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一种针对心肺复苏期间力引导与深度引导压缩对不同胸部和背部支撑表面影响的建模方法。

A modeling approach to the effects of force guided versus depth guided compression during cardiopulmonary resuscitation on different chests and back support surfaces.

机构信息

Biomedical Engineering Research Group, Department of Mechanical and Mechatronic Engineering, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa.

出版信息

Resuscitation. 2013 Jun;84(6):837-42. doi: 10.1016/j.resuscitation.2012.11.027. Epub 2012 Nov 29.

DOI:10.1016/j.resuscitation.2012.11.027
PMID:23201500
Abstract

OBJECTIVES

To validate an existing theoretical model for the mechanics of chest compression (CC) during constant peak force cardiopulmonary resuscitation (CPR) using experimental human and manikin CC data from the literature. Also, to gain insights into the clinical application of force guided CPR.

METHODS

The experimental CC data from the literature were analyzed and compared to theoretical predictions from the constant peak force CPR model. The CPR model was also used to explore how CC rate and peak sternal force may influence CC performance during the clinical application of force guided CPR.

RESULTS

The model predictions matched the human CC data to within an average difference of less than 1.5% at CC rates of 60 cpm and 90 cpm, and 0.6% for the manikin data at a CC rate of 90 cpm. The model predictions also showed that the net sternum-to-spine compression depth achieved during force guided CPR strongly depends on the patient's thoracic stiffness.

CONCLUSIONS

Good quantitative agreement between the experimental data from the literature and the theoretical model suggests that the constant peak force CPR model developed by Boe and Babbs provides reasonable prediction of CC mechanics during CPR over a range of clinically relevant CC rates. The model predictions also suggest that the effectiveness of CC during force guided CPR is highly sensitive to the patient's thoracic stiffness and insensitive to the back support stiffness. Patients having high thoracic stiffness (≥ 100 Ncm(-1)) were found to require higher CC forces, which may exceed the force above which severe chest wall trauma and abdominal injury occurs, in order to achieve the ERC recommended CC depth range. This suggests that the choice of maximum sternal force applied by clinicians during constant peak force CPR ought to be based on a general assessment of the patient's thoracic stiffness.

摘要

目的

利用文献中来自人体和模拟假人的实验性胸外按压(CC)数据,验证现有的用于恒定峰值力心肺复苏(CPR)期间 CC 力学的理论模型。此外,还旨在深入了解力引导 CPR 的临床应用。

方法

分析文献中的实验性 CC 数据,并将其与恒定峰值力 CPR 模型的理论预测进行比较。还使用 CPR 模型来探索 CC 率和胸骨峰值力如何影响力引导 CPR 临床应用中的 CC 性能。

结果

模型预测与 CC 率为 60 cpm 和 90 cpm 时的人体 CC 数据的平均差异小于 1.5%,CC 率为 90 cpm 时的模拟假人数据的平均差异为 0.6%,吻合较好。模型预测还表明,在力引导 CPR 期间,胸骨到脊柱的净压缩深度强烈依赖于患者的胸廓刚度。

结论

文献中的实验数据与理论模型之间存在良好的定量一致性,这表明由 Boe 和 Babbs 开发的恒定峰值力 CPR 模型能够在一系列与临床相关的 CC 率范围内合理预测 CPR 期间的 CC 力学。模型预测还表明,力引导 CPR 期间的 CC 效果对患者的胸廓刚度高度敏感,而对背部支撑刚度不敏感。具有高胸廓刚度(≥ 100 Ncm(-1))的患者被发现需要更高的 CC 力,为了达到 ERC 推荐的 CC 深度范围,这些力可能会超过发生严重胸壁创伤和腹部损伤的力。这表明,临床医生在恒定峰值力 CPR 期间应用的最大胸骨力的选择应基于对患者胸廓刚度的一般评估。

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引用本文的文献

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Effect of thoracic stiffness on chest compression performance - A prospective randomized crossover observational manikin study.胸廓僵硬对胸外按压性能的影响——一项前瞻性随机交叉观察性人体模型研究。
Heliyon. 2022 Oct 8;8(10):e10990. doi: 10.1016/j.heliyon.2022.e10990. eCollection 2022 Oct.
2
Recognition of Abnormal Chest Compression Depth Using One-Dimensional Convolutional Neural Networks.使用一维卷积神经网络识别异常胸部按压深度。
Sensors (Basel). 2021 Jan 27;21(3):846. doi: 10.3390/s21030846.