s and its correlation to POD development is still lacking. We explored the relationship between perioperative EEG spectra-derived parameters and POD development, aiming to ascertain the diagnostic utility of these parameters to detect patients developing POD. METHODS: Patients aged ≥65 years undergoing elective surgeries that were expected to last more than 60 minutes were included in this prospective, observational single center study (Biomarker Development for Postoperative Cognitive Impairment [BioCog] study). Frontal EEGs were recorded, starting before induction of anesthesia and lasting until recovery of consciousness. EEG data were analyzed based on raw EEG files and downloaded excel data files. We performed multitaper spectral analyses of relevant EEG epochs and further used multitaper spectral estimate to calculate a corresponding spectral parameter. POD assessments were performed twice daily up to the seventh postoperative day. Our primary aim was to analyze the relation between the perioperative spectral edge frequency (SEF) and the development of POD. RESULTS: Of the 237 included patients, 41 (17%) patients developed POD. The preoperative EEG in POD patients was associated with lower values in both SEF (POD 13.1 ± 4.6 Hz versus no postoperative delirium [NoPOD] 17.4 ± 6.9 Hz; P = .002) and corresponding γ-band power (POD −24.33 ± 2.8 dB versus NoPOD −17.9 ± 4.81 dB), as well as reduced postinduction absolute α-band power (POD −7.37 ± 4.52 dB versus NoPOD −5 ± 5.03 dB). The ratio of SEF from the preoperative to postinduction state (SEF ratio) was ~1 in POD patients, whereas NoPOD patients showed a SEF ratio >1, thus indicating a slowing of EEG with loss of unconscious. Preoperative SEF, preoperative γ-band power, and SEF ratio were independently associated with POD (P = .025; odds ratio [OR] = 0.892, 95% confidence interval [CI], 0.808–0.986; P = .029; OR = 0.568, 95% CI, 0.342–0.944; and P = .009; OR = 0.108, 95% CI, 0.021–0.568, respectively). CONCLUSIONS: Lower preoperative SEF, absence of slowing in EEG while transitioning from preoperative state to unconscious state, and lower EEG power in relevant frequency bands in both these states are related to POD development. These findings may suggest an underlying pathophysiology and might be used as EEG-based marker for early identification of patients at risk to develop POD....

中文翻译：

---

与老年患者术后谵妄相关的围手术期脑电图谱动力学

s 及其与 POD 发展的相关性仍然缺乏。我们探讨了围手术期 EEG 谱衍生参数与 POD 发展之间的关系，旨在确定这些参数在检测 POD 患者方面的诊断效用。方法：这项前瞻性、观察性单中心研究（术后认知障碍的生物标志物开发 [BioCog] 研究）纳入了 65 岁以上接受择期手术且预计持续时间超过 60 分钟的患者。记录额叶脑电图，从麻醉诱导前开始，一直持续到意识恢复。基于原始 EEG 文件和下载的 excel 数据文件分析 EEG 数据。我们对相关的 EEG 时期进行了多锥谱分析，并进一步使用多锥谱估计来计算相应的谱参数。POD 评估每天进行两次，直到术后第七天。我们的主要目的是分析围手术期频谱边缘频率 (SEF) 与 POD 发展之间的关系。结果：在纳入的 237 名患者中，41 名 (17%) 患者出现 POD。POD 患者的术前 EEG 与 SEF（POD 13.1 ± 4.6 Hz 与无术后谵妄 [NoPOD] 17.4 ± 6.9 Hz；P = .002）和相应的 γ 波段功率（POD -24.33 ± 2.8 dB）的较低值相关与 NoPOD -17.9 ± 4.81 dB），以及降低的诱导后绝对 α 波段功率（POD -7.37 ± 4.52 dB 与 NoPOD -5 ± 5.03 dB）。从术前到诱导后状态的 SEF 比率（SEF 比率）在 POD 患者中约为 1，而 NoPOD 患者显示 SEF 比率 >1，因此表明 EEG 减慢并失去意识。术前 SEF、术前 γ 波段功率和 SEF 比值与 POD 独立相关（P = .025；优势比 [OR] = 0.892，95% 置信区间 [CI]，0.808–0.986；P = .029；OR = 0.568, 95% CI, 0.342–0.944；P = .009；OR = 0.108, 95% CI, 0.021–0.568)。结论：术前 SEF 较低，从术前状态过渡到无意识状态时脑电图没有减慢，这两种状态下相关频段的脑电图功率较低都与 POD 的发展有关。