Evidence map›Paper›PMID 41180426›Full record

ArticleMedical research archives2025

The Importance of a Continuously Changing Heart Rate in Venous and Arterial Pressure Analysis.

Gabriel P Bonvillain, Lauren D Pierce, Adria Abella Villafranca, Sam E Stephens, Luke E Ferguson, Hanna K Jensen, Joseph A Sanford, Jingxian Wu, Kevin Sexton, Morten Jensen

Abstract read
In one paragraph

Article in Medical research archives, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Gabriel P BonvillainDepartment of Biomedical Engineering, University of Arkansas, Fayetteville, Arkansas.
Lauren D PierceDepartment of Biomedical Engineering, University of Arkansas, Fayetteville, Arkansas.
Adria Abella VillafrancaDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Sam E StephensDepartment of Biomedical Engineering, University of Arkansas, Fayetteville, Arkansas.
Luke E FergusonDepartment of Biomedical Engineering, University of Arkansas, Fayetteville, Arkansas.
Hanna K JensenDepartment of Surgery, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Joseph A SanfordDepartment of Anesthesiology, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Jingxian WuDepartment of Electrical Engineering, University of Arkansas, Fayetteville, Arkansas.
Kevin SextonDepartment of Biomedical Engineering, University of Arkansas, Fayetteville, Arkansas.
Morten JensenDepartment of Biomedical Engineering, University of Arkansas, Fayetteville, Arkansas.

Funding

Expanding Translational Research in ArkansasUL1TR003107 · NCATS · UNIV OF ARKANSAS FOR MED SCIS · PI JAMES, LAURA P · 2019 to 2023
$21.6M
J. NRSA TrainingTL1TR003109 · NCATS · UNIV OF ARKANSAS FOR MED SCIS · PI SEXTON, KEVIN WAYNE · 2019 to 2023
$1.5M
NCATS NIH HHS TL1 TR003109NCATS NIH HHS UL1 TR003107
6 · The paper itself

Abstract

Purpose: Previous studies have suggested that minimally invasive peripheral venous and arterial pressure waveforms provide a greater ability to detect acute changes in blood volume than traditional vital signs. Many of these studies are using Fast Fourier Transforms and power spectral densities to evaluate changes in the power at the heart rate frequency. Using the frequency domain requires a segment of the time domain to be converted into the frequency domain, which means that the heart rate derived from frequency domain analysis is an average of the segment used. However, in clinical settings the heart rate is changing continuously. Methods: This study evaluates the changing heart rate frequency power under varying time segments and compares the heart rate obtained from Fast Fourier Transform and power spectral density analysis with the instantaneous heart rate to gain a better insight into how a changing heart rate may influence the heart rate frequency power. Results: Spectral analysis revealed non-linear trends in heart rate frequency power, with changes that correspond to changes in the heart rate. We found the time segment chosen and the absolute difference between the instantaneous heart rate and the average heart rate obtained from power spectral density analysis influences the heart rate frequency power, such that as the instantaneous heart rate approaches the average heart rate, the heart rate frequency power increases. Conclusion: These results suggest that the time segment chosen for frequency domain analysis influences the power spectrum of the pressure waveforms. Furthermore, this study emphasizes the importance of utilizing a continuously changing heart rate in pressure waveform analysis.

Identifiers

PMID41180426
PMCPMC12574384

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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 OpenQuestion graph.