术后谵妄患者围术期脑电图特点的临床研究进展

Clinical Research Progress on the Characteristics of Perioperative Electroencephalogram in Patients with Postoperative Delirium

摘要: 术后谵妄作为手术患者常见的术后并发症，因可导致患者康复延迟、认知功能受损、住院费用攀升及死亡率升高等一系列不良后果，已成为临床医师重点关注的问题。脑电图作为一种兼具客观性与实用性的术中监测技术，能够通过量化数据直观反映特定患者群体的生理特征。近年来，围绕术后谵妄患者围术期脑电图特点的临床研究取得了快速发展，相关成果已成为医学领域的研究热点。本综述以该领域临床研究进展为核心，旨在系统梳理现有研究成果、深入分析当前面临的挑战，并对未来研究方向进行展望。研究通过系统检索中国知网、PubMed等权威数据库，筛选出近年发表的高质量相关文献，经深入分析与归纳后，重点综述了不同年龄、不同手术类型及围术期不同时间段患者的脑电图特征。研究结果显示，尽管脑电图监测在探索术后谵妄患者围术期特征方面已取得显著进展，但在以下方面仍存在挑战：一是与其他生物学标志物的关联性研究不足；二是深度机器学习算法在数据分析中的应用有待拓展；三是大规模多中心研究的开展仍需推进。

Abstract: Postoperative delirium, as a common postoperative complication for surgical patients, has become a key concern for clinicians due to a series of adverse consequences such as delayed recovery, impaired cognitive function, increased hospitalization costs and elevated mortality. Electroencephalogram (EEG), as an intraoperative monitoring technique that combines objectivity and practicality, can visually reflect the physiological characteristics of specific patient groups through quantitative data. In recent years, clinical research on the characteristics of perioperative electroencephalogram (EEG) in patients with postoperative delirium has developed rapidly, and the related achievements have become a research hotspot in the medical field. This review takes the clinical research progress in this field as its core, aiming to systematically sort out the existing research achievements, deeply analyze the current challenges, and look forward to the future research directions. The study conducted a systematic search of authoritative databases such as CNKI and PubMed, screened out high-quality relevant literature published in recent years, and after in-depth analysis and induction, focused on reviewing the electroencephalogram characteristics of patients of different ages, different surgical types, and different perioperative time periods. The research results show that although electroencephalogram (EEG) monitoring has made significant progress in exploring the perioperative characteristics of patients with postoperative delirium, there are still challenges in the following aspects: First, there is insufficient research on the association with other biological markers; Second, the application of deep machine learning algorithms in data analysis needs to be expanded. Third, the development of large-scale multi-center research still needs to be advanced.