Li Yaru, Wang Lu, Han Qiaoyu, Han Qi, Jiang Luyang, Wu Yaqing, Feng Yi
Department of Anesthesiology, Peking University People's Hospital, Beijing, China.
Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Beijing, China.
Brain Behav. 2023 Oct;13(10):e3196. doi: 10.1002/brb3.3196. Epub 2023 Jul 26.
Chronic postoperative pain poses challenges, emphasizing the importance of accurately predicting pain in advance. Generally, pain perception is associated with the temporal dynamics of the brain, which can be represented by microstates. Specifically, microstates are transient and patterned brain topographies formed by temporally overlapping and spatially synchronized oscillatory activities. Consequently, by characterizing brain activity, microstates offer valuable insights into pain perception.
In this prospective study, 66 female patients undergoing breast cancer surgery were included. Their preoperative resting-state electroencephalography (EEG) was recorded. Preoperative resting-state EEG was recorded and four specific brain microstates (labeled as A, B, C, and D) were extracted. Temporal characteristics were then analyzed from these microstates. Patients were classified into two groups based on their Numerical Rating Scale (NRS) scores at three months postoperatively. Those with NRS scores ranging from 4 to 10 were classified as the high pain group, while patients with NRS ranging from 0 to 3 were classified as the lowpain group. Statistical analyses were performed to compare the microstate characteristics between these two groups.
Twenty-one patients (32%) were classified as the high pain group and forty-five (68%) as the low-pain group. The occurrence and coverage of microstate C were significantly higher in the high pain group. Additionally, there were significant differences in the microstates transitions between the two groups. Furthermore, the study revealed a positive correlation between the coverage of microstate C and the NRS.
Preoperative resting-state microstate features have shown correlations with postoperative pain. This study presents a novel and advanced perspective on the potential of microstates as a marker for postoperative pain.
慢性术后疼痛带来了诸多挑战，凸显了提前准确预测疼痛的重要性。一般来说，疼痛感知与大脑的时间动态相关，这可以通过微状态来表示。具体而言，微状态是由时间上重叠且空间上同步的振荡活动形成的短暂且有模式的脑地形图。因此，通过表征大脑活动，微状态为疼痛感知提供了有价值的见解。
在这项前瞻性研究中，纳入了66名接受乳腺癌手术的女性患者。记录了她们术前的静息态脑电图（EEG）。记录术前静息态EEG并提取四个特定的脑微状态（标记为A、B、C和D）。然后从这些微状态分析时间特征。根据患者术后三个月的数字评分量表（NRS）得分将其分为两组。NRS得分在4至10之间的患者被归类为高疼痛组，而NRS得分在0至3之间的患者被归类为低疼痛组。进行统计分析以比较两组之间的微状态特征。
21名患者（32%）被归类为高疼痛组，45名（68%）被归类为低疼痛组。微状态C在高疼痛组中的出现率和覆盖率显著更高。此外，两组之间的微状态转换存在显著差异。此外，研究还揭示了微状态C的覆盖率与NRS之间存在正相关。
术前静息态微状态特征已显示出与术后疼痛相关。本研究为微状态作为术后疼痛标志物的潜力提供了一个新颖且先进的视角。
