Evidence map›Paper›PMID 31813071›Full record

ArticleBiomechanics and modeling in mechanobiology2020

Predictions of hypertrophy and its regression in response to pressure overload.

Kyoko Yoshida, Andrew D McCulloch, Jeffrey H Omens, Jeffrey W Holmes

Abstract read
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Computational models of cardiac hypertrophy.Progress in biophysics and molecular biology · 2021
    Review
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

4 authors.

Kyoko YoshidaDepartment of Biomedical Engineering, University of Virginia, Box 800759, Health System, Charlottesville, VA, 22903, USA.
Andrew D McCullochDepartment of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA.
Jeffrey H OmensDepartment of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA.
Jeffrey W HolmesDepartment of Biomedical Engineering, University of Virginia, Box 800759, Health System, Charlottesville, VA, 22903, USA. holmes@virginia.edu.ORCID http://orcid.org/0000-0001-9125-7220

Funding

Analyzing the Cardiac Power Grid: Adaptive responses to fluctuating local demandU01HL122199 · NHLBI · UNIVERSITY OF WASHINGTON · PI BEARD, DANIEL A, DASH, RANJAN K · 2015 to 2019
$3.3M
Multiscale Models of Cardiac Growth, Remodeling, and Myocardial InfarctionU01HL127654 · NHLBI · UNIVERSITY OF VIRGINIA · PI HOLMES, JEFFREY W · 2015 to 2019
$2.7M
Systems Biology of Hypertrophic Heart Disease from Molecular Pathways to Organ SystemR01HL137100 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCCULLOCH, ANDREW D. · 2017 to 2020
$2.0M
NHLBI NIH HHS R01 HL137100NHLBI NIH HHS U01 HL122199NHLBI NIH HHS U01 HL127654NIBIB NIH HHS U01 HL127654
6 · The paper itself

Abstract

Mechanics-based cardiac growth models can now predict changes in mass, chamber size, and wall thickness in response to perturbations such as pressure overload (PO), volume overload, and myocardial infarction with a single set of growth parameters. As these models move toward clinical applications, many of the most interesting applications involve predictions of whether or how a patient's heart will reverse its growth after an intervention. In the case of PO, significant regression in wall thickness is observed both experimentally and clinically following relief of overload, for example following replacement of a stenotic aortic valve. Therefore, the objective of this work was to evaluate the ability of a published cardiac growth model that captures forward growth in multiple situations to predict growth reversal following relief of PO. Using a finite element model of a beating canine heart coupled to a circuit model of the circulation, we quantitatively matched hemodynamic data from a canine study of aortic banding followed by unbanding. Surprisingly, although the growth model correctly predicted the time course of PO-induced hypertrophy, it predicted only limited growth reversal given the measured unbanding hemodynamics, contradicting experimental and clinical observations. We were able to resolve this discrepancy only by incorporating an evolving homeostatic setpoint for the governing growth equations. Furthermore, our analysis suggests that many strain- and stress-based growth laws using the traditional volumetric growth framework will have similar difficulties capturing regression following the relief of PO unless growth setpoints are allowed to evolve.

Indexed as

AlgorithmsAnimalsComputer SimulationConstriction, PathologicDogsFinite Element AnalysisHeartHeart FailureHemodynamicsHomeostasisHumansHypertrophyModels, CardiovascularMyocardial ContractionMyocardial InfarctionRegression AnalysisFinite element modelGrowthHypertrophyPressure overloadReverse growth

Identifiers

PMID31813071
PMCPMC8071348

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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 OpenQuestion graph.