Evidence map›Paper›PMID 36843637›Full record

ArticlePhysics reports2022

The physics of heart rhythm disorders.

Wouter-Jan Rappel

Abstract read
In one paragraph

Article in Physics reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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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

13 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. How spatiotemporal dynamics can enhance ecosystem resilience.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Spatially Conserved Spiral Wave Activity During Human Atrial Fibrillation.Circulation. Arrhythmia and electrophysiology · 2024
    Article
  13. 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

1 author.

Wouter-Jan RappelDepartment of Physics, University of California San Diego, La Jolla, CA 92037.

Funding

The Dynamics of Human Atrial FibrillationR01HL083359 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Sanjiv M Narayan · 2008 to 2026
$7.9M
Patient-Directed Computational Analysis of Atrial FibrillationR01HL122384 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WOUTER-JAN RAPPEL · 2015 to 2026
$5.3M
Machine Learning in Atrial FibrillationR01HL149134 · NHLBI · STANFORD UNIVERSITY · PI NARAYAN, SANJIV M · 2020 to 2024
$3.8M
NHLBI NIH HHS R01 HL083359NHLBI NIH HHS R01 HL122384NHLBI NIH HHS R01 HL149134
6 · The paper itself

Abstract

The global burden caused by cardiovascular disease is substantial, with heart disease representing the most common cause of death around the world. There remains a need to develop better mechanistic models of cardiac function in order to combat this health concern. Heart rhythm disorders, or arrhythmias, are one particular type of disease which has been amenable to quantitative investigation. Here we review the application of quantitative methodologies to explore dynamical questions pertaining to arrhythmias. We begin by describing single-cell models of cardiac myocytes, from which two and three dimensional models can be constructed. Special focus is placed on results relating to pattern formation across these spatially-distributed systems, especially the formation of spiral waves of activation. Next, we discuss mechanisms which can lead to the initiation of arrhythmias, focusing on the dynamical state of spatially discordant alternans, and outline proposed mechanisms perpetuating arrhythmias such as fibrillation. We then review experimental and clinical results related to the spatio-temporal mapping of heart rhythm disorders. Finally, we describe treatment options for heart rhythm disorders and demonstrate how statistical physics tools can provide insights into the dynamics of heart rhythm disorders.

Indexed as

ArrhythmiasFibrillationHeart rhythm disordersModeling

Identifiers

PMID36843637
PMCPMC9949723

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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.