【摘要】：心臟驟停(cardiac arrest，CA)，又稱心源性猝死(sudden death)是指心臟的機(jī)械活動停止，同時左心室收縮不足或停止收縮。在美國每年大約有22.5萬人死于院外(Out-of-hospital)心源性猝死，同時每年約有37～75萬住院病人因心臟驟停實(shí)施心肺復(fù)蘇術(shù)(cardiopulmonary resuscitation，CPR)。我國雖然還沒有確切的心源性猝死的流行病學(xué)資料，但專家估計(jì)這個數(shù)字會達(dá)到每年600萬人。 由于心臟驟停常是冠心病的首發(fā)表現(xiàn)形式，有效的心肺復(fù)蘇是搶救這類患者的唯一途徑。心肺復(fù)蘇是通過對心臟驟停的快速識別和積極搶救，人工重建或恢復(fù)自主呼吸與循環(huán)，避免發(fā)生心肺腦功能不全�？焖俨扇』旧С�(basic life support，BLS)是心肺復(fù)蘇成功的關(guān)鍵。 心臟驟停有兩種不同的形式。一種是由于節(jié)律失常引起的心臟驟停(dysarhithmic cardiac arrest)，另一種是因?yàn)楹粑Ｖ挂鸬男呐K驟停(asphyxial or respiratory cardiac arrest)。前一種類型的心臟驟停患者大都出現(xiàn)心室顫動(ventricular fibrillation，VF)，而后一類心臟驟停則是由于溺死、藥物過量或外傷引起，只有約5％～15％的患者出現(xiàn)心室顫動。對前一類型的患者強(qiáng)調(diào)早期除顫和即時的心肺復(fù)蘇，而對后一種類型的患者則需要實(shí)施有效的胸外按壓和人工通氣治療。 目前心肺復(fù)蘇有效的搶救成功率依然很低，只有對其不斷改進(jìn)才有可能降低死亡率，這主要是由于以下三個原因引起的。(1)心肺復(fù)蘇開始得比較晚，包括胸外按壓和人工通氣。(2)胸外按壓的效率較低以及頻繁間斷。(3)電擊除顫不及時造成搶救時機(jī)的延誤。 心室顫動如不及時去除可在數(shù)分鐘內(nèi)轉(zhuǎn)為心室靜止(asystole)。為了增加早期除顫的機(jī)會，盡量縮短除顫時間，體外自動除顫儀(automatic external defibrillator, AED)應(yīng)運(yùn)而生。AED的最大特點(diǎn)是提高了電擊除顫的自動化程度，是專為非醫(yī)務(wù)人員和初級救生員設(shè)計(jì)使用的，其識別心室顫動的敏感性與特異性均超過94％。搶救人員只要發(fā)現(xiàn)患者意識喪失，無脈搏就可將AED置于患者的胸壁上并啟動開關(guān)，AED感知心電信號，如能識別出室性心動過速(Ventricular Tachycardia，VT)，或心室顫動，就可自動除顫。應(yīng)用AED后的研究顯示，與單純的基礎(chǔ)生命支持相比可明顯提高存活率。美國AHA和IAFC已要求每輛急救車和消防車均需配備AED。隨著AED的推廣和普及，可以期望更多的生命將會被挽救。 由于心臟驟�；颊呓^大部分(60％-70％)發(fā)生在院前，而且在常溫下心臟停搏5分鐘后腦細(xì)胞即可發(fā)生不可逆損害，10分鐘后腦細(xì)胞死亡。在此期間如果不實(shí)施心肺復(fù)蘇術(shù)，則心臟的電活動就會逐漸消失，最后出現(xiàn)心室靜止，心電圖出現(xiàn)一條直線。心肺復(fù)蘇和藥物治療可能會增加缺血心肌的血液和氧氣循環(huán)，，從而將心室靜止轉(zhuǎn)變?yōu)樾氖翌潉樱蠓娇呻姄舫�。因心室靜止和心室顫動期間心臟停止收縮，因此無法檢測到脈搏信號。如果心臟只存在心肌的電活動而沒有相應(yīng)的機(jī)械收縮，則稱為心電機(jī)械分離(electromechanical dissociation，EMD)或無脈搏心電活動(pulseless electrical activity, PEA)。這種情況常會出現(xiàn)在藥物治療或心肺復(fù)蘇但沒有實(shí)施電擊除顫，或由心室顫動轉(zhuǎn)變?yōu)樾氖异o止的過程中。 目前心肺復(fù)蘇有一個標(biāo)準(zhǔn)的操作指南(the international guidelines)，它根據(jù)對呼吸、脈搏以及心電節(jié)律的檢測來確定相應(yīng)的復(fù)蘇措施。而目前使用的AED只能根據(jù)患者的心電波形做出相應(yīng)的節(jié)律分析決定是否需要電擊除顫，其它如呼吸檢測、脈搏檢查等均需要由目擊者或搶救人員來判斷。為實(shí)現(xiàn)心肺復(fù)蘇的全自動化，目前仍需要解決以下一些問題： (1)胸外按壓過程中的心電節(jié)律識別。心臟驟�；颊叩拇婊盥孰S心室顫動持續(xù)時間的延長而迅速降低，平均每分鐘下降約7％～10％。當(dāng)施行電擊除顫的時間延遲10～12分鐘以上時，存活的可能性幾乎為零。盡早應(yīng)用基礎(chǔ)的心肺復(fù)蘇，并盡快實(shí)施電擊除顫，可有效提高心臟驟�；颊叩拇婊盥�。但目前使用的體外自動除顫儀在實(shí)施電擊除顫之前需要反復(fù)進(jìn)行節(jié)律分析。否則如果將正常的非除顫心室搏動節(jié)律誤判為除顫節(jié)律，并實(shí)施不必要的電擊，那么將會對病人的心臟產(chǎn)生極大的損傷，并導(dǎo)致嚴(yán)重的后果。因此為確保心室顫動的正確識別，在節(jié)律分析期間，必須停止對病人的胸外按壓和通氣過程。這一過程大約需要12至20秒的時間。在這一過程中，電擊除顫的成功率因?yàn)槭翌潟r間的延長而大大降低，尤其是在院外病人的復(fù)蘇期間。因此如果能有一種比較可靠的心室顫動節(jié)律識別算法，即使是在對病人實(shí)施胸外按壓期間也能對心電波形進(jìn)行可靠分析，那么病人存活的幾率將會得到有效提高。 (2)胸外心臟按壓的有效性監(jiān)測分析。胸外心臟按壓的質(zhì)量也是成功復(fù)蘇的關(guān)鍵，包括按壓深度、按壓頻率和胸廓的回彈程度。尤其的恰當(dāng)?shù)陌磯荷疃�，它是保持一定冠狀動脈灌注壓(coronary perfusion pressure，CPP)的關(guān)鍵。但是，研究表明許多心臟驟�；颊咴谛姆螐�(fù)蘇過程中沒有得到有效的胸外按壓，主要表現(xiàn)在按壓頻率較低、按壓深度不足以及沒有保持適當(dāng)?shù)难h(huán)血流。而在院外急救過程中，胸外按壓由于沒有得到有效的監(jiān)測，整個過程就只能靠搶救者的感覺和視覺判斷。隨著復(fù)蘇過程的進(jìn)行，急救人員急需了解胸外按壓的效果以及由此產(chǎn)生的病人心臟血流的變化，從而實(shí)施進(jìn)一步的治療，包括優(yōu)化電擊除顫或繼續(xù)胸外按壓治療。 (3)實(shí)時呼吸及脈搏檢測。在過去的20年里，心室顫動或室性心動過速在心臟驟停中出現(xiàn)的比例逐漸下降，已經(jīng)低于50％，而無脈搏心電活動PEA及其它類型的心臟驟停所占比例并沒有改變。心室顫動的下降通過心室靜止增加得以補(bǔ)償。這就要求第一目擊者或急救人員快速判斷病人在失去意識的情況下，是否具有呼吸、脈搏或者足夠的血液循環(huán)。但這兩項(xiàng)指標(biāo)的檢測對院外急救來說卻非常困難。因?yàn)閭鹘y(tǒng)脈搏檢測是通過感觸病人頸動脈的搏動來實(shí)現(xiàn)的，呼吸檢測則是通過貼近病人嘴部感覺呼吸氣流和觀察胸腔的變化來實(shí)現(xiàn)。這些適用于普通人群的方法，很難應(yīng)用于心跳和呼吸極其微弱的冠心病患者。若不能準(zhǔn)確地檢測呼吸與脈搏，就不能正確區(qū)分由于節(jié)律失常和窒息引起的心臟停搏，并實(shí)施正確的復(fù)蘇措施。 針對以上心肺復(fù)蘇過程中的問題，我們擴(kuò)展了目前AED使用的心電采集及除顫電極功能，利用一對胸前除顫電極實(shí)現(xiàn)心電信號與胸阻抗信號的采集分析。通過對按壓過程中心電信號的分析實(shí)現(xiàn)對胸外按壓效果的監(jiān)測，通過對胸阻抗信號的處理實(shí)現(xiàn)微弱呼吸與脈搏信號的檢測，實(shí)現(xiàn)了心肺復(fù)蘇的自動化實(shí)現(xiàn)方案，其中的主要算法包括： (1)不間斷胸外按壓過程中的心電節(jié)律識別算法。采用基于連續(xù)小波變換及形態(tài)一致性評估的分析方法實(shí)現(xiàn)對心電信號的節(jié)律識別。通過對心電信號中R波形態(tài)一致性的量化分析，可以區(qū)別規(guī)則性心電節(jié)律(organized rhythm)和不規(guī)則心電節(jié)律(disorganized rhythm)。對于規(guī)則性心電節(jié)律，通過連續(xù)小波變換中R波峰值出現(xiàn)的頻率來估計(jì)心率的變化，以區(qū)別室性心動過速與正常節(jié)律。而對于不規(guī)則性心電信號，則通過幅度頻率譜面積分析來區(qū)分心室顫動與心室靜止。 (2)胸外按壓有效性的監(jiān)測與電擊除顫的優(yōu)化算法。早期對胸外按壓有效性的監(jiān)測通過對心室顫動信號的幅度分析來實(shí)現(xiàn)。此后動物與臨床實(shí)驗(yàn)研究表明，心室顫動信號的頻率與CPP呈相關(guān)性。但由于心電信號的幅度與頻率均因病人的個體差異而對實(shí)驗(yàn)結(jié)果有較大的影響。本研究小組將心電信號的幅度與頻率相結(jié)合，提出了一種基于幅度頻率譜面積的分析方法，它定義為一定頻帶寬度下信號功率譜所包含的面積。我們期望這種用于對電擊除顫優(yōu)化分析的方法可擴(kuò)展應(yīng)用于對胸外按壓有效性的實(shí)時監(jiān)測中。 (3)實(shí)時呼吸及脈搏檢測分析算法。利用心電檢測／除顫用電極提取的胸阻抗信號由兩部分組成：一是包含了頻率較低但幅度較高的呼吸阻抗信號，二是頻率略高但幅度較低的反映心臟機(jī)械活動的心阻抗信號。我們用心電信號作為參考，利用自適應(yīng)濾波器將呼吸阻抗信號和心阻抗信號相分離。最后用峰值檢測算法利用檢測到的心阻抗信號幅度，判斷檢測脈搏信號的有無，并用呼吸阻抗信號的幅度估計(jì)潮氣量的大小，從而確定呼吸的類別。 為檢驗(yàn)這些算法的有效性，我們對不同的算法進(jìn)行了相應(yīng)的實(shí)驗(yàn)設(shè)計(jì)與臨床實(shí)驗(yàn)。對用AED記錄的232例院外心臟驟停患者的心電信號分析結(jié)果表明，所提出的自動心電節(jié)律分析算法可以實(shí)現(xiàn)在胸外按壓不間斷情況下對心電節(jié)律的可靠分析。對除顫信號的檢測敏感率為93％，特異性為89％。在一組由心律失常引起的心臟驟停動物模型中，幅度頻率譜面積分析與CPP分析結(jié)果具有良好的相關(guān)性，并且對電擊除顫結(jié)果的預(yù)測具有較高的準(zhǔn)確性。在另一個由窒息引起的心臟驟停動物模型中，由心臟機(jī)械活動引起的心阻抗信號變化與脈搏電壓具有良好的相關(guān)性，而由呼吸引起的呼吸阻抗信號的變化則與呼吸潮氣量的變化正相關(guān)。 臨床研究結(jié)果表明，通過對脈搏及呼吸信號的無創(chuàng)檢測，本研究提出的算法能夠正確地區(qū)分因心律失常和窒息引起的不同類型的心臟驟停，從而及時地提示急救人員實(shí)施相應(yīng)的復(fù)蘇方案。而在不間斷胸外按壓情況下對心電節(jié)律的實(shí)時分析，則有效地避免了因節(jié)律分析造成的延誤，提高患者的存活率，同時可以避免不必要或不成功的電擊除顫，較好地解決了當(dāng)前心肺復(fù)蘇過程中存在的不足，實(shí)現(xiàn)了心肺復(fù)蘇的全自動化。
[Abstract]:Cardiac arrest (CA), also known as sudden cardiac death (sudden death) refers to the mechanical activity of the heart, and the left ventricular systolic and contractile contraction. In the United States, about 225 thousand people die of sudden cardiac death outside the hospital (Out-of-hospital) in the United States each year, and about 37~75 million hospitalized patients undergo cardiopulmonary resuscitation every year because of cardiac arrest. (cardiopulmonary resuscitation, CPR). Although there is no exact epidemiological data on sudden cardiac death in China, experts estimate that this number will reach 6 million people a year.
Cardiac arrest is often the first manifestation of coronary heart disease. Effective cardiopulmonary resuscitation is the only way to rescue this type of patients. Cardiopulmonary resuscitation is a rapid identification and active rescue of cardiac arrest, artificial reconstruction or recovery of spontaneous breathing and circulation to avoid cardiopulmonary cerebral dysfunction. Basic life support (basic life) is adopted quickly. Support, BLS) is the key to the success of cardiopulmonary resuscitation.
Cardiac arrest has two different forms. One is dysarhithmic cardiac arrest caused by arrhythmia and the other is cardiac arrest caused by respiratory arrest (asphyxial or respiratory cardiac arrest). The former type of cardiac arrest is mostly ventricular fibrillation (ventricular fibrillation, VF). The latter type of cardiac arrest is caused by drowning, drug overdose or trauma, only about 5% to 15% of the patients have ventricular fibrillation. Early defibrillation and immediate cardiopulmonary resuscitation are emphasized in the previous type of patients, while effective external compression and artificial ventilation are required for the latter type of patients.
At present, the effective rescue success rate of cardiopulmonary resuscitation is still very low. It is possible to reduce the death rate only by continuous improvement. This is mainly due to the following three reasons. (1) cardiopulmonary resuscitation begins relatively late, including external chest compression and artificial ventilation. (2) the efficiency of chest compressions is low and frequent interruption. (3) defibrillation is not made in time. The delay of the time of rescue.
Ventricular fibrillation, if not removed in time, can turn to asystole in a few minutes. In order to increase the opportunity for early defibrillation, the defibrillation time is shortened as far as possible. In vitro automatic defibrillator (automatic external defibrillator, AED) is the largest characteristic of.AED to improve the degree of automation of electric shock defibrillation, which is specially for non medical personnel and The primary lifesaver designed to use the sensitivity and specificity of identifying ventricular fibrillation more than 94%. rescuers can put AED on the chest wall of the patient and start the switch without pulse, and AED to perceive the ECG signals, such as identifying ventricular tachycardia (Ventricular Tachycardia, VT), or ventricular fibrillation, Automatic defibrillation. Research after the application of AED shows that the survival rate can be significantly increased compared with the simple basic life support. AHA and IAFC in the United States have required each emergency vehicle and fire engine to be equipped with AED. with the promotion and popularization of AED, and more life will be expected to be saved.
Because most of the patients with cardiac arrest (60%-70%) occur before the hospital and the brain cells can have irreversible damage after 5 minutes of cardiac arrest at normal temperature, the brain cells die after 10 minutes. During this period, the electrical activity of the heart will gradually disappear if the cardiopulmonary resuscitation is not implemented, and the ventricular rest is finally appeared, and a cardiogram appears in the heart. Cardiopulmonary resuscitation and drug therapy may increase the circulation of blood and oxygen in the ischemic myocardium, and then turn the rest of the ventricle into ventricular fibrillation, and then electric shock defibrillation. The heart stops contraction during the rest of the ventricle and ventricular fibrillation, so the pulse signal can not be detected. If the heart only exists electrical activity of the heart, there is no corresponding The mechanical contraction is called electromechanical dissociation (EMD) or pulseless electrical activity (PEA). This often occurs in the process of drug treatment or cardiopulmonary resuscitation, without electric shock defibrillation, or ventricular fibrillation to the rest of the ventricle.
Currently, cardiopulmonary resuscitation has a standard operation guide (the international guidelines) to determine corresponding recovery measures based on detection of respiratory, pulse, and electrocardiographic rhythms. The current use of AED can only make corresponding rhythmic analysis based on the electrocardiogram of the patient to determine whether electric shock defibrillation is required, other such as breathing detection, pulse. Cardiopulmonary resuscitation (CPR) should be fully automated. The following problems still need to be solved:
(1) cardiopulmonary rhythm identification in the process of chest compression. The survival rate of patients with cardiac arrest rapidly decreases with the duration of ventricular fibrillation. The average survival rate is about 7% to 10%. per minute. The possibility of survival is almost zero when the time of electric shock defibrillation is delayed more than 10~12 minutes. Electric defibrillation can effectively improve the survival rate of patients with cardiac arrest. But the current automatic defibrillator needs repeated rhythms before defibrillation is implemented. Otherwise, if the normal non defibrillating ventricular beat rhythm is misjudged as defibrillation rhythm and the unnecessary electric shock is implemented, it will produce the heart of the patient. In order to ensure the correct identification of ventricular fibrillation, it is necessary to stop the external compression and ventilation of the patients during the rhythm analysis. This process takes about 12 to 20 seconds. In this process, the success rate of defibrillation is greatly reduced because of the prolongation of the time of ventricular fibrillation. During the recovery of patients outside the hospital, a reliable algorithm for ventricular fibrillation rhythm identification, even if a reliable analysis of the ECG waveform is carried out during external compression of the patient's chest, then the probability of patient survival will be effectively improved.
(2) monitoring and analysis of the effectiveness of the chest compression. The quality of the external cardiac compression is also the key to successful recovery, including the compression depth, the compression frequency and the rebound degree of the chest. The critical depth of compression is the key to maintaining a certain coronary perfusion pressure, CPP. However, the study shows many hearts In the process of cardiopulmonary resuscitation, patients with CPR did not get effective chest compressions, mainly in lower pressing frequency, less pressing depth and no proper circulation blood flow. In the process of first aid, the external pressure of the chest was not effectively monitored, and the whole process could only depend on the sense and visual judgment of the rescuers. With the process of resuscitation, emergency personnel urgently need to understand the effects of chest compressions and the resulting changes in the blood flow of the patient's heart, so as to carry out further treatment, including the optimization of electric shock defibrillation or the continuation of chest compressions.
(3) real time breathing and pulse detection. In the past 20 years, the proportion of ventricular fibrillation or ventricular tachycardia in cardiac arrest has declined gradually, already less than 50%, and the proportion of PEA without pulse electrocardiography and other types of cardiac arrest has not changed. It is required that first witnesses or first aid personnel quickly judge whether the patient has breathing, pulse, or sufficient blood circulation in the absence of consciousness. But the detection of these two indicators is very difficult for the first aid, because the traditional pulse detection is achieved by the pulsation of the patient's neck movement. It is close to the patient's mouth feel breathing air flow and observation of the changes in the chest. These are difficult to apply to common people. It is difficult to apply to patients with very weak heartbeat and breathing. If you can't accurately detect breathing and pulse, you can't correctly distinguish the cardiac arrest caused by arrhythmia and asphyxia, and carry out the correct recovery. Sue measures.
In order to solve the problems in the process of cardiopulmonary resuscitation, we extend the function of ECG acquisition and defibrillation electrode used by AED, and use a pair of predefibrillation electrodes to collect and analyze the ECG signal and thoracic impedance signal. Through the analysis of the central electrical signal of the pressing process, we can monitor the effect of chest compression, through the impedance signal to the chest. Processing realizes the detection of weak respiratory and pulse signals, and realizes the automatic implementation of CPR. The main algorithms include:
(1) ECG rhythm recognition algorithm in uninterrupted chest compressions. The rhythmic recognition of ECG signals is realized by continuous wavelet transform and morphological consistency evaluation. The regular ECG rhythm (organized rhythm) and irregular ECG joint can be distinguished by quantitative analysis of the conformance of R wave in ECG signals. Law (disorganized rhythm). For regular ECG rhythm, the change of heart rate is estimated by the frequency of the peak of peak of R wave in continuous wavelet transform in order to distinguish ventricular tachycardia and normal rhythm. For irregular ECG, the area of ventricular fibrillation and ventricular quiescence by amplitude frequency spectrum area analysis.
(2) an optimal algorithm for monitoring the effectiveness of compressions and defibrillation. Early monitoring of the effectiveness of chest compressions was achieved by the amplitude analysis of ventricular fibrillation signals. Animal and clinical studies have shown that the frequency of ventricular fibrillation signals is related to CPP, but the amplitude and frequency of ECG signals are due to the patient's The study group combines the amplitude and frequency of the ECG signal and proposes an analytical method based on the amplitude frequency spectrum area. It is defined as the area contained in the signal power spectrum under a certain band width. We expect that this method can be extended to the optimization analysis of electric shock defibrillation. It is applied to real-time monitoring of chest compression effectiveness.
(3) real-time breathing and pulse detection analysis algorithm. The impedance signals extracted from electrocardiogram detection / defibrillation electrodes are composed of two parts: one is a respiratory impedance signal with a lower frequency but a higher amplitude, and two is a cardiac impedance signal with a slightly higher frequency but a lower amplitude that reflects the mechanical activity of the heart. Our attentively electrical signal is used as a reference. An adaptive filter is used to separate the respiratory impedance signal and the impedance signal of the heart. Finally, the peak detection algorithm is used to determine whether the pulse signal is detected by the detected amplitude of the impedance signal, and the magnitude of the tidal volume is estimated with the amplitude of the respiratory impedance signal, thus the category of the respiration is determined.
In order to test the effectiveness of these algorithms, we have carried out the corresponding experimental design and clinical experiments on different algorithms. The results of electrocardiogram analysis of 232 patients with cardiac arrest by AED show that the proposed automatic ECG rhythm analysis algorithm can be reliable to the reliability of ECG rhythm under uninterrupted chest compressions. Analysis. The sensitivity of defibrillation signal detection was 93%, and the specificity was 89%. in a group of cardiac arrest animal models caused by arrhythmia. The amplitude frequency spectrum area analysis was well correlated with the results of CPP analysis, and had high accuracy for the prediction of electric shock defibrillation results. In another, the heart sudden caused by asphyxia. In the animal model, the change of the cardiac impedance signal caused by cardiac mechanical activity is closely related to the pulse voltage, and the change of respiratory impedance signals caused by respiration is positively related to the change of the volume of respiratory tide.
The results of the clinical study show that the proposed algorithm can correctly distinguish the different types of cardiac arrest caused by arrhythmia and asphyxia by the noninvasive detection of pulse and respiratory signals, and prompt the emergency personnel to implement the corresponding resuscitation scheme in time. The analysis can effectively avoid the delay caused by the rhythm analysis, improve the survival rate of the patients, and avoid the unnecessary or unsuccessful electric shock defibrillation, and better solve the shortcomings of the current cardiopulmonary resuscitation.
【學(xué)位授予單位】：南方醫(yī)科大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2007
【分類號】：R459.7;R311

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 李永勤;糖尿病早期自主神經(jīng)病變無創(chuàng)檢測方法研究[D];中國人民解放軍第一軍醫(yī)大學(xué);2003年

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