VEEG监测对鉴别癫及非癫发作的意义

目的探讨发作期视频脑电图（VEEG）在诊断癫性发作及发作类型的临床价值。方法对435例发作性疾病患者的临床资料和发作期VEEG进行回顾性分析。结果 VEEG共监测到临床发作733次,发作期脑电图记录到样放电557次。诊断为癫381例,其中癫合并非癫性发作（NES）24例,占6.3%;单纯NES 54例。癫发作类型以部分性发作为主,癫发作及发作间期样放电多见于NREMⅠ、Ⅱ期。结论 发作期VEEG监测对鉴别癫及非癫发作有重要的鉴别意义。     

长程视频脑电图在癫癇诊断与鉴别诊断中的作用

目的评价长程视频脑电图对癫癇和非癫癇发作性疾病的诊断价值。方法对因发作性事件就诊并拟诊为癫癇或可疑癫癇的279例患者的长程视频脑电图资料进行回顾分析。结果 279例患者中122例(43.73%)长程视频脑电图监测到临床发作,其中84例可见发作期同步样放电而确诊为癫癇发作,38例发作期无同步样放电而确诊为非癫癇发作;157例(56.27%)未监测到临床发作,其中102例可见发作间期样放电。监测到发作期或发作间期样放电的188例患者中97例明确癫癇发作类型,其中75例进一步确定为癫癇综合征。结论长程视频脑电图在癫癇的诊断、分型及其与非癫癇发作性疾病的鉴别诊断中具有重要临床价值。     

儿童非癫的癫样发作34例临床分析

目的探讨儿童非癫样的癫样发作的临床特点及诊断。方法对我院34例临床拟诊癫的发作性疾病做视频脑电图检查并进行分析。结果34例临床拟诊癫病患儿视频脑电图检查结果示患儿临床发作时同步脑电图无癫波发放。结论诊断儿童癫病应慎重,视频脑电图是确诊癫与非癫可靠有效的方法。     

长程视频脑电监测对癫的诊断价值

目的评价长程视频脑电图对癫等发作性疾病的诊断价值,提高癫及癫综合征的诊断。方法对在本院神经内科癫中心门诊及住院患者中首次以发作性疾病就诊的患者进行不同时程的视频脑电图监测,对其临床资料进行回顾性分析。结果 24 h组视频脑电监测对癫异常脑波放电的阳性检出率较高(76.9%),8 h组最低(30.1%),15 h组介于两者之间(55.4%),在24 h组1920例患者中有1476例有异常放电,287例记录到临床同步发作,其中153例明确癫发作类型,153例中96例进一步明确为癫综合征,使对癫的分型及癫综合征的分类更加明了细化。结论 24 h视频脑电监测能够显著提高癫患者的诊断率及异常脑波的检出率,有效地降低了假阴性率并且在癫的鉴别诊断、分型及癫综合症的诊断方面有重要的临床意义,同时对其他发作性疾病的鉴别提供了可靠的的临床依据。     

小儿颞叶癫的临床表现及脑电图分析

目的探讨小儿颞叶癫的临床特征及脑电图特点。方法收集16例颞叶癫患儿,对其发作的临床特点及脑电图资料进行分析,对比难治性癫的脑电图变化规律。结果患儿的癫发作形式主要表现为单纯部分性发作、复杂部分性发作、继发全面性发作。单纯部分发作频率高而持续时间短,复杂部分发作持续时间长但发作频率低并常见发作后朦胧状态。颞叶癫的脑电图特点:背景正常者约占62.5%(10/16);背景异常约占37.5%(6/16);异常放电及部位:颞叶棘波或慢波放电,表现为单侧或双侧同步或不同步放电。结论小儿颞叶癫是一组部分性症状性癫综合征,多表现为复杂部分发作,临床发作及同步脑电图特点可为临床诊治提供帮助。     

89例动态脑电图监测对诊断癫（癎）的意义

目的探讨动态脑电图(ambulatory electroencephalogram,AEEG)对癫鉴别诊断的意义。方法对89例临床可疑癫病人进行动态脑电图监测,并对监测结果分析。结果AEEG检查发现有样放电者69例,占77.5%,其中27例(30.3%)有临床发作,42例(47.2%)仅在AEEG检查发现样放电,20例(22.5%)排除癫。结论AEEG对癫的鉴别诊断具有重要作用。     

视频脑电图在癫(癎)诊断中的应用

目的:探讨视频脑电图对癫的诊断价值及其适用性。方法:对117例发作性疾病患者进行视频脑电图监测后进行分析比较。结果:117例患者视频脑电图共诊断癫37例,诊断阳性率27.4%;60例临床未诊断癫患者中,视频脑电图比常规脑电图诊断阳性率高(11例)18.3%(P=0.04);57例临床诊断癫患者中,有5例临床诊断的癫分型与其发作时临床表现不符,不符合率为8.8%。结论:视频脑电图可以提高癫诊断率及分型的准确性,有利于指导临床合理用药。     

VEEG监测对鉴别癫及非癫发作的意义

目的 探讨发作期视频脑电图(VEEG)在诊断癫性发作及发作类型的临床价值.方法 对435例发作性疾病患者的临床资料和发作期VEEG进行回顾性分析.结果 VEEG共监测到临床发作733次,发作期脑电图记录到样放电557次.诊断为癫381例,其中癫合并非癫性发作(NES)24例,占6.3%;单纯NES 54例.癫发作类型以部分性发作为主,癫发作及发作间期样放电多见于NREMⅠ、Ⅱ期.结论 发作期VEEG监测对鉴别癫及非癫发作有重要的鉴别意义.     

儿童局灶性发作发作期电-临床特征分析

目的探讨儿童期局灶性发作发作期电-临床特征。方法以2017年1月至2018年6月确诊的257例局灶性发作共409次患儿为受试者,结合头部影像学资料分析视频脑电图特征。结果发作期症状主要表现为双眼斜凝视(202次)、偏转(142次)、不对称性强直(138次)、口角歪斜(45次)、单个或一侧肢体强直-阵挛(42次)、感觉异常(32次)、自主神经症状(92次)、过度运动(93次),以及手、口自动症行为(92次)、发声(68次)和局灶性失张力(6次)、局灶性肌阵挛(4次)、局灶性强直(2次),以上症状以单一或组合方式出现。视频脑电图监测,发作类型呈局灶性发作(249次)、局灶继发双侧强直-阵挛发作(121次)、局灶性发作持续状态(29次)、局灶性发作伴痉挛(10次);发作期脑电初始模式分别表现为脑区性(188次)、局灶性(55次)、一侧大脑半球(53次)、非一侧性(71次)或无法确定(42次);发作间期脑电活动则呈局灶性放电(92例)、多灶性放电(49例)、广泛性放电(27例)或无放电(89例)。257例中178例(69.26%)归类于癫综合征,其中年龄相关性癫综合征以良性家族性或非家族性婴儿惊厥为主占54.26%(51/94例),而部位相关性癫则以额叶癫更高发占62.50%(50/80例)。结论儿童局灶性发作发作期症状具有局灶性特征,发作期初始脑电模式呈多样性,可与多种癫综合征相伴发,视频脑电图监测是目前明确诊断不可替代的方法。     

51例婴儿痉挛症临床与录像脑电图分析

目的通过51例婴儿痉挛症的临床与录像脑电图分析,探讨同步录像脑电图(VEEG)监测对癫发作类型的诊断及鉴别诊断的临床价值。方法采用Nicolet录像脑电图仪,按照国际10/20系统安放电极,采用网帽固定,按时间常数0.3s,走纸速度3cm/s,常规单双导联描记。所记录的图像与脑电信号存储于计算机硬盘内,可在检查后随意调用回放分析。结果51例患儿脑电图均为重度异常,其中典型高度失律EEG及非典型高度失律EEG共40例(占总数的78.4%),其他形式的样放电11例(占总数的21.6%)。51例中同时伴有爆发抑制现象3例(占总数的5.9%)。结论VEEG监测可显著提高样放电的检出率,并有助于区别其他类型的癫发作。     

Video-EEG in the diagnosis of paroxysmal events in children with mental retardation and in children with normal intelligence

Video-EEG monitoring was performed to evaluate 193 children (91 females, 102 males; mean age 9.6 years, SD 5.7) who presented with paroxysmal events of uncertain etiology. Diagnosis of the type of event, i.e. epileptic or non-epileptic, was successfully established in 130 of 193 patients (67.3%). Seventy children (36%) had mental retardation* (MR). Children with MR were more likely (p<0.05) than children without MR to have events during the studies. Children with and without MR had strikingly similar frequencies of epileptic and non-epileptic events. In participants who had events recorded and characterized, epileptic seizures were identified in 67 children (51.5%), non-epileptic events in 54 children (41.5%), and both epileptic and non-epileptic events in nine children (7%). Improved diagnosis prompted appropriate management. This should encourage more frequent use of video-EEG in children, especially in those with MR, to differentiate epilepsy from behavioral disturbances so that specific treatment can be provided.     

The value of provocation methods in patients suspected of having non-epileptic seizures.

Non-epileptic seizures (NES) are reported in 18-23% of patients referred to comprehensive epilepsy centres. Non-epileptic seizures may also be present in 5-20% of the patients who are diagnosed as having refractory seizures. Because of their prevalence, financial and psychosocial outcomes cannot be ignored and accurate diagnosis is of the utmost importance. Various methods of seizure induction have been developed with the aim of differentiating epileptic from non-epileptic seizures. However, recording the attacks by video-EEG monitoring is the gold standard. In our outpatient EEG laboratory we try to induce seizures with verbal suggestion or IV saline infusion in patients who are referred by a clinician with the diagnosis of probable non-epileptic seizures. In this study we investigated the results of 72 patients who were referred between January 1992-June 1996. Non-epileptic seizures were observed in 52 (72.2%) patients. Thirteen of these patients still had risk factors for epilepsy. We could not decide whether all of their previous attacks were non-epileptic because 10-30% of the patients with NES also have epileptic seizures. For a more accurate diagnosis it was decided that these 13 patients, together with the 20 patients who did not have seizures with induction, needed video-EEG monitoring. Thirty-nine patients who had NES and no risk factors for epilepsy were thought to have pure non-epileptic seizures. We claim that not all patients suspected of having NES need long-term video-EEG monitoring and almost half (54.2%) of the cases can be eliminated by seizure induction with some provocative techniques.     

Outpatient Video-EEG Monitoring in Children

Summary: Video-EEG monitoring enables correlation of behavioral activity with EEG activity, which is useful in recognition of pseudoepileptic seizures and in investigation of patients for epilepsy surgery. Because most patients are monitored for a prolonged time as in-patients, the cost of the procedure is high. We investigated the value of brief (2–3 h) outpatient video-EEG monitoring in 43 children with frequent seizures, most of whom had symptomatic generalized epilepsy. Indications for monitoring included differentiation of epileptic from nonepileptic behavior, seizure classification, and determination of seizure frequency. Clinical episodes were recorded in 36 of 43 children (83%). A definite diagnosis was established in 9 of the 17 patients investigated to determine the nature of the clinical behavior. Seizures were classified in 1.5 of the 25 patients investigated to determine seizure type, and classification was different from the original in 9 of the 15 children. A change in epilepsy syndrome classification was made in 9 children. The video-EEG allowed diagnosis in 25 of the 43 children (59.5%). Video-EEG appears to be an effective method for outpatient investigation of children with frequent seizures, particularly those with symptomatic géneralizéd epilepsy.     

Video-EEG monitoring in the elderly: a review of 94 patients

PURPOSE: We sought to determine the utility and results of video-EEG monitoring in elderly patients. There is an increased incidence of epilepsy in the elderly population. Few studies have assessed the characteristics of epileptic and nonepileptic seizures in this age group. Diagnostic evaluation with video-EEG monitoring is a means to distinguish these different types of events. METHODS: The authors reviewed all patients aged 60 years and older who were admitted to the epilepsy monitoring unit at Columbia-Presbyterian Medical Center from January 21, 1991, to April 12, 1999. RESULTS: A total of 94 patients and 99 patient admissions were identified, accounting for 8% of all admissions. The average age was 70 years, and the mean length of stay was 3.8 days. Typical events were recorded in 75 of the 99 patient admissions. A total of 118 seizures was recorded in 46 patients, and 98 nonepileptic events were seen in 27 patients. Of the patients with nonepileptic events, 13 had psychogenic seizures. The majority of patients with nonepileptic events were taking antiepileptic medication. Whereas 76% of the patients with epileptic events had interictal epileptiform discharges, 26% of the patients with nonepileptic events had epileptiform discharges as well. CONCLUSIONS: Video-EEG monitoring in the elderly leads to a definitive diagnosis in the majority of patients in a relatively short time. Interictal recordings are inadequate in determining the nature of paroxysmal events. Nonepileptic events are common in the elderly, including psychogenic seizures, and these are often misdiagnosed and mistreated as epileptic seizures.     

Video-EEG monitoring of paroxysmal events in the elderly

OBJECTIVES: To determine the importance of video-EEG monitoring (VEM) in elderly patients with various paroxysmal events. MATERIAL AND METHODS: We retrospectively identified 16 subjects > or = 60 years old out of 834 (1.9%; 7 females, mean age 67.8 +/- 7.7 years), who were admitted to the Video-EEG Unit between 1997 and 2005 and compared data between those with and without epileptic events. RESULTS: Epilepsy was confirmed in six patients, psychogenic non-epileptic seizures (NES) were diagnosed in seven, one patient had NES and epilepsy whereas the recorded events were non-conclusive in two. NES patients had a higher predisposition to psychiatric disturbances (P<0.02). Following VEM and management alteration, the frequency of monthly events decreased significantly for the cohort as a whole (P<0.001). VEM directly influenced the diagnosis, treatment and outcome of 14 of 16 (88%) patients. CONCLUSION: Video-EEM plays a vital role in the evaluation of paroxysmal events in the elderly, but is vastly underutilized in this population group.     

The tendency to have psychogenic non-epileptic attacks out of camera view during long-term video-EEG monitoring.

The aim of this study was to compare out of camera view seizure occurrence rates between psychogenic non-epileptic and epileptic seizures during long-term video-EEG monitoring. From 1996 to 2001, 208 adult patients were monitored in 212 sessions, and 196 patients were included in the study. Depending on video-EEG recordings and witnessed accounts, 18 of the patients had no seizures recorded, 160 had epileptic seizures and 18 had psychogenic non-epileptic seizures, four of whom had psychogenic non-epileptic seizures plus true epileptic seizures. Six hundred and ninety two seizures were recorded; 634 of them were epileptic seizures and 58 of them, psychogenic non-epileptic ones. Out of camera attack occurrence was significantly higher in patients with psychogenic non-epileptic attacks compared with epileptic ones (chi-square with Yates correction = 19.75, df = 1, P< 0.001).     

Autism and epilepsy: a retrospective follow-up study

So-called "idiopathic" autism, which exhibited no major complications before diagnosis is well-known as one of the risk factors for epilepsy. This retrospective follow-up study aimed to clarify the characteristics of epilepsy in the autism; onset of seizure, seizure types, EEG findings and epilepsy outcome and the differences as a group between the autism with epilepsy and those without epilepsy. One hundred thirty individuals with autistic disorder or atypical autism diagnosed in childhood were followed up over 10 years and were evaluated almost every year up to 18-35 years of age. Their medical records related to perinatal conditions, IQ, social maturity scores and several factors of epilepsy were reviewed in October 2005. Thirty-three of the follow-up group (25%) exhibited epileptic seizures. The onset of epilepsy was distributed from 8 to 26 years of age. Two types of seizure were observed; partial seizure with secondarily generalized seizure and generalized seizure. Twenty of the epileptics (61%) showed the partial seizure. Although 18% of the non-epileptic group exhibited epileptic discharges on EEG, 68% of the epileptic group revealed epileptiform EEG findings before the onset of epilepsy. No differences were observed concerning the sex ratio, autistic disorder/atypical autism and past history of febrile seizures between the epileptic and non-epileptic groups. Lower IQ, lower social maturity score and higher frequency of prescribed psychotropics were observed in the epileptic group compared to the non-epileptics. Idiopathic autism was confirmed as the high risk factor for epilepsy. Epileptiform EEG findings predict subsequent onset of epileptic seizures in adolescence. Epilepsy is one of negative factors on cognitive, adaptive and behavioral/emotional outcomes for individuals with autism.     

Alice in wonderland syndrome in an elderly patient with focal onset epilepsy

Alice in wonderland syndrome (AIWS) is a rare perceptual disorder characterized by subjective distortions of visual and somatosensory perception. Symptoms of AIWS are attributable to functional and structural changes of the visual and somatosensory perceptual system; however, few reports have investigated the pathophysiology of AIWS with regard to epilepsy, especially ictal electroencephalogram (EEG) changes. Herein, we describe the case of an 82-year-old woman with focal onset epilepsy presenting with AIWS, whose seizures were documented by video-EEG monitoring. Video-EEG revealed multiple focal impaired awareness seizures, and ictal EEG changes arose from the right occipital region with small periodic positive discharges with evolution towards the right centro-parietal regions. Our case highlights not only a relationship between epileptic seizures and AIWS but also provides pathological insight into AIWS.     

The relative influence of epileptic EEG discharges, short nonconvulsive seizures, and type of epilepsy on cognitive function

PURPOSE: This study addressed whether cognitive impairment in children with epilepsy is caused by disease-related stable factors, such as the type of epilepsy, or by acute effects of paroxysmal epileptic activity such as epileptic EEG discharges. We studied a nonselected group with short nonconvulsive seizures, as these seizures may elude detection and may therefore persist over a longer period. In this group, the diagnostic issue is to differentiate between the combined effects of several epilepsy-related factors on cognition. METHODS: All children were assessed with 32-channel EEG, synchronized with a computerized cognitive test system and a video-monitoring system. Recording time was 2 h. The primary inclusion criteria were unclear seizures and fluctuations in cognitive performance and/or frequent epileptic EEG discharges in a recent EEG. RESULTS: One hundred fifty-two patients met the inclusion criteria; 31 patients appeared not to have a diagnosis of epilepsy and were used as a nonepilepsy control group. Our results show that type of epilepsy has an impact on stable cognitive functions, such as educational achievement. Paroxysmal epileptic activity (acute effects of seizures and epileptic EEG discharges) affects primarily transient mechanistic cognitive processes (alertness, mental speed). CONCLUSIONS: These results suggest that the effects of paroxysmal epileptic activity on transient cognitive mechanisms may accumulate over time and consequently affect the more stable aspects of cognitive function such as educational achievement. The clinical relevance is that early detection of the cognitive impact of seizure-related activity and subsequent treatment may prevent its detrimental impact on cognitive and educational development.