Perioperative, electroencephalographic characteristics of postoperative delirum in elderly

• Applicant: Dr. Susanne Koch
• Subject Area: Anaesthesiology ; Human Cognitive and Systems Neuroscience ; Cognitive, Systems and Behavioural Neurobiology
• Term: from 2018 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 409495393

Postoperative Delirium (POD) in elderly patients is the most common clinical manifestation of brain dysfunction following surgery. POD is associated with an increased length of hospital stay, higher mortality rate, as well as an impaired long-term cognitive function. Identifying individual predisposing factors and avoiding precipitating risk factors are essential for an effective POD prevention. However, until now there are no effective biomarkers to identify patients at higher risk for developing POD that may enable anesthesiologist to adapt the anesthetic procedure / medication and to prepone POD therapy options.Although EEG monitoring is the most feasible approach for tracking brain states under general anesthesia, nowadays solely a single EEG derived, Index (BIS-Index, Narcotrend Index, PSI Index) is used in routine anesthesiological practices not taking age and different anesthetic agents into account. Sophisticated spectral analysis of EEG data oscillation under general anesthesia are in the focus of current research projects analyzing the effect of different anesthetic agents and age groups during general anesthesia. Different anesthetics agents interact with different molecular targets and neural circuits to induce unconsciousness, subsequently inducing distinct intraoperative EEG signatures. The research group around Emery Brown has recently represented this by conducting spectral analysis of raw EEG files. This knowledge is critical, when aiming to identify perioperative EEG signatures in elderly patients at risk to develop POD. Interestingly, it has been proven that prolonged periods of deep anesthesia, as classified by visual analysis of the raw EEG identifying prolonged burst suppression epochs, are one of the main precipitating risk factors contributing to a higher incidence of POD. Additionally, EEG spectral analysis has recently been shown to be a valuable tool to monitor cognitive function in elderly patients with neurodegenerative diseases that could help predict conversion from mild cognitive impairment to dementia. Based on these results derived from more sophisticated analysis methods in EEG, we presume that patients at risk for developing POD can be identified perioperatively using specific EEG parameters / signatures. In the present study, we focus on biomarkers obtained from pre-, intra- and post-operative EEG recordings. We aim (1) to identify preoperative EEG markers indicating patients at risk to develop POD; (2) to specify intraoperative EEG signatures / states that are related to POD; and (3) to detect EEG signatures during stay in the recovery room that are directly related to POD, and may therefore be used as diagnostic tool. We want to improve postoperative, cognitive outcome in elderly patients, by identifying EEG based POD-Biomarkers, developed with more sophisticated, perioperative EEG data analysis methods, taking EEG dynamics related to age and different anesthetics agents into account.

• DFG Programme: Research Grants
• Co-Investigator: Professorin Dr. Claudia Spies