基于in silico数据的各种方法的准确性和错误源的比较,用于非侵入性地估计中央大动脉血压
Xujie Zhang1, Zhaojun Li2, Zhi Zhang3
1Department of Engineering Mechanics, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China.
Computer methods and programs in biomedicine
|October 6, 2024
概括
非侵入性中央大动脉血压 (CABP) 估计方法在准确性和容错性方面有所不同. 像GTF和SCWR这样的预训练算法方法显示较小的错误,但在容忍脉冲波错误方面并不优越.
科学领域:
- 心血管生理学心血管生理学
- 生物医学工程 生物医学工程
- 医疗器械技术 医疗器械技术
背景情况:
- 中枢大动脉血压 (CABP) 在临床上比外围血压更为重要.
- 为了估计CABP存在许多非侵入性方法,但缺乏系统的比较.
- 了解方法特定的误差公差对于临床应用至关重要.
研究的目的:
- 系统地比较经典的非侵入性CABP估计方法.
- 分析方法差异,容忍个体变化和测量错误.
- 为方法选择和优化提供理论证据.
主要方法:
- 使用心血管计算模型生成了一个大规模的虚拟受试者数据集 (n=600).
- 研究了六种经典的CABP估计方法:直接,GTF,NPMA,SBP2,MBWA和SCWR.
- 估计错误被分析为大小,分布,生理相关性和对测量错误的敏感性.
主要成果:
- 在CABP估计错误 (平均值和SD) 中观察到显著的方法间差异.
- 使用预训练算法 (GTF,SCWR) 的方法的错误较小,对生理变化和初始测量错误的敏感度较低.
- 所有方法的性能都降低了,引入了脉冲波误差;GTF和SCWR在这方面没有表现出优越的容错率.
结论:
- 经典的非侵入性CABP估计方法在准确性和错误来源方面表现出相当大的差异.
- 方法特定的错误档案为临床观察和潜在优化提供了理论见解.
- 这种比较分析指导了临床数据的解释和改进的估计技术的开发.
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