Evidence map›Paper›PMID 35892747›Full record

ArticleBioengineering (Basel, Switzerland)2022

A Computationally Efficient Approach to Simulate Heart Rate Effects Using a Whole Human Heart Model.

Jiang Yao, Shawn Chen, Julius M Guccione

Open access · goldAbstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2022. 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
0.5field-weighted citation impact, top 34% of its field
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, 3 citations in OpenAlex.

  1. 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

3 authors at 3 institutions in 1 country.

Jiang YaoDassault Systèmes, Johnston, RI 02919, USA.
Shawn ChenAbbott, Sylmar, CA 91342, USA.
Julius M GuccioneDepartment of Surgery, University of California at San Francisco, San Francisco, CA 94143, USA.
Abbott (United States) · USDassault Systèmes (United States) · USUniversity of California, San Francisco · US

Funding

Multi-Scale Laws of Myocardial Growth and RemodelingU01HL119578 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GUCCIONE, JULIUS MATTEO, KASSAB, GHASSAN S · 2014 to 2018
$3.8M
VIRTUAL TOOLS FOR CARDIAC VENTRICULAR REMODELING SURGERYR01HL077921 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GUCCIONE, JULIUS MATTEO · 2006 to 2015
$3.4M
Minimally Invasive Ventricular Polymeric Injection for Treatment of Heart FailureR01HL118627 · NHLBI · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI GUCCIONE, JULIUS MATTEO, KASSAB, GHASSAN S · 2013 to 2016
$3.0M
NIH HHS R01-HL-077921NIH HHS R01-HL-118627NIH HHS U01-HL-119578
6 · The paper itself

Abstract

Computational modeling of the whole human heart has become a valuable tool to evaluate medical devices such as leadless pacemakers, annuloplasty rings and left ventricular assist devices, since it is often difficult to replicate the complex dynamic interactions between the device and human heart in bench-top and animal tests. The Dassault Systèmes Living Heart Human Model (LHHM) is a finite-element model of whole-human-heart electromechanics that has input parameters that were previously calibrated to generate physiological responses in a healthy heart beating at 60 beat/min (resting state). This study demonstrates that, by adjusting only six physiologically meaningful parameters, the LHHM can be recalibrated to generate physiological responses in a healthy heart beating at heart rates ranging from 90−160 beat/min. These parameters are as follows: the sinoatrial node firing period decreases from 0.67 s at 90 bpm to 0.38 s at 160 bpm, atrioventricular delay decreases from 0.122 s at 90 bpm to 0.057 s at 160 bpm, preload increases 3-fold from 90 bpm to 160 bpm, body resistance at 160 bpm is 80% of that at 90 bpm, arterial stiffness at 160 bpm is 3.9 times that at 90 bpm, and a parameter relating myofiber twitch force duration and sarcomere length decreases from 238 ms/mm at 90 bpm to 175 ms/mm at 160 bpm. In addition, this study demonstrates the feasibility of using the LHHM to conduct clinical investigations in AV delay optimization and hemodynamic differences between pacing and exercise. AV delays in the ranges of 40 ms to 250 ms were simulated and stroke volume and systolic blood pressure showed clear peaks at 120 ms for 90 bpm. For a heart during exercise, the increase in cardiac output continues to 160 bpm. However, for a heart during pacing, those physiological parameter adjustments are removed that are related to changes in body oxygen requirements (preload, arterial stiffness and body resistance). Consequently, cardiac output increases initially with heart rate; as the heart rate goes up (>100 bpm), the increasing rate of cardiac output slows down and approaches a plateau.

Indexed as

AV delaycomputational modelingexerciseleadless pacemakersnormal cardiac physiologyregional electromechanics

Identifiers

PMID35892747
PMCPMC9331290
OpenAlexW4287009225

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.