本文選題：阻塞性睡眠呼吸暫停低通氣綜合征 + 腦電�。� 參考：《天津醫(yī)科大學(xué)》2017年碩士論文

【摘要】：研究目的阻塞性睡眠呼吸暫停低通氣綜合征(Obstructive Sleep Apnea-hypopnea Syndrome,OSA)是一種睡眠障礙疾病,常伴隨著心腦血管疾病的發(fā)生,嚴(yán)重?fù)p害患者的身心健康和認(rèn)知功能。多導(dǎo)睡眠監(jiān)測(cè)(Polysomnogram,PSG)是目前臨床檢測(cè)OSA的常用手段,但PSG在描述OSA睡眠障礙的內(nèi)在機(jī)制方面存在局限性。因此,本論文在OSA患者PSG監(jiān)測(cè)的基礎(chǔ)上,以O(shè)SA多通道睡眠腦電(Electroencephalographs,EEGs)為研究對(duì)象,定量研究OSA患者在不同睡眠期EEGs神經(jīng)振蕩的異常模式,進(jìn)而探索OSA睡眠EEGs網(wǎng)絡(luò)的連接缺損機(jī)制,為OSA的臨床診斷、治療和發(fā)病機(jī)制研究提供新的研究思路和技術(shù)支持。研究方法1.受試者分組制定OSA入組標(biāo)準(zhǔn),OSA組由10名符合入組標(biāo)準(zhǔn)的OSA患者組成,正常對(duì)照(Control)組由10名正常受試者組成,兩組受試者在年齡、性別、教育程度上相匹配。所有受試者均來自天津醫(yī)科大學(xué)總醫(yī)院呼吸科睡眠診療中心。2.PSG指標(biāo)兩組受試者PSG監(jiān)測(cè)指標(biāo)如下:呼吸暫停低通氣指數(shù)(Apnea/Hypopnea Index,AHI),氧飽和度低于90%的時(shí)間占監(jiān)測(cè)時(shí)間的百分比(Percent of Time in Saturation Lower 90%,%TST90%),最低血氧飽和度(Minimal Pulse Oxygen Saturation,minSaO2),平均血氧飽和度(Average Oxyhemoglobin Saturation,meanSaO2),氧減指數(shù)(Oxygen Desaturation Index,ODI),微覺醒指數(shù)(Arousal Index,AI)。3.記錄睡眠EEGs記錄每名受試者在5個(gè)睡眠期:閉目清醒期(Wake Period,W)、睡眠Ⅰ期(Non-REM Sleep Stage 1,N1)、睡眠Ⅱ期(Non-REM Sleep Stage 2,N2)、睡眠Ⅲ期(Non-REM Sleep Stage 3,N3)和快速眼動(dòng)期(Rapid-eye Movement Sleep Stage,R)有效的16通道EEGs數(shù)據(jù),每期各10段,每段數(shù)據(jù)長為10 s。4.預(yù)處理原始記錄EEGs數(shù)據(jù)原始記錄EEGs數(shù)據(jù)去除基線漂移、工頻干擾和肌電、眼電、心電造成的噪聲和偽跡等。5.研究OSA睡眠EEGs振蕩的特征模式應(yīng)用快速傅里葉變換(Fast Fourier Transform,FFT)方法,計(jì)算OSA組和Control組在5個(gè)睡眠期EEGs各個(gè)頻段(Delta、Theta、Alpha、Beta、Gamma)的平均能量密度,定量描述EEGs在各個(gè)頻段的神經(jīng)振蕩。統(tǒng)計(jì)比較兩組EEGs能量密度差異,研究OSA EEGs振蕩的特征睡眠期、特征頻段和特征腦區(qū)。6.研究OSA睡眠EEGs網(wǎng)絡(luò)連接的特征模式應(yīng)用頻域Granger因果分析方法,計(jì)算OSA組和Control組在5個(gè)睡眠期EEGs各個(gè)頻段的定向傳遞函數(shù)(Directed Transfer Function,DTF),定量描述EEGs在各個(gè)頻段因果網(wǎng)絡(luò)的連接強(qiáng)度。統(tǒng)計(jì)比較兩組DTF連接值差異,研究OSA EEGs網(wǎng)絡(luò)連接的特征睡眠期、特征頻段和特征腦區(qū)。7.統(tǒng)計(jì)學(xué)分析應(yīng)用SPSS 22.0統(tǒng)計(jì)分析軟件對(duì)數(shù)據(jù)進(jìn)行獨(dú)立樣本t檢驗(yàn),計(jì)量資料用均值±標(biāo)準(zhǔn)誤(Mean±SEM)表示,相關(guān)性分析采用Pearson直線相關(guān)分析。研究結(jié)果1.OSA的PSG指標(biāo)特征OSA的PSG監(jiān)測(cè)結(jié)果顯示全夜睡眠過程中的minSaO2、meanSaO2顯著低于Control組,%TST90%、ODI指數(shù)及AI指數(shù)顯著高于Control組,差異具有統(tǒng)計(jì)學(xué)意義(P0.05)。2.OSA睡眠EEGs振蕩的特征模式(1)OSA在W期Delta頻段,額區(qū)和中央?yún)^(qū)的EEGs能量密度比Control組顯著增大(P0.01);在Alpha頻段,頂區(qū)和枕區(qū)的EEGs能量密度比Control組顯著減低(P0.05)。(2)OSA在N1期Delta頻段,額區(qū)和中央?yún)^(qū)的EEGs能量密度比Control組顯著增大(P0.01)。(3)OSA在N3期Delta頻段和Theta頻段,中央?yún)^(qū)的EEGs能量密度比Control組顯著增大(P0.05)。3.OSA睡眠EEGs網(wǎng)絡(luò)連接的特征模式(1)OSA在W期Gamma頻段,額區(qū)的EEGs平均DTF值比Control組顯著增大(P0.05);在Gamma頻段中央?yún)^(qū)的EEGs平均DTF值比Control組顯著減小(P0.05)。(2)OSA在N1期Beta頻段,中央?yún)^(qū)的EEGs平均DTF值比Control組顯著增大(P0.05)。(3)OSA在N3期Beta頻段,中央?yún)^(qū)的EEGs平均DTF值比Control組顯著增大(P0.05)。研究結(jié)論1.PSG監(jiān)測(cè)結(jié)果提示OSA主要睡眠障礙表現(xiàn)為低氧損傷和睡眠結(jié)構(gòu)紊亂。2.OSA發(fā)生睡眠障礙的特征睡眠期為W期、N1期和N3期。3.OSA在W期EEGs的神經(jīng)振蕩在Delta頻段增強(qiáng),在Alpha頻段減弱,提示OSA患者在清醒時(shí)常處于思睡狀態(tài),腦電呈現(xiàn)慢波化,警覺水平下降;OSA在N1期、N3期EEGs的神經(jīng)振蕩在Delta和Theta頻段增強(qiáng),提示OSA在睡眠狀態(tài)下的EEGs振蕩發(fā)生慢波化改變,慢波抑制機(jī)制喪失,可能與OSA睡眠中喚醒反應(yīng)能力下降,大腦覺醒功能損傷有關(guān)。4.OSA W期EEGs網(wǎng)絡(luò)功能連接在Gamma頻段增強(qiáng),提示OSA患者清醒狀態(tài)下腦功能連接代償性增強(qiáng),可能為維持注意、警覺等正常腦功能所做的代償性調(diào)節(jié);OSA N1期、N3期EEGs網(wǎng)絡(luò)功能連接在Beta頻段增強(qiáng),可能與睡眠呼吸暫停過程中大腦對(duì)呼吸肌的調(diào)節(jié)控制努力有關(guān),反映了OSA睡眠狀態(tài)下為彌補(bǔ)感覺運(yùn)動(dòng)功能缺陷的代償機(jī)制。5.OSA發(fā)生睡眠EEGs振蕩異常與網(wǎng)絡(luò)連接異常的腦區(qū)主要集中在額區(qū)和中央?yún)^(qū),提示OSA睡眠EEGs模式的改變可能與其額區(qū)、中央?yún)^(qū)的結(jié)構(gòu)和功能損傷有關(guān)。
[Abstract]:Objective obstructive sleep apnea hypopnea syndrome (Obstructive Sleep Apnea-hypopnea Syndrome, OSA) is a kind of sleep disorder, often accompanied by the occurrence of cardiovascular and cerebrovascular diseases, which seriously damage the physical and mental health and cognitive function of the patients. Polysomnogram (PSG) is a common means of clinical detection of OSA at present. But PSG has limitations in describing the internal mechanism of OSA sleep disorder. Therefore, on the basis of PSG monitoring in OSA patients, this paper uses OSA multichannel sleep electroencephalogram (Electroencephalographs, EEGs) as the research object to quantitatively study the abnormal mode of EEGs nerve ringing in OSA patients during different sleep periods, and then explore the connection of OSA sleep EEGs network. The mechanism of defect connection provides new research ideas and technical support for the clinical diagnosis, treatment and pathogenesis of OSA. Methods 1. subjects were divided into groups to set up a standard of OSA group, group OSA was composed of 10 OSA patients who met the standard of entry group, and the normal control group (Control) was composed of 10 normal subjects, and the two subjects were in age, sex, education. All subjects were from the two group of.2.PSG indicators in the sleep diagnosis center of General Hospital Affiliated to Tianjin Medical University Department of respiration. The PSG monitoring indexes of the two groups were as follows: the apnea hypopnea index (Apnea/Hypopnea Index, AHI), the percentage of oxygen saturation less than 90% (Percent of Time in Saturation Lower 90%,%) TST90%), the lowest blood oxygen saturation (Minimal Pulse Oxygen Saturation, minSaO2), the average blood oxygen saturation (Average Oxyhemoglobin Saturation, meanSaO2), the oxygen subtraction index (Oxygen Desaturation), the micro awakening index recorded in the 5 sleep periods of each subject. ), sleep phase I (Non-REM Sleep Stage 1, N1), sleep stage II (Non-REM Sleep Stage 2, N2), sleep stage III (Non-REM Sleep Stage 3, N3) and rapid eye movement 16 channel data, each period of 10 segments, each segment of the data is 10 Baseline drift, frequency interference and EMG, electromyography, noise and artifacts caused by electrocardiography, the.5. study of the characteristic patterns of OSA sleep EEGs oscillations using the fast Fourier transform (Fast Fourier Transform, FFT) method to calculate the average energy density of OSA and Control groups at each of the 5 sleep periods (Delta, Theta, etc.). The neural oscillations of EEGs in each frequency band. Compare the difference of the two groups of EEGs energy density, study the characteristic sleep period of the OSA EEGs oscillation, the characteristic frequency and the characteristic brain region.6. study OSA sleep EEGs network connection characteristic pattern using the frequency domain Granger causality analysis method, and calculate the orientation of the OSA group and Control group in the 5 sleep EEGs frequency bands. Directed Transfer Function (DTF), quantificationally describe the connection strength of EEGs in each frequency and effect network, compare the difference between two groups of DTF connection values, study the characteristic sleep period of OSA EEGs network connection, the characteristic frequency and the statistical analysis of the characteristic brain region, and apply the SPSS 22 statistical analysis software to carry out the independent sample t test of the data. The measurement data were expressed with mean standard error (Mean + SEM), and correlation analysis used Pearson linear correlation analysis. The results of PSG monitoring of OSA of PSG index of 1.OSA showed that meanSaO2 was significantly lower than Control group and%TST90%, and the ODI index and index index were significantly higher than those in the group, and the difference was statistically significant. The characteristic mode of EEGs oscillation of P0.05.2.OSA sleep (1) OSA in W phase Delta band, EEGs energy density in the frontal and central regions is significantly higher than that of Control group (P0.01), and the EEGs energy density in the Alpha band, the top and the occipital region is significantly lower than that of the Control group. (2) the energy density of the frontal and central regions is more than that of the Control. The group was significantly increased (P0.01). (3) OSA in the N3 phase Delta band and Theta band, the EEGs energy density in the central region was significantly higher than that in the Control group (P0.05) in the.3.OSA sleep EEGs network connection model (1) OSA in the W phase, and the average value of the frontal region was significantly higher than that of the Control group. Group ol decreased significantly (P0.05). (2) the average EEGs DTF value in the central region was significantly higher than that of the Control group (P0.05) at the Beta band of the N1 phase (P0.05). (3) OSA was in N3 Beta band, and the mean value of the central region was significantly higher than that of the Control group. The characteristic sleep period of SA is W phase, and the nervous oscillation of EEGs in phase N1 and N3 phase is enhanced at the Delta frequency, and the Alpha frequency is weakened. It suggests that the OSA patients are often in the sleep state, the electroencephalogram presents slow wave, and the alert level drops. The EEGs oscillation in the state of sleep may change slowly, the mechanism of slow wave inhibition is lost, and the arousal response ability in OSA sleep may be reduced. The impairment of the brain awakening function is related to the enhancement of the Gamma band in the EEGs network of the.4.OSA W phase, suggesting that the brain function connection is compensatory in the sober state of the OSA patients, which may be the maintenance of attention and vigilance. Compensatory regulation such as normal brain function; OSA N1 phase, N3 phase EEGs network function connection is enhanced in the Beta band, may be related to the control efforts of the brain in the process of sleep apnea, reflecting the compensatory mechanism of OSA sleep to compensate for the dysfunction of sensory motor function.5.OSA to occur sleep EEGs oscillation abnormal and net The abnormal cerebral regions of the collaterals are mainly concentrated in the frontal and central areas, suggesting that the changes in the EEGs pattern of OSA sleep may be related to the structural and functional impairment in the central area.

【學(xué)位授予單位】：天津醫(yī)科大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R766

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