Dravet综合征临床和脑电图特征及演变过程

Clinical-electroencephalogram characteristics and its evolutionary process of Dravet syndrome

目的 分析Dravet综合征的临床和脑电图特征及演变过程,以改善对本病的早期诊断与合理治疗.方法 分析50例Dravet综合征儿童各种发作类型的起病年龄、诱因、各年龄段发作特征及其与脑电图演变过程的关系.结果 患儿平均起病年龄（5.5±1.9）个月,病程中持续存在热敏感现象.早期以全面性、一侧性或局灶性惊厥发作为主,以后出现肌阵挛、失神等多种发作类型.出现肌阵挛发作的平均年龄（M50）为16个月,13例（26%）无肌阵挛发作.患儿1岁以内脑电图36例次（76%）正常,在1～2岁期间尽管临床出现多种形式发作,但脑电图异常放电出现率仅在50%左右.3岁以后脑电图背景和异常放电出现率均在90%以上.5/18例（28%）有光敏性反应伴肌阵挛发作.结论 Dravet综合征病程早期脑电图与临床发作呈现不平行的进展过程,2岁之前常表现为临床发作严重而脑电图异常率较低.3岁以后各种脑电图异常特征逐渐充分表现.认识Dravet综合征这种临床和脑电图特征有助于早期做出临床诊断,筛选进行SCN1A基因检测的病例.

Objective To analyze the clinical and electroencephalogram （EEG） characteristics as well as its evolutionary process of Dravet syndrome （DS） in order to improve early diagnosis and appropriate treatment.Methods Fifty patients with DS were studied including onset age, trigger factors, seizure types on different age stages and relationship with EEG characteristics and its evolution process.Results The average age of seizure onset was （ 5.5 ± 1.9 ） months.The fever sensitivity continuously existed in the entire course of disease.In the early stage, generalized tonic-clonic seizures （GTCS） and focal or unilateral seizures were main types.Multi seizure types included myoclonic seizures （MS） and atypical absence occurred later.The onset ages of MS were average （M50） of 16 months.MS never occurred in 26% of the patients.During the first year of life, EEGs were normal in 76% of these patients.The epileptiform discharges only recorded in about 50% of the patients in spite of multi seizure types had presented.After three years ago, both EEG background abnormalities and discharges occurred in more 90% of the all patients.Photosensitivity response with MS occurred in the 28% of 18 patients.Conclusions The clinical and EEG are not parallel progressively process in early stage of DS.The children often express more severe clinical seizures than EEG abnormalities until 2 years of age.Various abnormal EEG manifestation obviously display gradually after 3 years age.Precise recognizing with the clinical and EEG characteristics of DS will help get correct early diagnosis and screen the candidate cases to test SCN1A gene.