and waning activity has been associated with a higher risk factor for postoperative delirium. Commercial patient monitoring systems seem to underestimate the occurrence of Burst Suppression because the detection algorithms may not capture every suppression episode. A visual identification of this pattern is possible, but in the context of anesthesia monitoring, there is no standard definition of a Burst Suppression-EEG in the perioperative setting. Further, it displays unique clinical morphological characteristics. In particular, parameters of the EEG frequency spectrum are remarkably influenced by patients age and anesthetic agents. In order to agree on a definition for Burst Suppression during general anesthesia that will help to standardize Burst Suppression research and to optimize Burst Suppression monitoring, an expert consensus is essential. The planned project aims to pave the way to such a consensus of international expert societies in anesthesiology. Based on EEG data recorded within the framework of previous studies (approved Ethics application dated 20.08.2018 with number 246/18 S & 213/17S, dated 24.05.2017), the investigators will compose a representative data set (overall 50 EEG patterns) consisting of definitive Burst Suppression patterns (positive control), intraoperative EEG without Burst Suppression (negative control) and patterns that indicate different manifestations of a possible Burst Suppression-like pattern. The EEG recordings of this data set will be evaluated by selected international leading experts in EEG-based anesthesia monitoring. Therefore, a software environment (MATLAB) was developed, that allows the international experts to access the data set and score the traces pseudonymously. After the data sets have been scored, the interrater agreement for the single EEG episodes will be statistically analyzed.

Intraoperative EEG based monitoring, Burst Suppression, EEG-signal characteristics, intraoperative monitoring, general anesthesia

A software environment (MATLAB) was developed, that allows the international experts to access the data set and score the traces pseudonymously. This MATLAB-based interface shows 50 EEG traces. A representative dataset was composed, consisting of definite Burst Suppression patterns (positive control), intraoperative EEG without Burst Suppression patterns (negative control), and patterns indicating different manifestations of a possible Burst Suppression-like pattern.

MATLAB-based interface, showing 50 EEG traces, classification of the EEG-pattern as Burst Suppression possible, yes, no.

A software environment (MATLAB) was developed, that allows the international experts to access the data set and score the traces pseudonymously. This MATLAB-based interface shows 50 EEG traces. A representative dataset was composed, consisting of definite Burst Suppression patterns (positive control), intraoperative EEG without Burst Suppression patterns (negative control), and patterns indicating different manifestations of a possible Burst Suppression-like pattern.

To obtain expert knowledge that can help to introduce a clear definition of EEG features to identify anesthetic-induced Burst Suppression.

Investigation of spectral and time domain EEG features to assess objectively the individual raters scoring criteria.

Establishment of structures and working groups for the development of international definition criteria for Burst Suppression during general anesthesia.

International, validated definition criteria for Burst Suppression during general anesthesia (as a result of international expert knowledge).

Multi-stage coordination process; testing of the applicability in the subject-specific context and clinical routine.

Inclusion Criteria: leading international experts in the field of intraoperative EEG analysis Exclusion Criteria: members of study group