Predictive Value of Preoperative Profiling of Serum Metabolites for Emergence Agitation After General Anesthesia in Adult Patients

• Published in: Frontiers in molecular biosciences Vol. 8; p. 739227
• Main Authors: Wang, Qian, Zhou, Jiansuo, Liu, Taotao, Yang, Ning, Mi, Xinning, Han, Dengyang, Han, Yongzheng, Chen, Lei, Liu, Kaixi, Zheng, Hongcai, Zhang, Jing, Lin, Xiaona, Li, Yitong, Hong, Jingshu, Li, Zhengqian, Guo, Xiangyang
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 21.10.2021
• Subjects: emergence agitation (EA); general anesthesia (GA); lipid metabolism; metabonomics; Molecular Biosciences; postoperative delirium (POD)
• ISSN: 2296-889X; 2296-889X
• DOI: 10.3389/fmolb.2021.739227

Background: Emergence agitation (EA) in adult patients under general anesthesia leads to increased postoperative complications and heavy medical burden. Unfortunately, its pathogenesis has not been clarified until now. The purpose of the present study was to explore the relationship between preoperative serum metabolites and EA. Methods: We used an untargeted metabolic analysis method to investigate the different metabolomes in the serum of EA patients and non-EA patients undergoing elective surgical procedures after the induction of general anesthesia. A Richmond Agitation–Sedation Scale score ≥ +2 was diagnosed as EA during postoperative emergence. Non-EA patients were matched with EA patients according to general characteristics. Preoperative serum samples of the two groups were collected to investigate the association between serum metabolites and EA development. Results: The serum samples of 16 EA patients with 34 matched non-EA patients were obtained for metabolic analysis. After screening and alignment with databases, 31 altered metabolites were detected between the two groups. These metabolites were mainly involved in the metabolism of lipids, purines, and amino acids. Analyses of receiver-operating characteristic curves showed that the preoperative alterations of choline, cytidine, glycerophosphocholine, L-phenylalanine, oleamide, and inosine may be associated with adult EA. Conclusion: Multiple metabolic abnormalities (including those for lipids, purines, and amino acids) and other pathological processes (e.g., neurotransmitter imbalance and oxidative stress) may contribute to EA. Several altered metabolites in serum before surgery may have predictive value for EA diagnosis. This study might afford new metabolic clues for the understanding of EA pathogenesis.