Li Yongqin, Bisera Joe, Geheb Fredrick, Tang Wanchun, Weil Max Harry
Weil Institute of Critical Care Medicine, Rancho Mirage, CA, USA.
Crit Care Med. 2008 Jan;36(1):198-203. doi: 10.1097/01.CCM.0000295589.64729.6B.
Current versions of automated external defibrillators (AEDs) mandate interruptions of chest compression for rhythm analyses because of artifacts produced by chest compressions. Interruption of chest compressions reduces likelihood of successful resuscitation by as much as 50%. We sought a method to identify a shockable rhythm without interrupting chest compressions during cardiopulmonary resuscitation (CPR).
Experimental study.
Weil Institute of Critical Care Medicine, Rancho Mirage, CA.
None.
Electrocardiographs (ECGs) were recorded in conjunction with AEDs during CPR in human victims. A shockable rhythm was defined as disorganized rhythm with an amplitude > 0.1 mV or, if organized, at a rate of > or = 180 beats/min. Wavelet-based transformation and shape-based morphology detection were used for rhythm classification. Morphologic consistencies of waveform representing QRS components were analyzed to differentiate between disorganized and organized rhythms. For disorganized rhythms, the amplitude spectrum area was computed in the frequency domain to distinguish between shockable ventricular fibrillation and nonshockable asystole. For organized rhythms, in victims in whom the absence of a heartbeat was independently confirmed, the heart rate was estimated for further classification.
To derive the algorithm, we used 29 recordings on 29 patients from the Creighton University ventricular tachyarrhythmia database. For validation, the algorithm was tested on an independent population of 229 victims, including recordings of both ECG and depth of chest compressions obtained during suspected out-of-hospital sudden death. The recordings included 111 instances in which the ECG was corrupted during chest compressions. A shockable rhythm was identified with a sensitivity of 93% and a specificity of 89%, yielding a positive predictive value of 91%. A nonshockable rhythm was identified with a sensitivity of 89%, a specificity of 93%, and a positive predictive value of 91% during uninterrupted chest compression.
The algorithm fulfilled the potential lifesaving advantages of allowing for uninterrupted chest compression, avoiding pauses for automated rhythm analyses before prompting delivery of an electrical shock.
由于胸部按压产生的伪迹，当前版本的自动体外除颤器（AED）要求中断胸部按压以进行心律分析。胸部按压的中断会使成功复苏的可能性降低多达50%。我们寻求一种在心肺复苏（CPR）期间不中断胸部按压就能识别可电击心律的方法。
实验研究。
加利福尼亚州兰乔米拉奇的威尔重症医学研究所。
无。
在对人类受害者进行心肺复苏期间，将心电图（ECG）与自动体外除颤器同步记录。可电击心律定义为振幅>0.1 mV的紊乱心律，或者如果是规整心律，则心率>或 = 180次/分钟。基于小波的变换和基于形状的形态学检测用于心律分类。分析代表QRS波群成分的波形的形态一致性，以区分紊乱心律和规整心律。对于紊乱心律，在频域中计算振幅谱面积，以区分可电击的心室颤动和不可电击的心脏停搏。对于规整心律，在独立确认无心跳的受害者中，估计心率以进行进一步分类。
为了推导该算法，我们使用了来自克里顿大学室性快速性心律失常数据库的29例患者的29份记录。为了进行验证，该算法在229名受害者的独立人群中进行了测试，包括在疑似院外猝死期间获得的心电图和胸部按压深度的记录。这些记录包括111例在胸部按压期间心电图被干扰的情况。在不中断胸部按压的情况下，识别可电击心律的灵敏度为93%，特异度为89%，阳性预测值为91%。识别不可电击心律的灵敏度为89%，特异度为93%，阳性预测值为91%。
该算法实现了允许不间断胸部按压的潜在救生优势，避免了在提示电击之前进行自动心律分析的停顿。
