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本文引用的文献

1
Short ECG segments predict defibrillation outcome using quantitative waveform measures.使用定量波形测量短 ECG 段预测除颤效果。
Resuscitation. 2016 Dec;109:16-20. doi: 10.1016/j.resuscitation.2016.09.020. Epub 2016 Oct 1.
2
Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators.用于自动体外除颤器中可电击心律检测的机器学习技术
PLoS One. 2016 Jul 21;11(7):e0159654. doi: 10.1371/journal.pone.0159654. eCollection 2016.
3
See through ECG technology during cardiopulmonary resuscitation to analyze rhythm and predict defibrillation outcome.在心肺复苏期间运用可透视心电图技术来分析心律并预测除颤结果。
Curr Opin Crit Care. 2016 Jun;22(3):199-205. doi: 10.1097/MCC.0000000000000297.
4
Combining Amplitude Spectrum Area with Previous Shock Information Using Neural Networks Improves Prediction Performance of Defibrillation Outcome for Subsequent Shocks in Out-Of-Hospital Cardiac Arrest Patients.使用神经网络将振幅频谱面积与先前电击信息相结合可提高院外心脏骤停患者后续电击除颤结果的预测性能。
PLoS One. 2016 Feb 10;11(2):e0149115. doi: 10.1371/journal.pone.0149115. eCollection 2016.
5
Part 7: Adult Advanced Cardiovascular Life Support: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care.第7部分：成人高级心血管生命支持：2015年美国心脏协会心肺复苏及心血管急救指南更新
Circulation. 2015 Nov 3;132(18 Suppl 2):S444-64. doi: 10.1161/CIR.0000000000000261.
6
Association Between Chest Compression Interruptions and Clinical Outcomes of Ventricular Fibrillation Out-of-Hospital Cardiac Arrest.胸部按压中断与院外室颤性心脏骤停临床结局的关联。
Circulation. 2015 Sep 15;132(11):1030-7. doi: 10.1161/CIRCULATIONAHA.115.014016. Epub 2015 Aug 7.
7
Adaptive rhythm sequencing: A method for dynamic rhythm classification during CPR.自适应节律序列：CPR 期间动态节律分类的一种方法。
Resuscitation. 2015 Jun;91:26-31. doi: 10.1016/j.resuscitation.2015.02.031. Epub 2015 Mar 21.
8
Association between survival and early versus later rhythm analysis in out-of-hospital cardiac arrest: do agency-level factors influence outcomes?院外心脏骤停患者生存与早期和晚期节律分析之间的关联：机构层面因素是否会影响结果？
Ann Emerg Med. 2014 Jul;64(1):1-8. doi: 10.1016/j.annemergmed.2014.01.014. Epub 2014 Feb 13.
9
Course of quantitative ventricular fibrillation waveform measure and outcome following out-of-hospital cardiac arrest.院外心脏骤停后定量心室颤动波形测量和结果的过程。
Heart Rhythm. 2014 Feb;11(2):230-6. doi: 10.1016/j.hrthm.2013.10.049. Epub 2013 Oct 28.
10
Amplitude spectrum area to guide resuscitation-a retrospective analysis during out-of-hospital cardiopulmonary resuscitation in 609 patients with ventricular fibrillation cardiac arrest.振幅谱面积指导复苏——609 例室颤性心脏骤停患者院外心肺复苏的回顾性分析。
Resuscitation. 2013 Dec;84(12):1697-703. doi: 10.1016/j.resuscitation.2013.08.017. Epub 2013 Sep 1.

心室颤动波形测量结合先前的电击结果可预测心肺复苏期间的除颤成功率。

Ventricular fibrillation waveform measures combined with prior shock outcome predict defibrillation success during cardiopulmonary resuscitation.

作者信息

Coult Jason, Kwok Heemun, Sherman Lawrence, Blackwood Jennifer, Kudenchuk Peter J, Rea Thomas D

机构信息

Department of Bioengineering, University of Washington, Seattle, WA, USA; Center for Progress in Resuscitation, University of Washington, Seattle, WA, USA.

Center for Progress in Resuscitation, University of Washington, Seattle, WA, USA; Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA.

出版信息

J Electrocardiol. 2018 Jan-Feb;51(1):99-106. doi: 10.1016/j.jelectrocard.2017.07.016. Epub 2017 Aug 1.

DOI:10.1016/j.jelectrocard.2017.07.016
PMID:28893389
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5776045/
Abstract

AIM

Amplitude Spectrum Area (AMSA) and Median Slope (MS) are ventricular fibrillation (VF) waveform measures that predict defibrillation shock success. Cardiopulmonary resuscitation (CPR) obscures electrocardiograms and must be paused for analysis. Studies suggest waveform measures better predict subsequent shock success when combined with prior shock success. We determined whether this relationship applies during CPR.

METHODS

AMSA and MS were calculated from 5-second pre-shock segments with and without CPR, and compared to logistic models combining each measure with prior return of organized rhythm (ROR).

RESULTS

VF segments from 692 patients were analyzed during CPR before 1372 shocks and without CPR before 1283 shocks. Combining waveform measures with prior ROR increased areas under receiver operating characteristic curves for AMSA/MS with CPR (0.66/0.68 to 0.73/0.74, p<0.001) and without CPR (0.71/0.72 to 0.76/0.76, p<0.001).

CONCLUSIONS

Prior ROR improves prediction of shock success during CPR, and may enable waveform measure calculation without chest compression pauses.

摘要

目的

振幅频谱面积（AMSA）和中位数斜率（MS）是预测除颤电击成功的室颤（VF）波形指标。心肺复苏（CPR）会干扰心电图，必须暂停以进行分析。研究表明，波形指标与先前的电击成功相结合时，能更好地预测后续电击成功。我们确定这种关系在心肺复苏期间是否适用。

方法

在有和没有心肺复苏的情况下，从电击前5秒的片段中计算AMSA和MS，并与将每种指标与先前的有组织节律恢复（ROR）相结合的逻辑模型进行比较。

结果

在1372次电击前的心肺复苏期间以及1283次电击前没有心肺复苏的情况下，分析了692例患者的室颤片段。将波形指标与先前的ROR相结合，增加了有CPR时AMSA/MS的受试者工作特征曲线下面积（从0.66/0.68增至0.73/0.74，p<0.001）以及无CPR时的曲线下面积（从0.71/0.72增至0.76/0.76，p<0.001）。

结论

先前的ROR可改善心肺复苏期间电击成功的预测，并可能无需暂停胸外按压就能进行波形指标计算。