Evidence map›Paper›PMID 25033442›Full record

ArticlePloS one2014

Continuous stroke volume estimation from aortic pressure using zero dimensional cardiovascular model: proof of concept study from porcine experiments.

Shun Kamoi, Christopher Pretty, Paul Docherty, Dougie Squire, James Revie, Yeong Shiong Chiew, Thomas Desaive, Geoffrey M Shaw, J Geoffrey Chase

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In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. The modified arterial reservoir: An update with consideration of asymptotic pressure (Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine · 2020
    Pooled it
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4 · The record

Corrections and comments

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.

Shun KamoiDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
Christopher PrettyDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
Paul DochertyDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
Dougie SquireDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
James RevieDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
Yeong Shiong ChiewDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
Thomas DesaiveGIGA Cardiovascular Science, University of Liege, Liege, Belgium.
Geoffrey M ShawIntensive Care Unit, Christchurch Hospital, Christchurch, New Zealand.
J Geoffrey ChaseDepartment of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAccurate, continuous, left ventricular stroke volume (SV) measurements can convey large amounts of information about patient hemodynamic status and response to therapy. However, direct measurements are highly invasive in clinical practice, and current procedures for estimating SV require specialized devices and significant approximation.

methodThis study investigates the accuracy of a three element Windkessel model combined with an aortic pressure waveform to estimate SV. Aortic pressure is separated into two components capturing; 1) resistance and compliance, 2) characteristic impedance. This separation provides model-element relationships enabling SV to be estimated while requiring only one of the three element values to be known or estimated. Beat-to-beat SV estimation was performed using population-representative optimal values for each model element. This method was validated using measured SV data from porcine experiments (N = 3 female Pietrain pigs, 29-37 kg) in which both ventricular volume and aortic pressure waveforms were measured simultaneously.

resultsThe median difference between measured SV from left ventricle (LV) output and estimated SV was 0.6 ml with a 90% range (5th-95th percentile) -12.4 ml-14.3 ml. During periods when changes in SV were induced, cross correlations in between estimated and measured SV were above R = 0.65 for all cases.

conclusionThe method presented demonstrates that the magnitude and trends of SV can be accurately estimated from pressure waveforms alone, without the need for identification of complex physiological metrics where strength of correlations may vary significantly from patient to patient.

Indexed as

AlgorithmsAnimalsArterial PressureCardiovascular DiseasesFemaleHeart VentriclesHemodynamicsModels, CardiovascularStroke VolumeSwineVentricular Function

Identifiers

PMID25033442
PMCPMC4102500

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Registered trials

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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.