Evidence mapPaperPMID 36909238Full record

ArticleFrontiers in physiology2023

Wave reflection quantification analysis and personalized flow wave estimation based on the central aortic pressure waveform.

Hongming Sun, Yang Yao, Wenyan Liu, Shuran Zhou, Shuo Du, Junyi Tan, Yin Yu, Lisheng Xu, Alberto Avolio

Abstract read
In one paragraph

Article in Frontiers in physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Hongming SunCollege of Medicine and Biological and Information Engineering, Northeastern University, Shenyang, China.
Yang YaoSchool of Information Science and Technology, ShanghaiTech University, Shanghai, China.
Wenyan LiuCollege of Medicine and Biological and Information Engineering, Northeastern University, Shenyang, China.
Shuran ZhouCollege of Medicine and Biological and Information Engineering, Northeastern University, Shenyang, China.
Shuo DuCollege of Medicine and Biological and Information Engineering, Northeastern University, Shenyang, China.
Junyi TanCollege of Medicine and Biological and Information Engineering, Northeastern University, Shenyang, China.
Yin YuCollege of Medicine and Biological and Information Engineering, Northeastern University, Shenyang, China.
Lisheng XuCollege of Medicine and Biological and Information Engineering, Northeastern University, Shenyang, China.
Alberto AvolioMacquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulse wave reflections reflect cardiac afterload and perfusion, which yield valid indicators for monitoring cardiovascular status. Accurate quantification of pressure wave reflections requires the measurement of aortic flow wave. However, direct flow measurement involves extra equipment and well-trained operator. In this study, the personalized aortic flow waveform was estimated from the individual central aortic pressure waveform (CAPW) based on pressure-flow relations. The separated forward and backward pressure waves were used to calculate wave reflection indices such as reflection index (RI) and reflection magnitude (RM), as well as the central aortic pulse transit time (PTT). The effectiveness and feasibility of the method were validated by a set of clinical data (13 participants) and the Nektar1D Pulse Wave Database (4,374 subjects). The performance of the proposed personalized flow waveform method was compared with the traditional triangular flow waveform method and the recently proposed lognormal flow waveform method by statistical analyses. Results show that the root mean square error calculated by the personalized flow waveform approach is smaller than that of the typical triangular and lognormal flow methods, and the correlation coefficient with the measured flow waveform is higher. The estimated personalized flow waveform based on the characteristics of the CAPW can estimate wave reflection indices more accurately than the other two methods. The proposed personalized flow waveform method can be potentially used as a convenient alternative for the measurement of aortic flow waveform.

Indexed as

arterial stiffnesspersonalized flow waveformtriangular flow waveformwave reflectionwave separation analysis

Identifiers

PMID36909238
PMCPMC9996124

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.