本文選題：PICU + 昏迷　； 參考：《吉林大學》2017年碩士論文

【摘要】：背景及目的:判明昏迷患兒預后和識別癲癇發(fā)作都是PICU經(jīng)常面臨的臨床難題。本研究評估定量腦電圖CDSA對PICU昏迷患兒的預后價值及其在癲癇發(fā)作監(jiān)測方面的作用,以期建立簡單直觀的PICU床旁腦功能CDSA監(jiān)測方法。方法:1)收集我院PICU住院且符合入組標準的昏迷患兒42例,在入院3天內(nèi)首先進行Glasgow(GCS)評分,然后腦電監(jiān)測儀記錄CDSA不少于16h,隨訪3個月為終點。依據(jù)兒童腦功能分類量表,將正常、輕度殘疾、中度殘疾歸為預后良好組(n=21),將嚴重殘疾、昏迷或植物狀態(tài)、腦死亡、臨床死亡歸為預后不良組(n=21)�；胤臗DSA和原始腦電圖數(shù)據(jù),從背景活動、醒睡周期、睡眠分期、藥物性快波、雙側(cè)大腦半球?qū)ΨQ性等方面評估,并通過建立受試者工作特征曲線(Receiver Operating Characteristic,ROC)與GCS評分比較,對比兩種方法對預后的評估效力。2)選取小兒神經(jīng)科腦電室日常27次視頻腦電圖記錄,經(jīng)傅里葉轉(zhuǎn)化為4h/屏的CDSA圖形,選取其中27張,標記出共256次區(qū)別于背景的圖形改變,其中109處為發(fā)作事件,147處為對照。選取6名受試者(腦電圖醫(yī)生1名、腦電圖技師1名、分別對照PICU醫(yī)生2名、PICU護士2名),經(jīng)2h包括CDSA基本原理、發(fā)作期圖形、識別偽差等方面的培訓后,在不接觸原始腦電圖數(shù)據(jù)的情況下,分別對27張CDSA圖形中的256次圖形改變進行判讀,標記癇樣發(fā)作事件,分析上述受試者判斷發(fā)作性事件的一致性、漏判率、誤判率及發(fā)生錯誤原因。結(jié)果:1)昏迷患者共42例,男女各21例,平均年齡89.81±46.39月。預后良好組21例,預后不良組21例,預后不良率50%。不同預后之間性別、年齡和病因構成無統(tǒng)計學差異(P0.05)。研究表明,與預后相關的因素包括醒睡分期、睡眠分期、藥物性快波和CDSA分型。Logistic回歸分析顯示,醒睡周期是影響昏迷預后的獨立危險因素。以預后不良為金標準,醒睡周期、GCS評分構建ROC曲線,結(jié)果表明,醒睡周期對判斷昏迷患兒預后不良的效力優(yōu)于GCS評分。2)6受試者應用CDSA圖形識別癲癇發(fā)作的正確次數(shù)平均為82.6±3.5,敏感性為75.7%左右,其中癲癇持續(xù)狀態(tài)均被正確識別。6人平均遺漏率約為24.1%,平均遺漏次數(shù)為26.3次,應用CDSA圖形判讀發(fā)作性事件的特異性達80%。經(jīng)秩合檢驗比較,受試者間的敏感性和特異性無統(tǒng)計學差異(P0.05)。結(jié)論:1)CDSA圖形中背景活動的可變化型、醒睡周期、睡眠分期、對藥物具有反應性與昏迷患兒預后良好密切相關;無光譜型、單一慢型與昏迷患兒死亡密切相關。無醒睡周期是昏迷患兒預后不良的獨立危險因素。醒睡周期對預后的評估效力優(yōu)于GCS評分。2)CDSA識別癲癇發(fā)作具有中等敏感性,較低的誤判率和漏判率。PICU醫(yī)護人員經(jīng)短期培訓后即可達到較為理想的判讀能力,PICU使用CDSA監(jiān)測昏迷患兒腦功能具有應用前景和可行性。
[Abstract]:Background and objective: to identify the prognosis and identify epileptic seizures in children with coma are often the clinical problems faced by PICU. The purpose of this study was to evaluate the prognostic value of quantitative electroencephalogram (CDSA) in children with PICU coma and its role in monitoring epileptic seizures in order to establish a simple and intuitive CDSA monitoring method for PICU bedside brain function. Methods 42 cases of coma children who were admitted to our hospital with PICU were collected. Glasgow GCSs were scored within 3 days of admission, then CDSA was recorded by EEG monitor for no less than 16 hours, and followed up for 3 months as the end point. According to the children's brain function scale, normal, mild and moderate disability were classified as good prognosis group, severe disability, coma or vegetative state, brain death and clinical death were classified as poor prognosis group. CDSA and original EEG data were replayed and evaluated from background activity, sleep cycle, sleep stage, drug fast wave, bilateral cerebral hemispheres symmetry, and compared with GCS score by establishing receiver Operating characteristic roc. To compare the effectiveness of two methods in evaluating prognosis. 2) 27 times of daily video EEG records were recorded in the electroencephalogram (EEG) of the neurologic department of children, which were transformed into CDSA images of 4h/ screen by Fourier transform, and 27 of them were selected to mark out a total of 256-times image changes different from the background. Of these, 109 were seizures and 147 were controls. Six subjects (1 EEG doctor and 1 EEG technician) were selected and compared with 2 nurses in PICU. After 2 hours' training including basic principles of CDSA, pattern of attack period, identification of pseudo-error, etc. In the absence of contact with the original EEG data, the changes of 27 CDSA images were interpreted, and the epileptiform seizure events were labeled. The consistency of judging the paroxysmal events and the rate of missing judgment were analyzed. Error rate and cause of error. Results there were 42 comatose patients, 21 males and 21 males, with an average age of 89.81 鹵46.39 months. There were 21 cases in good prognosis group and 21 cases in poor prognosis group, the rate of poor prognosis was 50%. There was no significant difference in sex, age and etiological composition among different prognosis (P 0.05). The results showed that the prognostic factors included sleep stage, drug fast wave and CDSA classification. Logistic regression analysis showed that sleep cycle was an independent risk factor for coma prognosis. With poor prognosis as the gold standard, the ROC curve was constructed by waking and sleeping cycle. The results showed that, The effectiveness of waking and sleeping cycle in judging the poor prognosis of coma children was better than that in the subjects with GCS score. 2The correct times of using CDSA pattern to identify epileptic seizures were 82.6 鹵3.5 on average, and the sensitivity was about 75.7%. The average rate of omission was about 24.1and the average number of omissions was 26.3. The specificity of interpreting paroxysmal events with CDSA pattern was 80%. There was no significant difference in sensitivity and specificity among subjects by rank test (P 0.05). Conclusion the changes of background activity, sleep cycle, sleep stage, drug reactivity and prognosis of coma children are closely related to the changes of background activity in the CDSA pattern of 1: 1 CDSA, while the absence of spectrum type and the single slow type are closely related to the death of the comatose children. Unawake sleep cycle is an independent risk factor for poor prognosis in coma children. The effectiveness of sleep cycle in evaluating prognosis was better than that in GCS score. 2CDSA was of moderate sensitivity in the identification of epileptic seizures. The lower misjudgment rate and missed judgment rate. After short-term training, the medical staff in PICU can achieve a more ideal interpretation ability. The application prospect and feasibility of using CDSA to monitor brain function of coma children in PICU.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R720.597

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1 劉桂苓;彩色密度譜陣列在昏迷患兒早期預后評估和識別癇樣發(fā)作中的應用[D];吉林大學;2017年

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