Evidence map›Paper›PMID 39715272›Full record

ArticlePLoS computational biology2024

Sensitivity analysis of closed-loop one-chamber and four-chamber models with baroreflex.

Karolina Tlałka, Harry Saxton, Ian Halliday, Xu Xu, Andrew Narracott, Daniel Taylor, Maciej Malawski

Abstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Karolina TlałkaSano Centre for Computational Medicine, Cracow, Poland.ORCID 0009-0005-4575-3510
Harry SaxtonSchool of Computer Science, University of Sheffield, Sheffield, United Kingdom.ORCID 0000-0001-7433-6154
Ian HallidayDivision of Clinical Medicine, University of Sheffield, Sheffield, United Kingdom.
Xu XuSchool of Computer Science, University of Sheffield, Sheffield, United Kingdom.ORCID 0000-0002-9721-9054
Andrew NarracottDivision of Clinical Medicine, University of Sheffield, Sheffield, United Kingdom.
Daniel TaylorDivision of Clinical Medicine, University of Sheffield, Sheffield, United Kingdom.
Maciej MalawskiSano Centre for Computational Medicine, Cracow, Poland.ORCID 0000-0001-6005-0243

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The baroreflex is one of the most important control mechanisms in the human cardiovascular system. This work utilises a closed-loop in silico model of baroreflex regulation, coupled to pulsatile mechanical models with (i) one heart chamber and 36-parameters and (ii) four chambers and 51 parameters. We perform the first global sensitivity analysis of these closed-loop systems which considers both cardiovascular and baroreflex parameters, and compare the models with their respective unregulated equivalents. Results show the reduced influence of regulated parameters compared to unregulated equivalents and that, in the physiological resting state, model outputs (pressures, heart rate, cardiac output etc.) are most sensitive to parasympathetic arc parameters. This work provides insight into the effects of regulation and model input parameter influence on clinical metrics, and constitutes a first step to understanding the role of regulation in models for personalised healthcare.

Indexed as

BaroreflexComputer SimulationModels, CardiovascularBlood PressureComputational BiologyHeart RateHumans

Identifiers

PMID39715272
PMCPMC11706439

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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.