Perioperative, electroencephalographic characteristics of postoperative delirum in elderly
老年人术后谵妄的围术期、脑电图特征
基本信息
- 批准号:409495393
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:德国
- 项目类别:Research Grants
- 财政年份:2018
- 资助国家:德国
- 起止时间:2017-12-31 至 2023-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
老年患者术后妄想(POD)是手术后脑功能障碍最常见的临床表现。POD与住院时间延长、死亡率较高以及长期认知功能受损有关。识别个体易感因素和避免诱发风险因素是有效预防POD的关键。然而,到目前为止,还没有有效的生物标志物来识别POD的高危患者,使麻醉医生能够适应麻醉程序/药物,并准备POD治疗方案。虽然脑电监测是最可行的方法来跟踪全身麻醉下的脑状态,但目前在常规麻醉实践中仅使用单一的EEG衍生指数(BIS指数、麻醉趋势指数、PSI指数),而不考虑年龄和不同的麻醉剂。全麻下脑电数据振荡的复杂频谱分析是当前研究项目的重点,该研究项目分析了不同麻醉剂和年龄组在全麻期间的影响。不同的麻醉剂与不同的分子靶点和神经回路相互作用,导致意识丧失,从而产生不同的术中脑电特征。围绕埃默里·布朗的研究小组最近通过对原始脑电文件进行频谱分析来表达这一点。这一知识对于识别有POD风险的老年患者的围手术期脑电信号是至关重要的。有趣的是,长时间的深度麻醉已被证明是导致POD发生率较高的主要危险因素之一,通过对识别出长时间猝发抑制时期的原始脑电的目测分析将其分类。此外,脑电频谱分析最近被证明是监测患有神经退行性疾病的老年患者认知功能的有价值的工具,可以帮助预测从轻度认知障碍到痴呆的转变。根据脑电分析方法得出的这些结果,我们推测,可以使用特定的脑电参数/信号在围手术期识别有发生POD风险的患者。在目前的研究中,我们主要关注从术前、术中和术后脑电记录中获得的生物标志物。我们的目标是(1)确定术前脑电标记物,以指示患者发生POD的风险;(2)明确与POD相关的术中EEG信号/状态;以及(3)检测与POD直接相关的在恢复室逗留期间的EEG信号,因此可用作诊断工具。我们希望通过识别基于脑电的POD生物标记物来改善老年患者的术后认知结果,该标记物是用更复杂的围术期脑电数据分析方法开发的,考虑了与年龄和不同麻醉剂相关的脑电动力学。
项目成果
期刊论文数量(0)
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