Department of Anesthesiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Tianjin 300060, China.
Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China.
J Healthc Eng. 2021 Apr 1;2021:5553029. doi: 10.1155/2021/5553029. eCollection 2021.
Postoperative cognitive dysfunction (POCD) refers to the complications of the central nervous system before and after surgery in patients without mental disorders. Many studies have shown that surgical anesthesia may cause POCD, especially in elderly patients. This article aims to study the relationship between artificial intelligence-based general anesthetics and postoperative cognitive dysfunction. This article first describes and classifies artificial intelligence, introduces its realization method, machine learning algorithms, and briefly introduces the basic principles of regression and classification methods in machine learning; then, the principles and techniques of general anesthetics are proposed. The pathogenesis of postoperative cognitive dysfunction (POCD) is explained in detail. Finally, the effect of anesthetics on postoperative cognitive dysfunction is obtained from both inhaled anesthetics and intravenous anesthetics. The impact on postoperative cognitive function is explained. The experimental results in this article show that there is no statistically significant difference in the two groups of patients' age, gender ratio, body mass index, education level, preoperative comorbidities, and other general indicators. Through the use of EEG bispectral index monitors to monitor the depth of anesthesia and postoperative cognitive dysfunction, first, there was no obvious relationship between the occurrence of postoperative cognitive dysfunction at 1, 5, 10, and 50 days and discharge time. The comprehensive monitoring group can reduce the clinical dose of preventive medication and cis-atracurium and shorten the patient's recovery time, extubation time, and recovery time. In addition, it can also reduce the increase of serum protein S100 in elderly patients and reduce the incidence of early postoperative cognitive dysfunction.
术后认知功能障碍（POCD）是指患者无精神障碍的中枢神经系统在手术前后的并发症。许多研究表明，手术麻醉可能会引起 POCD，尤其是老年患者。本文旨在研究基于人工智能的全身麻醉与术后认知功能障碍之间的关系。本文首先描述并分类了人工智能，介绍了它的实现方法、机器学习算法，并简要介绍了机器学习中回归和分类方法的基本原理；然后，提出了全身麻醉的原理和技术，详细解释了术后认知功能障碍（POCD）的发病机制。最后，从吸入性麻醉药和静脉麻醉药两方面得出麻醉对术后认知功能的影响。本文的实验结果表明，两组患者的年龄、性别比、体重指数、教育水平、术前合并症等一般指标差异均无统计学意义。通过使用脑电图双频谱指数监测仪监测麻醉深度和术后认知功能，首先，术后认知功能障碍在 1、5、10、50 天的发生与出院时间之间没有明显关系。综合监测组可以减少预防性用药和 cis-atracurium 的临床剂量，缩短患者的恢复时间、拔管时间和恢复时间。此外，还可以降低老年患者血清 S100 蛋白的增加，降低早期术后认知功能障碍的发生率。
