脑电图技术在癫痫患者睡眠障碍、认知障碍及痫样事件识别中的应用研究
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摘要
背景与目的：
癫痫患者常常并发有睡眠障碍、认知功能减退，严重影响其生活质量；不规律用药或感染较易诱发其出现癫痫持续状态，甚至威胁其生命。神经元异常放电是癫痫发作的基础，只有借助脑电图技术方可客观判定其异常痫样放电情况，常规脑电图操作一般不记录肌电、眼动，缺乏对睡眠结构的深入了解；对痫样放电仅能定性检测、缺乏量化的标准；此外，脑电图阅图繁琐、专业性强，不易在医护工作者间普及应用。因此，我们通过将传统脑电图技术改良，增加一些睡眠参数、定量分析方法及趋势图分析方法，能进一步探讨痫样放电与睡眠-觉醒周期关系、痫样放电与认知功能的关系、及痫样放电与频繁痫样发作的关系。
方法：
1.痫样放电与睡眠-觉醒周期的研究：我们将脑电图技术与眼动、肌电等睡眠参数结合，对200例癫痫患者及182例健康对照者进行24小时监测，记录结束后回放分析痫样放电出现方式、部位及睡眠结构、睡眠时相，并探讨二者之间的关系。
2.痫样放电与认知障碍的研究：我们对67例合并有认知障碍的癫痫患者进行24小时脑电图监测，并通过定量分析法对痫样放电指数进行分类，进而对不同痫样放电指数的癫痫患者进行认知相关性神经心理测试，并探讨二者之间的关系。
3.趋势图—CDSA、aEEG识别痫样发作准确性的研究：我们选择30条连续24小时记录的脑电图数据（20条包含有痫样发作、10条正常对照），3名经培训的电生理医师采用CDSA、aEEG阅图方法对30条脑电图记录进行解读，对疑似痫样发作之处进行标记，测试结束后与传统脑电图阅图法所判定的发作次数进行比较分析，明确敏感性、误诊率、漏诊率等，并统计分析不同阅图者之间的一致性。
结果：
1.在探讨痫样放电与睡眠-觉醒周期的研究中：我们发现约91%的癫痫患者可通过脑电图监测发现痫样放电；清醒期、睡眠期、清醒及睡眠Ⅰ-Ⅱ期的痫样放电率分别为7.1%、19.2%、25.3%，睡眠Ⅲ-Ⅳ期的痫样放电率为1.1%；癫痫组与正常对照组的总睡眠时间、REM期睡眠时间无明显差异（P＞0.05）；癫痫组与正常组比较，睡眠Ⅰ-Ⅱ期的睡眠时间延长(293.91±27.57min vs223.17±15.28, P=0.000)，睡眠Ⅲ-Ⅳ期时间缩短(50.11±12.12min vs133.96±10.77, P=0.000)；此外，26.7%的癫痫患者出现不对称性纺锤波，43.3%的癫痫患者发现较高睡眠时相转换率所致的睡眠结构片段化。
2.在探讨痫样放电与认知障碍的研究中：10%的痫样放电指数是对成年癫痫患者认知功能产生负性影响的最小研究截点；不同部位的痫样放电对认知功能产生不同的负性影响，如痫样放电位于额叶或颞叶者，显示较差的智商及记忆商；不同痫样放电分布，如局灶性痫样放电与多灶性、泛化性痫样放电对认知功能的负性影响无差异（WAIS-RC:86.11±11.3vs.84.04±10.8, P=0.35;WMS:84.23±9.6vs.82.31±10.23, P=0.35)；不同痫样放电持续时间，对认知功能的负性影响无差异。
3.在探讨趋势图—CDSA、aEEG识别痫样发作准确性的研究中：本研究获得较高的敏感性、较低的误诊率及漏诊率，采用CDSA阅图时，敏感性为80%，24小时的误诊率较低，约4次左右；aEEG阅图时，敏感性为81.3%，24小时的误诊率约2次；采用CDSA及aEEG阅图时，漏诊率均为每24小时，大约4次左右，且CDSA及aEEG两种阅图方法间，漏诊率无明显差异（P>0.05, X2）；此外三名电生理医师采用CDSA及aEEG两种阅图方法解读敏感性、误诊率、漏诊率时，一致性较好，一致性参数分别为κ=0.52及κ=0.68。
结论：
1.既往常规脑电图技术能对痫样放电进行检测分析，而睡眠结构分析需借助多导睡眠监测技术才能完成，本研究中将脑电图技术与睡眠参数相结合，同时对痫样放电与睡眠结构进行分析，建立二者之间的联系，痫样放电可以改变癫痫患者的睡眠结构，同时其睡眠结构的改变，促进痫样放电的发生，因此早期识别癫痫患者所并发的睡眠障碍、制定诊疗方案有助于更好的抑制痫样放电，控制癫痫发作，改善其生活质量。目前此类研究国内报道较少、且国内外未见大样本临床研究，而本实验临床样本量较大、且纳入的癫痫发作类型全面。
2.本研究将脑电图与定量分析法结合，在临床样本中证实痫样放电成为影响成人癫痫患者认知功能的潜在的、隐性的因素，且定量分析引起成人癫痫患者认知功能受损的最小痫样放电指数。既往癫痫常规治疗中对于临床发作次数少的癫痫患者，暂不给予药物治疗或仅给予小剂量药物治疗，不能有效抑制其痫样放电。而我们的研究可能改变传统的治疗观念，即由单纯控制癫痫的临床发作，发展为不仅控制临床发作，还需控制痫样放电，减少认知损伤，我们认为临床发作次数少，脑电图显示频繁临床下痫样放电的患者，需要早期治疗抑制痫样放电以延缓或减少对认知功能的负性影响。我们首次提出10%的痫样放电指数对成人癫痫患者认知功能存在负性影响，此类研究国内未见报道，国外有关痫样放电与认知损伤的报道较少，均在儿童癫痫患者中进行且研究阈值不同，未在成人癫痫患者中研究验证。
3.本研究证实，将脑电趋势图—CDSA及aEEG应用于痫样发作识别中，具有较高的敏感率、较低的误诊率、漏诊率，且简便快捷、可操作性强，有利于非专业医护人员应用，在成人重症病房中的推广具有应用前景。既往此种研究方法多应用于新生儿重症病房，在国内成人重症病房的应用较少，且类似研究结果不同，有一定的临床应用及推广价值。
Background and purpose：
Epilepsy patients are often complicated with sleep disorders, cognitivedysfunction, and are often induced with status epilepticus easily, which may affecttheir life-quality seriously, even threat their lives. Neurons’ abnormal discharge isthe basis for epileptic seizures, EEG technology is an objective method to detect theabnormal epileptiform discharges, on the basis of traditional EEG technology, wehave made some improvements, such as increasing the number of sleep parameters,quantitative analysis and trend analysis, in order to explore the relationship betweenepileptiform discharges and sleep-wake cycle, the epileptiform discharges andcognitive function, and also the relationship between epileptiform discharges andfrequent epileptic seizures.
Method：
1. In the part of exploring the relationship between epileptiform discharges andsleep-wake cycle: We have added sleep parameters such as eye movement and EMGto the traditonal EEG technology, and applied to the200cases of epilepsy patientsand182cases of healthy controls, after the24h-monitoring, we made an analysis ofepileptiform discharges and sleep architecture, sleep phase, then explored therelationship.
2. In the part of exploring the relationship between the epileptiform dischargesand cognitive function: We have included67cases of epilepsy patients withcognitive impairment, after the24h-EEG monitoring, we used quantitative analysismethod to define the epileptiform discharges index, and gave the cognitive-relatedneuropsychological tests to these patients with different index of epileptiformdischarges,then explored the relationship.
3. In the part of exploring the accuracy of trend-CDSA, aEEG applied in theidentification of epileptic seizures: We have selected30continuous24h EEGrecording datas (20data contained epileptic seizures,10data were normal controls),three electrophysiology physician have been trained to use CDSA and aEEG tointerpret these30EEG recordings, and marked any suspected epileptic seizure, afterthe interpretation by CDSA and aEEG, three electrophysiology physician usedconventional EEG reading to identify the real number of seizures, then comparedCDSA and aEEG with conventional EEG to determine the sensitive rate,misdiagnosis rate, missed diagnosis rate, and also made a statistical analysis ofconsistency between the different reviewers.
Results：
1. In the part of exploring the relationship between epileptiform discharges andsleep-wake cycle: We found that about91%of epilepsy patients can be found withepileptiform discharges under the EEG monitoring; the epileptiform discharges ratein waking-phase, sleep-phase, both waking and sleep stage Ⅰ-Ⅱphase was7.1%,19.2%,25.3%respectively; epileptiform discharge rate in sleep stage Ⅲ-Ⅳ was1.1%; there was no significant difference of total sleep time between epilepsy groupand control group, there was also no significant difference of REM sleep time (P>0.05); sleep time of stage Ⅰ-Ⅱin epilepsy patients group was longer than controlgroup (293.91±27.57min vs223.17±15.28, P=0.000), sleep time of stage Ⅲ-Ⅳin epilepsy patients group was shorter than control group (50.11±12.12min vs133.96±10.77, P=0.000); besides this, asymmetric spindles have been found in26.7%of epilepsy patients, fragmented sleep architecture with a higher rate ofsleep-phase transformation have been found in43.3%of epilepsy patients.
2. In the part of exploring the relationship between the epileptiform dischargesand cognitive impairment: The index of10%of epileptiform discharges has anegative effect on cognitive function in adult epilepsy patients, the index of10%wasthe minimum study point; different index of epileptiform discharges have differentnegative impact on the cognitive function (72.13±10.3vs85.20±9.65, P=0.02); there was no difference in the different distribution of epileptiform discharges withnegative impact on cognitive function, such as focal and multifocal epileptiformdischarges, generalized epileptiform on cognitive function (WAIS-RC:86.11±11.3vs84.04±10.8, P=0.35; WMS:84.23±9.6vs82.31±10.23, P=0.35); there wasno difference in the different duration of epileptiform discharges with negativeimpact on cognitive function.
3. In the part of exploring the accuracy of CDSA, aEEG applied in theidentification of epileptic seizures: In our study, we have obtained a highersensitivity and lower misdiagnosis rate and missed diagnosis rate; when using theCDSA to interpret, the sensitivity was80%, misdiagnosis rate in24hours was low,about four times per24h; when using aEEG, the sensitivity was81.3%,misdiagnosis rate in24hours was2times per24h; when using CDSA and aEEG tointerpret, misdiagnosis rate was about4times per24h respectively, and there was nodifference between CDSA and aEEG (P>0.05, X2); besides this, when threeelectrophysiological physicians using CDSA and aEEG to interpret sensitive rate,misdiagnosis-rate and missed diagnosis rate, there was a better consistency,consistency parameters are κ=0.52and κ=0.68respectively when using CDSA andaEEG.
Conclusion：
1. In previous, routine EEG technology can be applied for the detection ofepileptiform discharges, but the structural analysis for the sleep requires the use ofsleep monitoring technology. Combing EEG technology with sleep parameters cananalyze the relationship between the epileptiform discharges and sleep-wake cycle,and can contribute to the early identification of sleep disorders in epilepsy patients,early treatment programs will be made to develop and improve their life quality.Such studies are few and no large-scale clinical studies have been foundcurrently,howecer, in our study, we have included a large amount of clinicalsamples, and various seizure types.
2.The combing EEG technology with quantitative analysis, can make a quantitative analysis of the minimum epileptiform discharges index, which can leadto impaired cognitive function in epilepsy patients,can also find potential andhidden factors of epileptiform discharges in epilepsy patients with cognitiveimpairment, for the controversial issue of clinical treatment " whether there was aneed for early intervention epileptiform discharges in order to delay or reduce thenegative impact on cognitive function " provided a theoretical basis. Such studieshave been reported domestic and foreign rarely, and have different thresholds.
3. The application of EEG trend-CDSA and aEEG in recognition of epilepticseizures has a high sensitivity, low misdiagnosis rate and missed diagnosis rate, andwhich was convenient and easier to operate, and in favor of widely application inICU by non-professional reviewers. In previous, such methods were used in themonitoring of sleep-wake cycle in newborn, neonatal cerebral function monitoringfor intensive brain injury, the monitoring of anesthesia depth, fewer studies havebeen done in adult intensive care, and showed different results.
癫痫患者常常并发有睡眠障碍、认知功能减退，严重影响其生活质量；不规律用药或感染较易诱发其出现癫痫持续状态，甚至威胁其生命。神经元异常放电是癫痫发作的基础，只有借助脑电图技术方可客观判定其异常痫样放电情况，常规脑电图操作一般不记录肌电、眼动，缺乏对睡眠结构的深入了解；对痫样放电仅能定性检测、缺乏量化的标准；此外，脑电图阅图繁琐、专业性强，不易在医护工作者间普及应用。因此，我们通过将传统脑电图技术改良，增加一些睡眠参数、定量分析方法及趋势图分析方法，能进一步探讨痫样放电与睡眠-觉醒周期关系、痫样放电与认知功能的关系、及痫样放电与频繁痫样发作的关系。
方法：
1.痫样放电与睡眠-觉醒周期的研究：我们将脑电图技术与眼动、肌电等睡眠参数结合，对200例癫痫患者及182例健康对照者进行24小时监测，记录结束后回放分析痫样放电出现方式、部位及睡眠结构、睡眠时相，并探讨二者之间的关系。
2.痫样放电与认知障碍的研究：我们对67例合并有认知障碍的癫痫患者进行24小时脑电图监测，并通过定量分析法对痫样放电指数进行分类，进而对不同痫样放电指数的癫痫患者进行认知相关性神经心理测试，并探讨二者之间的关系。
3.趋势图—CDSA、aEEG识别痫样发作准确性的研究：我们选择30条连续24小时记录的脑电图数据（20条包含有痫样发作、10条正常对照），3名经培训的电生理医师采用CDSA、aEEG阅图方法对30条脑电图记录进行解读，对疑似痫样发作之处进行标记，测试结束后与传统脑电图阅图法所判定的发作次数进行比较分析，明确敏感性、误诊率、漏诊率等，并统计分析不同阅图者之间的一致性。
结果：
1.在探讨痫样放电与睡眠-觉醒周期的研究中：我们发现约91%的癫痫患者可通过脑电图监测发现痫样放电；清醒期、睡眠期、清醒及睡眠Ⅰ-Ⅱ期的痫样放电率分别为7.1%、19.2%、25.3%，睡眠Ⅲ-Ⅳ期的痫样放电率为1.1%；癫痫组与正常对照组的总睡眠时间、REM期睡眠时间无明显差异（P＞0.05）；癫痫组与正常组比较，睡眠Ⅰ-Ⅱ期的睡眠时间延长(293.91±27.57min vs223.17±15.28, P=0.000)，睡眠Ⅲ-Ⅳ期时间缩短(50.11±12.12min vs133.96±10.77, P=0.000)；此外，26.7%的癫痫患者出现不对称性纺锤波，43.3%的癫痫患者发现较高睡眠时相转换率所致的睡眠结构片段化。
2.在探讨痫样放电与认知障碍的研究中：10%的痫样放电指数是对成年癫痫患者认知功能产生负性影响的最小研究截点；不同部位的痫样放电对认知功能产生不同的负性影响，如痫样放电位于额叶或颞叶者，显示较差的智商及记忆商；不同痫样放电分布，如局灶性痫样放电与多灶性、泛化性痫样放电对认知功能的负性影响无差异（WAIS-RC:86.11±11.3vs.84.04±10.8, P=0.35;WMS:84.23±9.6vs.82.31±10.23, P=0.35)；不同痫样放电持续时间，对认知功能的负性影响无差异。
3.在探讨趋势图—CDSA、aEEG识别痫样发作准确性的研究中：本研究获得较高的敏感性、较低的误诊率及漏诊率，采用CDSA阅图时，敏感性为80%，24小时的误诊率较低，约4次左右；aEEG阅图时，敏感性为81.3%，24小时的误诊率约2次；采用CDSA及aEEG阅图时，漏诊率均为每24小时，大约4次左右，且CDSA及aEEG两种阅图方法间，漏诊率无明显差异（P>0.05, X2）；此外三名电生理医师采用CDSA及aEEG两种阅图方法解读敏感性、误诊率、漏诊率时，一致性较好，一致性参数分别为κ=0.52及κ=0.68。
结论：
1.既往常规脑电图技术能对痫样放电进行检测分析，而睡眠结构分析需借助多导睡眠监测技术才能完成，本研究中将脑电图技术与睡眠参数相结合，同时对痫样放电与睡眠结构进行分析，建立二者之间的联系，痫样放电可以改变癫痫患者的睡眠结构，同时其睡眠结构的改变，促进痫样放电的发生，因此早期识别癫痫患者所并发的睡眠障碍、制定诊疗方案有助于更好的抑制痫样放电，控制癫痫发作，改善其生活质量。目前此类研究国内报道较少、且国内外未见大样本临床研究，而本实验临床样本量较大、且纳入的癫痫发作类型全面。
2.本研究将脑电图与定量分析法结合，在临床样本中证实痫样放电成为影响成人癫痫患者认知功能的潜在的、隐性的因素，且定量分析引起成人癫痫患者认知功能受损的最小痫样放电指数。既往癫痫常规治疗中对于临床发作次数少的癫痫患者，暂不给予药物治疗或仅给予小剂量药物治疗，不能有效抑制其痫样放电。而我们的研究可能改变传统的治疗观念，即由单纯控制癫痫的临床发作，发展为不仅控制临床发作，还需控制痫样放电，减少认知损伤，我们认为临床发作次数少，脑电图显示频繁临床下痫样放电的患者，需要早期治疗抑制痫样放电以延缓或减少对认知功能的负性影响。我们首次提出10%的痫样放电指数对成人癫痫患者认知功能存在负性影响，此类研究国内未见报道，国外有关痫样放电与认知损伤的报道较少，均在儿童癫痫患者中进行且研究阈值不同，未在成人癫痫患者中研究验证。
3.本研究证实，将脑电趋势图—CDSA及aEEG应用于痫样发作识别中，具有较高的敏感率、较低的误诊率、漏诊率，且简便快捷、可操作性强，有利于非专业医护人员应用，在成人重症病房中的推广具有应用前景。既往此种研究方法多应用于新生儿重症病房，在国内成人重症病房的应用较少，且类似研究结果不同，有一定的临床应用及推广价值。
Background and purpose：
Epilepsy patients are often complicated with sleep disorders, cognitivedysfunction, and are often induced with status epilepticus easily, which may affecttheir life-quality seriously, even threat their lives. Neurons’ abnormal discharge isthe basis for epileptic seizures, EEG technology is an objective method to detect theabnormal epileptiform discharges, on the basis of traditional EEG technology, wehave made some improvements, such as increasing the number of sleep parameters,quantitative analysis and trend analysis, in order to explore the relationship betweenepileptiform discharges and sleep-wake cycle, the epileptiform discharges andcognitive function, and also the relationship between epileptiform discharges andfrequent epileptic seizures.
Method：
1. In the part of exploring the relationship between epileptiform discharges andsleep-wake cycle: We have added sleep parameters such as eye movement and EMGto the traditonal EEG technology, and applied to the200cases of epilepsy patientsand182cases of healthy controls, after the24h-monitoring, we made an analysis ofepileptiform discharges and sleep architecture, sleep phase, then explored therelationship.
2. In the part of exploring the relationship between the epileptiform dischargesand cognitive function: We have included67cases of epilepsy patients withcognitive impairment, after the24h-EEG monitoring, we used quantitative analysismethod to define the epileptiform discharges index, and gave the cognitive-relatedneuropsychological tests to these patients with different index of epileptiformdischarges,then explored the relationship.
3. In the part of exploring the accuracy of trend-CDSA, aEEG applied in theidentification of epileptic seizures: We have selected30continuous24h EEGrecording datas (20data contained epileptic seizures,10data were normal controls),three electrophysiology physician have been trained to use CDSA and aEEG tointerpret these30EEG recordings, and marked any suspected epileptic seizure, afterthe interpretation by CDSA and aEEG, three electrophysiology physician usedconventional EEG reading to identify the real number of seizures, then comparedCDSA and aEEG with conventional EEG to determine the sensitive rate,misdiagnosis rate, missed diagnosis rate, and also made a statistical analysis ofconsistency between the different reviewers.
Results：
1. In the part of exploring the relationship between epileptiform discharges andsleep-wake cycle: We found that about91%of epilepsy patients can be found withepileptiform discharges under the EEG monitoring; the epileptiform discharges ratein waking-phase, sleep-phase, both waking and sleep stage Ⅰ-Ⅱphase was7.1%,19.2%,25.3%respectively; epileptiform discharge rate in sleep stage Ⅲ-Ⅳ was1.1%; there was no significant difference of total sleep time between epilepsy groupand control group, there was also no significant difference of REM sleep time (P>0.05); sleep time of stage Ⅰ-Ⅱin epilepsy patients group was longer than controlgroup (293.91±27.57min vs223.17±15.28, P=0.000), sleep time of stage Ⅲ-Ⅳin epilepsy patients group was shorter than control group (50.11±12.12min vs133.96±10.77, P=0.000); besides this, asymmetric spindles have been found in26.7%of epilepsy patients, fragmented sleep architecture with a higher rate ofsleep-phase transformation have been found in43.3%of epilepsy patients.
2. In the part of exploring the relationship between the epileptiform dischargesand cognitive impairment: The index of10%of epileptiform discharges has anegative effect on cognitive function in adult epilepsy patients, the index of10%wasthe minimum study point; different index of epileptiform discharges have differentnegative impact on the cognitive function (72.13±10.3vs85.20±9.65, P=0.02); there was no difference in the different distribution of epileptiform discharges withnegative impact on cognitive function, such as focal and multifocal epileptiformdischarges, generalized epileptiform on cognitive function (WAIS-RC:86.11±11.3vs84.04±10.8, P=0.35; WMS:84.23±9.6vs82.31±10.23, P=0.35); there wasno difference in the different duration of epileptiform discharges with negativeimpact on cognitive function.
3. In the part of exploring the accuracy of CDSA, aEEG applied in theidentification of epileptic seizures: In our study, we have obtained a highersensitivity and lower misdiagnosis rate and missed diagnosis rate; when using theCDSA to interpret, the sensitivity was80%, misdiagnosis rate in24hours was low,about four times per24h; when using aEEG, the sensitivity was81.3%,misdiagnosis rate in24hours was2times per24h; when using CDSA and aEEG tointerpret, misdiagnosis rate was about4times per24h respectively, and there was nodifference between CDSA and aEEG (P>0.05, X2); besides this, when threeelectrophysiological physicians using CDSA and aEEG to interpret sensitive rate,misdiagnosis-rate and missed diagnosis rate, there was a better consistency,consistency parameters are κ=0.52and κ=0.68respectively when using CDSA andaEEG.
Conclusion：
1. In previous, routine EEG technology can be applied for the detection ofepileptiform discharges, but the structural analysis for the sleep requires the use ofsleep monitoring technology. Combing EEG technology with sleep parameters cananalyze the relationship between the epileptiform discharges and sleep-wake cycle,and can contribute to the early identification of sleep disorders in epilepsy patients,early treatment programs will be made to develop and improve their life quality.Such studies are few and no large-scale clinical studies have been foundcurrently,howecer, in our study, we have included a large amount of clinicalsamples, and various seizure types.
2.The combing EEG technology with quantitative analysis, can make a quantitative analysis of the minimum epileptiform discharges index, which can leadto impaired cognitive function in epilepsy patients,can also find potential andhidden factors of epileptiform discharges in epilepsy patients with cognitiveimpairment, for the controversial issue of clinical treatment " whether there was aneed for early intervention epileptiform discharges in order to delay or reduce thenegative impact on cognitive function " provided a theoretical basis. Such studieshave been reported domestic and foreign rarely, and have different thresholds.
3. The application of EEG trend-CDSA and aEEG in recognition of epilepticseizures has a high sensitivity, low misdiagnosis rate and missed diagnosis rate, andwhich was convenient and easier to operate, and in favor of widely application inICU by non-professional reviewers. In previous, such methods were used in themonitoring of sleep-wake cycle in newborn, neonatal cerebral function monitoringfor intensive brain injury, the monitoring of anesthesia depth, fewer studies havebeen done in adult intensive care, and showed different results.
引文
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[3] Hippocrates: the sacred disease, aphorisms, and prognosis. Hippocraticwritings Penguin, Boston1983； pp:14.
[4] Sterman M, Shouse MN, Passouant PE: Historical views on sleep and epilepsy.Sleep and epilepsy, Academic Press, New York1991, Academic Press, NewYork(pp):6.
[5] Passouant, Cadilhac J, Philippot M: Rhythmicity of petit mal during sleep,generalized and localized rhythmic discharges. Rev Neurol，1951；84(6):659-663.
[6] Gibbs FA:Electroencephalography.AmJPsychiatry,1947;103(4):519-522.
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[10] LOPEZ—GOMARIZ E， HOYO-RODRIG0B． The effects of epilepticseizures on sleep architecture．Rev Neurol，2004；38：176—180．
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[2] Bonakis A, Koutroumanidis M: Epileptic discharges and phasic sleepphenomena in patients with juvenile myoclonic epilepsy. Epilepsia，2009；50(11):2434-2445.
[3] Hippocrates: the sacred disease, aphorisms, and prognosis. Hippocraticwritings Penguin, Boston1983； pp:14.
[4] Sterman M, Shouse MN, Passouant PE: Historical views on sleep and epilepsy.Sleep and epilepsy, Academic Press, New York1991, Academic Press, NewYork(pp):6.
[5] Passouant, Cadilhac J, Philippot M: Rhythmicity of petit mal during sleep,generalized and localized rhythmic discharges. Rev Neurol，1951；84(6):659-663.
[6] Gibbs FA:Electroencephalography.AmJPsychiatry,1947;103(4):519-522.
[7] Terzano MG, Mancia D, Salati MR, Costani G, Decembrino A, Parrino L: Thecyclic alternating pattern as a physiologic component of normal NREM sleep.Sleep，1985；8(2):137-145.
[8] Terzano MG, Parrino L, Fioriti G, Spaggiari MC, Piroli A: Morphologic andfunctional features of cyclic alternating pattern (CAP) sequences in normalNREM sleep. Funct Neurol，1986；1(1):29-41.
[9] Gigli GL, Calia E, Marciani MG, Mazza S, Mennuni G, Diomedi M, TerzanoMG, Janz D: Sleep microstructure and EEG epileptiform activity in patientswith juvenile myoclonic epilepsy.Epilepsia1,1992；33(5):799-804.
[10] LOPEZ—GOMARIZ E， HOYO-RODRIG0B． The effects of epilepticseizures on sleep architecture．Rev Neurol，2004；38：176—180．
[11] Temno MG，Parrino L，Anelli S，et a1．Effects of generalized interictal EEGDischarges on sleep stability assessment by means of cyclic alter．naingpattern．Epilepsia，1992；33：317—326．
[12]崇伦，张明，邓丽影等．颞叶癫痫患者的睡眠结构研究．实用医学杂志，2010；26：1329—1331．
[13]黄娟，麦坚凝，王秀英等．癫痫儿童发作间期全夜睡眠状况初步分析．中国当代儿科杂志，2007；9：6-10．
[14]高伟，吴立文．频繁的临床下癫痫样放电对睡眠结构的影响．国际神经病学神经外科学杂志，2008，35(5)：403-406．
[15] MacAllister WS,Schaffer SG.Neuropsychological deficits in childhoodepilepsy syndromes.Neuropsychol Rev,2007;17:427-444.
[16] Bhise VV, Burack GD, Mandelbaum DE. Baseline cognition, behavior, andmotor skills in children with new-onset idiopathic epilepsy. Dev Med ChildNeurol,2010;52:22-26.
[17]黄铁栓,李冰,胡雁,廖建湘等.癫痫样放电对癫痫儿童认知功能的影响.实用医学杂志,2005；21:909-910.
[18] Echenne B, Cheminal R, Rivier F, Negre C, Touchon J,Billiard M.Epileptic electroencephalographic abnormalities and developmentaldysphasias: a study of32patients. Brain Dev,1992;14:216—25.
[19] Kasteleijn-Nolst,Trenite DG,VermeirenR.The impact of subclinicalepileptiform discharges on complex tasks and cognition：relevance for aircrewand air traffic controllers.Epilepsy Behavior,2005;6:31-34.
[20] Aldenkamp AP，Beitler J，Arends J，et a1．Acute effects of subclinicalepileptiform EEG discharges on cognitive activation.Functional Neurology,2005;20：23—28．
[21] Seri S,Thai JN,Brazzo D,Pisani F,Cerquiglini A.Neurophysiology of CSWSassociated cognitive dysfunction.Epilepsia,2009;50:33-6.
[22] P.VanBogaert,C.Urbain,S.Galer,N.Ligot,P.Peigneux.The impact of focalinterictal epileptiform discharges on behaviour and cognition inchildren.Neurophysiologie Clinique/Clinical Neurophysiology,2011;42:53—58.
[23] S.Ebus,J.Arends,J.Hendriksen, E. van der Horst, N. de la Parra, R. HendriksenE. Cognitive effects of interictal epileptiform discharges in children. Europeanjournal of paediatric neurology,2012;16:697-706.
[24] Bedoin N, Herbillon V, Lamoury I, Arthaud-Garde P,Ostrowsky K, DeBellescize J, et al. Hemispheric lateralization of cognitive functions in childrenwith centrotemporal spikes.Epilepsy Behav，2006;9:268-74.
[25] Wolff M, Weiskopf N, Serra E, Preissl H, Birbaumer N, Kraegeloh-MannI.Benign partial epilepsy in childhood:selective cognitive deficits are related tothe location of focal spikes determined by combined EEG/MEG. Epilepsia，2005;46:1661-7.
[26] Volkl-Kernstock S, Willinger U, Feucht M. Spacial perception and spatialmemory in children with benign childhood epilepsy with centroetemporalspikes (BCECTS). Epilepsy Res，2006;72:39-48.
[27] Aldenkamp A,Arends J.The relative influence of epileptic EEG discharges,short nonconvulsive seizures, and type of epilepsy on cognitive function.Epilepsia,2004;45:54-63.
[28] MagantiR,Gerber,Drees C.Nonconvulsive status epilepticus． EpilepsyBehavior，2008;12：572-586．
[29] Drislane FW，Blum AS，Schemer DL．Unsuspected electrographic statusepileptieus in intensive care units．Neurology,1998;50(suppl11):395-396．
[30]王晓锋，潘速跃，陆兵勋．成人顽固性癫痫持续状态的临床分析.中华神经医学杂志,2007;6(7)：711-714．
[31] Sander L．Conquering the next frontier of ICU monitoring：the brain．NeonatalIntensive Care,2005;18(5):19-21．
[32] Scheuer ML．Continuous EEG monitoring in the intensive unite．Epilepsia，2002;43(3):114—127．
[33] Wallace B E，Wagner A K，Wagner E P，et a1．A history and review ofquantitative eIectroencephalography in traumatic brain injury．Head TraumaRehabil，2001；16：165—190.
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