Abstract:

Objective　To investigate the characteristics of quantitative electroencephalogram (QEEG) in patients with chronic consciousness disturbance, and to analyze its relationship with consciousness disturbance degree and its value in predicting the short-term outcomes of consciousness. Methods　This was a prospective study. A total of 70 patients with chronic consciousness disturbance treated at Xi'an International Medical Center Hospital from June 2021 to January 2024 were selected, and were divided into a vegetative state group (24 cases; 15 males and 9 females; VS group), a microconscious state - group (24 cases; 17 males and 7 females; MCS- group), and a microconscious state + group (22 cases; 14 males and 8 females; MCS+ group) according to the degree of consciousness disorder. All the patients completed 4-week follow-up. The Coma Recovery Scale Revised(CRS-R) scores at admission and 4-week follow-up were compared; the patients were divided into a consciousness improvement group and a no consciousness improvement group according to their improvement. QEEG examination was completed in all the groups. χ² test, t test, and analysis of variance were used for the statistical comparisons. The Pearson correlation analysis software was used to analyze the correlation between QEEG and CRS-R scores in the patients. Univariate and multivariate analyses were performed for the patients' short-term consciousness outcomes. The receiver operating characteristic curve (ROC) was drawn to analyze the predictive efficacy of QEEG for the patients' short-term consciousness outcomes. Results　In the MCS- group, 15 cases were of RAV classification Ⅲ and 6 cases of Ⅳ, and the spectral entropy was 54.43±4.13; in the MCS+ group, 9 cases, 11 cases, and 57.51±4.96; in the VS group, 4 cases, 3 cases, and 51.49±3.35; there were statistical differences between the 3 groups (all P<0.05). The Pearson correlation analysis showed that the CRS-R score was positively correlated with RAV, α relative band energy, and spectral entropy in the patients (r=0.392, 0.349, and 0.486; all P<0.05). The univariate and multivariate results showed that CRS-R, RAV grade, conscious state at admission, α relative band energy, and spectral entropy were independent factors influencing the patients' short-term conscious outcomes (all P<0.05). The ROC results showed that the predictive sensitivity and specificity of the combination of RAV classification, α relative band energy, and spectral entropy for the patients were 89.57% and 85.61%, respectively, which were higher than those of single index (all P<0.05). Conclusion　Chronic consciousness disturbance has typical QEEG characteristics, which can represent the degree of consciousness disturbance and improve the sensitivity and specificity of consciousness prognosis in short term.

Key words:

Disturbance of consciousness, Chronic, Quantitative electroencephalography, Outcomes, Correlation analysis

摘要：

目的　探讨慢性意识障碍患者的定量脑电图特征，分析其与意识障碍程度的关系及预测短期内意识转归的价值。方法　采用前瞻性研究，选取2021年6月至2024年1月西安国际医学中心医院收治的慢性意识障碍患者70例为对象，根据患者意识障碍程度分为植物状态（VS）组（24例，男15例，女9例）、微意识状态-（MCS-）组（24例，男17例，女7例）和微意识状态+（MCS+）组（22例，男14例，女8例）；均完成4周随访，比较入院时及随访4周时昏迷恢复量表修订版（CRS-R）评分，并根据意识改善情况分为改善组与未改善组；各组均完成定量脑电图检查。采用χ²、t、方差检验进行统计比较；Pearson相关性分析软件分析患者定量脑电图与CRS-R评分的相关性，对患者短期内意识转归完成单因素和多因素分析；绘制受试者操作特征曲线（ROC），分析定量脑电图在慢性意识障碍患者短期内意识转归中的预测效能。结果　MCS-组相对α变异（RAV）Ⅲ级15例、Ⅳ级6例，频谱熵水平为54.43±4.13，MCS+组分别为9例、11例、57.51±4.96，VS组分别为4例、3例、51.49±3.35，3组比较差异均有统计学意义（均P<0.05）。Pearson相关性分析结果表明，慢性意识障碍患者CRS-R评分与RAV、α相对频带能量及频谱熵呈正相关性（r=0.392、0.349、0.486，均P<0.05）；单因素和多因素结果显示，CRS-R、RAV分级、入院时意识状态、α相对频带能量和频谱熵是慢性意识障碍患者短期内意识转归的独立影响因素（均P<0.05）；ROC结果显示，RAV分级、α相对频带能量、频谱熵联合测定在慢性意识障碍患者短期内意识转归中的预测灵敏度和特异度分别为89.57%和85.61%，均高于单一指标（均P<0.05）。结论　慢性意识障碍具有典型的定量脑电图特征，其能反映患者意识障碍程度，典型特征参数联合测定可提升短期内意识转归的预测灵敏度和特异度。

关键词:

意识障碍, 慢性, 定量脑电图, 转归, 相关性分析