Study on the Characteristics of Non-targeted Metabolomics and EEG of Delayed Neurocognitive Recovery in Elderly Patients

Plain-language summary

Perioperative neurocognitive disorder (PND) refers to a broad range of postoperative cognitive complications, including preoperatively diagnosed cognitive decline, postoperative delirium (POD), delayed neurocognitive recovery (dNCR), and neurocognitive disorders . Among them, dNCR refers to a decline in cognitive function that occurs approximately 1-4 weeks after anesthesia/surgery in elderly patients. It is associated with an increased risk of postoperative complications and an increased length of hospital stay. The identification of potential predictive biomarkers would be beneficial for determining the individual risk of developing dNCR and for postoperative management of elderly patients. Although some predictive markers for PNDs, such as inflammatory factors, tau protein, S100B protein, neuron-specific enolase, and brain-derived neurotrophic factor, are widely known, most of them are postoperative predictive markers. The markers that can be used to predict PNDs before anesthesia/surgery are still largely unknown. Preoperative markers allow us to identify individuals who are susceptible to dNCR and intervene early. It is unclear whether the metabolic status of preoperative patients is related to the occurrence of postoperative cognitive dysfunction (POCD). In the framework of systems biology based on genome, transcriptome, proteome, and metabolome, metabolomics is the closest to biological phenotypes because it reflects biological events that have occurred in living organisms. Considering that metabolome reflects the metabolites of all biochemical reactions that have already taken place in an organism and contains a huge amount of information about an organism's health, preoperative patient metabolites may be a useful predictive biomarker. In this study, we used serum metabolomics to develop non-invasive, easily detectable, and inexpensive preoperative biomarkers from patient blood to determine the individual risk of dNCR and the relationship between metabolic system abnormalities and the pathogenesis of dNCR.

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