亚健康状态患者脑电地形图与对照组对比分析

目的通过调查亚健康状态患者的脑电地形图,并与对照组正常人群的脑电地形图进行对比分析,获得诊断学上的证据。方法把280例亚健康状态患者与280例正常人群均进行脑电图及脑电地形图的采样分析。结果脑电地形图中δ、θ、α、β及β频带与健康组比较,亚健康组出现的异常率明显增高（P＜0.05 ）。结论亚健康状态中患者的脑电活动不稳定,具有明显的焦虑趋势。脑电地形图侧重于大脑功能性的诊断,对亚健康人群中失眠者的诊断有诊断价值。     

植物状态患者脑深部电刺激术后脑脓肿1例报告并文献复习

目的探讨脑深部电刺激术后脑脓肿及手术部位感染的影响因素、预防措施和治疗方案。方法回顾性分析1例植物状态行脑深部电刺激(DBS)术后发生脑脓肿患者的临床和影像资料;并复习相关文献。结果本例患者脑深部电刺激植入术后26 d确诊脑脓肿,根据伤口引流液培养结果选用敏感药物复方新诺明治疗,3个月后脓肿消失。结合文献报道,脑深部电刺激术后感染的预后与致病菌种类等因素有关。结论脑深部电刺激手术部位感染一经发现,应尽早取得病原学证据,部分感染经抗生素治疗、局部清创等措施可避免植入物移除。     

精神分裂症患者静息态脑电微状态特征及研究进展

本文目的是探讨精神分裂症患者静息态脑电微状态的特征和研究进展,以期从神经电生理的角度为精神分裂症的临床研究提供参考。于2022年9月在中国知网、万方数据知识服务平台和Pub Med数据库进行计算机检索,最终纳入符合标准的文献共27篇。既往研究结果显示,静息状态下精神分裂症患者总是有着更多的C类脑电微状态和更少的D类脑电微状态,这使得静息态脑电微状态具有成为疾病内表型的潜质。虽然,精神分裂症患者的精神症状与静息态脑电微状态之间的相关性目前仍不明确,但可以肯定的是,治疗前后患者静息态脑电微状态的变化是有意义的。     

神经电刺激对昏迷及植物状态的影响

本文就神经电刺激对昏迷和植物状态影响的研究进展作以综述。近十年来的研究表明,神经电刺激对中枢神经系统的功能恢复有促进作用,尤其在改善脑代谢,增加脑血流,调节神经递质活性和促进神经电生理改善等方面均有肯定的作用,经临床实验证实神经电刺激对部分昏迷和植物状态病人有一定的治疗作用。但是许多研究也同时指出该治疗方法在实际应用中仍有许多限制。     

脑血管疾病导致的持续性植物状态4例临床和电生理报告

持续性植物状多见于心肺复生后昏迷病人的恢复期,但急慢性脑血管疾病也是重要的病因之一。本文报告4例由各种类型的脑血管病所引起的持续性植物状态(PVS)。我科从1974年至1988年底较系统地观察了4例由脑血管疾病导致的 PVS,部分病例做脑电图和诱发电位检查,现报告如下:例1.No.796410,57岁男性,高血压和脑动脉硬化史10年,冠心病合并心律异常8年,痴呆和生活不能自理5年。病程中经常肺部感染、高热、并有全身性抽搐发作。在一     

颈髓电刺激治疗持续性植物状态疗效观察

目的 探讨颈髓电刺激（cSCS）治疗持续性植物状态的临床疗效。方法 自2010年1月到2013年12月收治PVS患者40例,30采用常规治疗（脑室-腹腔分流术、颅骨修补术、药物、高压氧治疗等）和10例在常规治疗基础上加用cSCS治疗。根据2002年我国专家会议修订的PVS诊疗标准判断疗效,疗效提高≤2分为无效,≥3分为好转,≥8分为显效,12分为脱离植物状态;好转和显效为有效。结果 cSCS治疗组显效3例,好转5例,无效2例;常规治疗组显效3例,好转8例,无效19例。cSCS治疗组有效率（80%,8/10）明显高于常规治疗组（36.7%,11/30;P<0.05）。结论 cSCs治疗对持续性植物状态促醒有一定疗效。     

脊髓电刺激治疗持续性植物状态的作用机制

持续性植物状态目前无特殊有效治疗手段.脊髓电刺激通过高位颈髓节段硬脊膜外隙植入电极,发放持续电刺激脉冲,提高脑血流、调节多种神经递质水平、激活上行性网状激活系统、调节交感副交感神经、提高脑组织葡萄糖代谢率、改善神经电生理指标等可能机制,促进意识恢复.     

肺癌性脑损害患者的脑电地形图分析

本文报道６３例肺癌患者脑损害的临床表现，头颅ＣＴ、ＥＥＧ和ＢＥＡＭ检查结果，其中３１例出现肺癌性非转移性脑损害；３２例发现脑转移，分子了肺癌脑损害的脑电变化特点。结果表明，头颅ＣＴ可以确定脑转移病灶的存在，ＥＥＧ和ＢＥＡＭ既可显示肺癌脑转移病灶的脑电变化，还可显示非转移性肺癌性脑损害的存在。     

深部脑刺激术治疗持续植物状态：10年随访结果分析

目的与方法对21例各种脑外伤引起的持续性植物状态病人进行神经功能和脑电生理学评估。随后对病人均行深部脑刺激术治疗,并随访10年。刺激电极放置在中脑网状结构2例,丘脑板内核群19例。结果8例病人清醒,能按吩咐闭眼和张口,但仍卧床。对此8例病人进行持续脑电图监测,发现脑电波呈去同步化且尽管潜伏期延长,但还是能够记录到脑干反应第Ⅴ波和视觉诱发电位N20,且疼痛相关的P250波幅超过7 mV。此8例病人平均生存时间6.1年,其余13例为3.1年。本组4例(19%)生存时间超过10年,与未经深部脑刺激术治疗的持续性植物状病人生存期相比,明显提高。结…     

Altered resting state effective connectivity in long-standing vegetative state patients: An EEG study

ObjectiveRecent evidence mainly based on hemodynamic measures suggests that the impairment of functional connections between different brain areas may help to clarify the neuronal dysfunction occurring in patients with disorders of consciousness (DOC).The aim of this study was to evaluate effective EEG connectivity in a cohort of 18 patients in a chronic vegetative state (VS) observed years after the occurrence of hypoxic (eight) and traumatic or hemorrhagic brain insult.Methodswe analysed the EEG signals recorded under resting conditions using a frequency domain linear index of connectivity (partial directed coherence: PDC) estimated from a multivariate autoregressive model. The results were compared with those obtained in ten healthy controls.ResultsOur findings indicated significant connectivity changes in EEG activities in delta and alpha bands. The VS patients showed a significant and widespread decrease in delta band connectivity, whereas the alpha activity was hyper-connected in the central and posterior cortical regions.ConclusionThese changes suggest the occurrence of severe circuitry derangements probably due to the loose control of the subcortical connections. The alpha hyper-synchronisation may be due to simplified networks mainly involving the short-range connections between intrinsically oscillatory cortical neurons that generate aberrant EEG alpha sources. This increased connectivity may be interpreted as a reduction in information capacity, implying an increasing prevalence of stereotypic activity patterns.SignificanceOur observations suggest a remarkable rearrangement of connectivity in patients with long-standing VS. We hypothesize that in persistent VS, after a first period characterized by a breakdown of cortical connectivity, neurodegenerative processes, largely independent from the type of initial insult, lead to cortex de-afferentation and to a severe reduction of possible cortical activity patterns and states.     

Quantitative EEG reactivity and machine learning for prognostication in hypoxic-ischemic brain injury

ObjectiveElectroencephalogram (EEG) reactivity is a robust predictor of neurological recovery after cardiac arrest, however interrater-agreement among electroencephalographers is limited. We sought to evaluate the performance of machine learning methods using EEG reactivity data to predict good long-term outcomes in hypoxic-ischemic brain injury.MethodsWe retrospectively reviewed clinical and EEG data of comatose cardiac arrest subjects. Electroencephalogram reactivity was tested within 72 h from cardiac arrest using sound and pain stimuli. A Quantitative EEG (QEEG) reactivity method evaluated changes in QEEG features (EEG spectra, entropy, and frequency features) during the 10 s before and after each stimulation. Good outcome was defined as Cerebral Performance Category of 1–2 at six months. Performance of a random forest classifier was compared against a penalized general linear model (GLM) and expert electroencephalographer review.ResultsFifty subjects were included and sixteen (32%) had good outcome. Both QEEG reactivity methods had comparable performance to expert EEG reactivity assessment for good outcome prediction (mean AUC 0.8 for random forest vs. 0.69 for GLM vs. 0.69 for expert review, respectively; p non-significant).ConclusionsMachine-learning models utilizing quantitative EEG reactivity data can predict long-term outcome after cardiac arrest.SignificanceA quantitative approach to EEG reactivity assessment may support prognostication in cardiac arrest.     

Quantitative analysis of EEG reactivity for neurological prognostication after cardiac arrest

ObjectiveTo test whether 1) quantitative analysis of EEG reactivity (EEG-R) using machine learning (ML) is superior to visual analysis, and 2) combining quantitative analyses of EEG-R and EEG background pattern increases prognostic value for prediction of poor outcome after cardiac arrest (CA).MethodsSeveral types of ML models were trained with twelve quantitative features derived from EEG-R and EEG background data of 134 adult CA patients. Poor outcome was a Cerebral Performance Category score of 3–5 within 6 months.ResultsThe Random Forest (RF) trained on EEG-R showed the highest AUC of 83% (95-CI 80–86) of tested ML classifiers, predicting poor outcome with 46% sensitivity (95%-CI 40–51) and 89% specificity (95%-CI 86–92). Visual analysis of EEG-R had 80% sensitivity and 65% specificity. The RF was also the best classifier for EEG background (AUC 85%, 95%-CI 83–88) at 24 h after CA, with 62% sensitivity (95%-CI 57–67) and 84% specificity (95%-CI 79–88). Combining EEG-R and EEG background RF classifiers reduced the number of false positives.ConclusionsQuantitative EEG-R using ML predicts poor outcome with higher specificity, but lower sensitivity compared to visual analysis of EEG-R, and is of some additional value to ML on EEG background data.SignificanceQuantitative EEG-R using ML is a promising alternative to visual analysis and of some added value to ML on EEG background data.     

Quantitative EEG analysis at rest and during photic stimulation in drug-naive patients with first-episode paranoid schizophrenia

In the present study, quantitative EEG analysis was performed at rest and during 10 Hz photic stimulation in 14 drug-naive patients with first-episode paranoid schizophrenia and 20 sex- and age-matched control subjects. Compared with the normal controls, the patients had significantly lower alpha-2 band amplitude in the resting EEG over all recording regions. No significant group differences were found in other frequency bands. In addition, EEG analysis during photic stimulation demonstrated that the patients had a rather uniform topographic profile in EEG amplitude for the alpha band, with significant group differences being confined to the posterior regions in the left hemisphere. There were no significant group differences in the amplitude for the frequency bands harmonically related to the stimulus frequency. These findings provide further evidence that schizophrenic patients have abnormal EEG activity in both non-stimulus and stimulus conditions, and suggest a dysfunction in the mechanisms underlying EEG alpha generation in schizophrenia.     

MRI brain lesion patterns in patients in anoxia-induced vegetative state

The object of this study was to analyze magnetic resonance imaging data from patients with disorders of consciousness who were suffering from non-traumatically induced brain lesions with respect to the pattern of vulnerability and to examine the associations between the sizes of these lesions and the clinical outcome of the patients. To this end, T1- and T2-weighted brain images were examined in twelve patients in the post-anoxic vegetative state after a median of 21 days after the causative event. Predominant in the characteristic lesion patterns were regions of pathological white matter signals within the frontal and occipital lobes and in the periventricular regions. The total volumes of the lesions were found to be associated with the severity of the patients' clinical outcomes as measured by the Ranchos Los Amigos Cognitive Scale after a median of 25 months. These lesion patterns demonstrated damage to cerebral networks critical to higher cognitive processes (“consciousness”) in both white and gray matter. The relevance of these findings for patients in anoxia-induced decreased levels of consciousness is discussed.     

Automated EEG entropy measurements in coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state

Monitoring the level of consciousness in brain-injured patients with disorders of consciousness is crucial as it provides diagnostic and prognostic information. Behavioral assessment remains the gold standard for assessing consciousness but previous studies have shown a high rate of misdiagnosis. This study aimed to investigate the usefulness of electroencephalography (EEG) entropy measurements in differentiating unconscious (coma or vegetative) from minimally conscious patients. Left fronto-temporal EEG recordings (10-minute resting state epochs) were prospectively obtained in 56 patients and 16 age-matched healthy volunteers. Patients were assessed in the acute (≤1 month post-injury; n=29) or chronic (>1 month post-injury; n=27) stage. The etiology was traumatic in 23 patients. Automated online EEG entropy calculations (providing an arbitrary value ranging from 0 to 91) were compared with behavioral assessments (Coma Recovery Scale-Revised) and outcome. EEG entropy correlated with Coma Recovery Scale total scores (r=0.49). Mean EEG entropy values were higher in minimally conscious (73±19; mean and standard deviation) than in vegetative/unresponsive wakefulness syndrome patients (45±28). Receiver operating characteristic analysis revealed an entropy cut-off value of 52 differentiating acute unconscious from minimally conscious patients (sensitivity 89% and specificity 90%). In chronic patients, entropy measurements offered no reliable diagnostic information. EEG entropy measurements did not allow prediction of outcome. User-independent time-frequency balanced spectral EEG entropy measurements seem to constitute an interesting diagnostic - albeit not prognostic - tool for assessing neural network complexity in disorders of consciousness in the acute setting. Future studies are needed before using this tool in routine clinical practice, and these should seek to improve automated EEG quantification paradigms in order to reduce the remaining false negative and false positive findings.     

脑电图反应性联合中脑形态对重型颅脑损伤昏迷患者预后评估的临床研究

目的 探讨脑电图(EEG)反应性联合中脑形态对重型颅脑损伤昏迷患者临床预后的评估价值. 方法 选择南方医科大学附属花都医院神经外科自2011年4月至2012年10月收治的116例重型颅脑损伤昏迷患者,入院后72h内选用数字化视频EEG监测系统对患者行EEG监测,同时行头颅CT扫描并测量中脑前后径与横径的比值.统计分析患者EEG反应性、中脑前后径与横径的比值与患者预后的关系. 结果 116例患者中EEG有反应65例,无反应51例;中脑前后径与横径的比值为0.9～1.1者60例,比值＞1.1或＜0.9者56例.EEG有反应组预后良好率高于EEG无反应组,中脑前后径与横径的比值为0.9～1.1组预后良好率高于比值＞1.1或＜0.9组,差异有统计学意义(P＜ 0.05);EEG反应性联合中脑形态评估重型颅脑损伤昏迷患者预后的敏感度、特异度均较高. 结论 EEG反应性联合中脑形态检测可有效评估重型颅脑损伤昏迷患者的预后.     

Quantitative EEG asymmetry correlates with clinical severity in unilateral Sturge-Weber syndrome

PURPOSE: Sturge-Weber syndrome (SWS) is a neurocutaneous disorder with vascular malformations of the skin, brain, and eye. SWS results in ischemic brain injury, seizures, and neurologic deficits. We hypothesized that a decrease in quantitative EEG (qEEG) power, on the affected side, correlates with clinical severity in subjects with SWS. METHODS: Fourteen subjects had 16-channel scalp EEG recordings. Data were analyzed using fast Fourier transform and calculation of power asymmetry. Blinded investigators assigned scores for clinical neurological status and qualitative assessment of MRI and EEG asymmetry. RESULTS: The majority of subjects demonstrated lower total power on the affected side, usually involving all four frequency bands (delta, theta, alpha, and beta). qEEG asymmetry correlated strongly with neurologic clinical severity scores and MRI asymmetry scores. qEEG data generally agreed with the MRI evidence of regional brain involvement. In MRI-qEEG comparisons that did not agree, decreased power on qEEG in a brain region not affected on MRI was more likely to occur in subjects with more severe neurologic deficits. CONCLUSIONS: qEEG provides an objective measure of EEG asymmetry that correlates with clinical status and brain asymmetry seen on MRI. These findings support the conclusion that qEEG reflects the degree and extent of brain involvement and dysfunction in SWS. qEEG may potentially be a useful tool for early diagnosis and monitoring of disease progression in SWS. qEEG may prove useful, in severely affected individuals with SWS, for determining regions of brain dysfunction.     

持续性植物状态猫脑脊液中多巴胺变化实验研究

目的 探讨持续性植物状态猫脑脊液中多巴胺的变化及其意义。方法 用高效液相色谱测定持续性植物状态猫脑脊液中多巴胺含量，并与正常对照组对比。结果 持续性植物状态猫的脑脊液中多巴胺含量显降低。结论 多巴胺的减少可能是形成持续性植物状态猫的重要因素之一。     

脑死亡患者脑电图频谱分析

目的 通过对脑死亡患者脑电图进行定量分析,寻找敏感可靠的脑死亡诊断标准.方法 对17例确诊为脑死亡患者及5例临床脑死亡患者进行脑电图频谱分析,并与13例非脑死亡患者的脑电图资料进行比较.结果 脑死亡组的脑电功率值显著低于非脑死亡组(均P<0.01).临床脑死亡组脑电功率值介于脑死亡组与非脑死亡组之间,脑电功率值高者预后较好,脑电功率值低者预后较差.结论 脑电图频谱分析可能对脑死亡的判断、特别是临床脑死亡患者预后的判断有一定价值.