Estimation of pulse wave analysis indices from invasive arterial blood pressure only for a clinical assessment of wave reflection in a 5-day septic animal experiment.

IF 2.6 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Diletta Guberti, Manuela Ferrario, Marta Carrara
{"title":"Estimation of pulse wave analysis indices from invasive arterial blood pressure only for a clinical assessment of wave reflection in a 5-day septic animal experiment.","authors":"Diletta Guberti, Manuela Ferrario, Marta Carrara","doi":"10.1007/s11517-025-03328-8","DOIUrl":null,"url":null,"abstract":"<p><p>Wave separation analysis (WSA) is the gold standard to analyze the arterial blood pressure (ABP) waveform, decomposing it into a forward and a reflected wave. It requires ABP and arterial blood flow (ABF) measurement, and ABF is often unavailable in clinical settings. Therefore, methods to estimate ABF from ABP have been proposed, but they are not investigated in critical conditions. In this work, an autoregressive with exogenous input model was proposed as an original method to estimate ABF from the measured ABP. Its performance in assessing WSA indices to characterize the arterial tree was evaluated in critical conditions, i.e., during sepsis. The triangular and the personalized flow approximation and the multi-Gaussian ABP decomposition were compared to the proposed model. The results highlighted how the black-box modeling approach is superior to other flow estimation models when computing WSA indices in septic condition. This approach holds promise for overcoming challenges in clinical settings where ABF data are unavailable.</p>","PeriodicalId":49840,"journal":{"name":"Medical & Biological Engineering & Computing","volume":" ","pages":"2341-2353"},"PeriodicalIF":2.6000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12316715/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical & Biological Engineering & Computing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s11517-025-03328-8","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/27 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

Wave separation analysis (WSA) is the gold standard to analyze the arterial blood pressure (ABP) waveform, decomposing it into a forward and a reflected wave. It requires ABP and arterial blood flow (ABF) measurement, and ABF is often unavailable in clinical settings. Therefore, methods to estimate ABF from ABP have been proposed, but they are not investigated in critical conditions. In this work, an autoregressive with exogenous input model was proposed as an original method to estimate ABF from the measured ABP. Its performance in assessing WSA indices to characterize the arterial tree was evaluated in critical conditions, i.e., during sepsis. The triangular and the personalized flow approximation and the multi-Gaussian ABP decomposition were compared to the proposed model. The results highlighted how the black-box modeling approach is superior to other flow estimation models when computing WSA indices in septic condition. This approach holds promise for overcoming challenges in clinical settings where ABF data are unavailable.

Abstract Image

Abstract Image

Abstract Image

在5天脓毒症动物实验中,从有创动脉血压中估计脉搏波分析指标,仅用于临床评估波反射。
波分离分析(WSA)是分析动脉血压(ABP)波形的金标准,将其分解为正向波和反射波。它需要ABP和动脉血流量(ABF)测量,而ABF在临床环境中通常不可用。因此,已经提出了从ABP估计ABF的方法,但没有在临界条件下进行研究。在这项工作中,提出了一种带有外源性输入的自回归模型,作为一种从测量的ABP中估计ABF的原始方法。在危急情况下,即脓毒症期间,评估了其在评估WSA指标以表征动脉树的性能。将三角流近似和个性化流近似以及多高斯ABP分解与所提出的模型进行了比较。结果表明,黑箱建模方法在计算化粪池条件下的WSA指数时优于其他流量估计模型。这种方法有望克服临床环境中无法获得ABF数据的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Medical & Biological Engineering & Computing
Medical & Biological Engineering & Computing 医学-工程:生物医学
CiteScore
6.00
自引率
3.10%
发文量
249
审稿时长
3.5 months
期刊介绍: Founded in 1963, Medical & Biological Engineering & Computing (MBEC) continues to serve the biomedical engineering community, covering the entire spectrum of biomedical and clinical engineering. The journal presents exciting and vital experimental and theoretical developments in biomedical science and technology, and reports on advances in computer-based methodologies in these multidisciplinary subjects. The journal also incorporates new and evolving technologies including cellular engineering and molecular imaging. MBEC publishes original research articles as well as reviews and technical notes. Its Rapid Communications category focuses on material of immediate value to the readership, while the Controversies section provides a forum to exchange views on selected issues, stimulating a vigorous and informed debate in this exciting and high profile field. MBEC is an official journal of the International Federation of Medical and Biological Engineering (IFMBE).
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信