Evidence map›Paper›PMID 40414963›Full record

ArticleScientific reports2025

Assessment of a non-invasive approach for pressure volume loop prediction in mice.

Liliana Jelú Reyes, Maria Emilia Alfaro, Janet Akoth Kireta, Michele Lynn Joyner, Soumya Ullas, Brianna LaViolette, Dinesh Hirenallur-Shanthappa, Nessy Tania

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

8 authors.

Liliana Jelú Reyes *Translational Clinical Sciences, Pfizer Research and Development, Cambridge, MA, 02139, USA.
Maria Emilia Alfaro *Department of Mathematics and Statistics, East Tennessee State University, Johnson City, 37614, USA.
Janet Akoth KiretaDepartment of Mathematics and Statistics, East Tennessee State University, Johnson City, 37614, USA.
Michele Lynn JoynerDepartment of Mathematics and Statistics, East Tennessee State University, Johnson City, 37614, USA.
Soumya UllasDrug Safety Research & Development, Pfizer Research and Development, Cambridge, MA, 02139, USA.
Brianna LaVioletteDrug Safety Research & Development, Pfizer Research and Development, Cambridge, MA, 02139, USA.
Dinesh Hirenallur-ShanthappaDrug Safety Research & Development, Pfizer Research and Development, Cambridge, MA, 02139, USA.
Nessy TaniaTranslational Clinical Sciences, Pfizer Research and Development, Cambridge, MA, 02139, USA. nessy.tania@pfizer.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Left ventricular pressure-volume (PV) loop measurement provides insights into cardiac function by mapping the relationship between left ventricular pressure and volume throughout the cardiac cycle. PV loops are used extensively in pre-clinical studies, but they are obtained through invasive and often terminal procedures. In prior studies utilizing data from large mammals (e.g., pigs and humans), quantitative models have been utilized to estimate PV loops utilizing non-invasive measurements. These studies rely on three key assumptions: constant normalized elastance (ratio of pressure over volume) across individuals, accurate non-invasive estimation of left ventricular systolic and diastolic pressure, and non-invasive estimation of left ventricular volume data. Here we assessed the application and suitability of these approaches to mice, a smaller pre-clinical animal. We found limitations of this approach due to variability in elastance among mice, suggesting that the constancy observed in larger animals might not generally extend to rodents. Additionally, while non-invasive estimates of end systolic pressures were close to invasively obtained measurements, they were not reliable for determining maximum elastance. Moreover, although individual correlations between invasive and non-invasive volume measurements were strong, creating a generalized predictive model of pressure-volume loop proved challenging due to variability across sample data set.

Indexed as

Ventricular Function, LeftVentricular PressureAnimalsBlood PressureHeart VentriclesMaleMiceMice, Inbred C57BLSystoleCardiacElastanceInvasiveNon-invasivePressure-volume loop

Identifiers

PMID40414963
PMCPMC12104428

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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.