Evidence map›Paper›PMID 30233399›Full record

ReviewFrontiers in physiology2018

Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges.

Márcia Vagos, Ilsbeth G M van Herck, Joakim Sundnes, Hermenegild J Arevalo, Andrew G Edwards, Jussi T Koivumäki

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in physiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
5.3field-weighted citation impact, top 3% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
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  5. Article
  6. Overview of Cardiac Arrhythmias and Treatment Strategies.Pharmaceuticals (Basel, Switzerland) · 2023
    Review
  7. Article
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  20. Doxycycline Improves Fibrosis-Induced Abnormalities in Atrial Conduction and Vulnerability to Atrial Fibrillation in Chronic Intermittent Hypoxia Rats.Medical science monitor : international medical journal of experimental and clinical research · 2020
    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

6 authors at 3 institutions in 2 countries.

Márcia VagosComputational Physiology Department, Simula Research Laboratory, Lysaker, Norway.
Ilsbeth G M van HerckComputational Physiology Department, Simula Research Laboratory, Lysaker, Norway.
Joakim SundnesComputational Physiology Department, Simula Research Laboratory, Lysaker, Norway.
Hermenegild J ArevaloComputational Physiology Department, Simula Research Laboratory, Lysaker, Norway.
Andrew G EdwardsComputational Physiology Department, Simula Research Laboratory, Lysaker, Norway.
Jussi T KoivumäkiBioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland.
Innovation Norway (Norway) · NOSimula Research Laboratory · NOUniversity of Eastern Finland · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pathophysiology of atrial fibrillation (AF) is broad, with components related to the unique and diverse cellular electrophysiology of atrial myocytes, structural complexity, and heterogeneity of atrial tissue, and pronounced disease-associated remodeling of both cells and tissue. A major challenge for rational design of AF therapy, particularly pharmacotherapy, is integrating these multiscale characteristics to identify approaches that are both efficacious and independent of ventricular contraindications. Computational modeling has long been touted as a basis for achieving such integration in a rapid, economical, and scalable manner. However, computational pipelines for AF-specific drug screening are in their infancy, and while the field is progressing quite rapidly, major challenges remain before computational approaches can fill the role of workhorse in rational design of AF pharmacotherapies. In this review, we briefly detail the unique aspects of AF pathophysiology that determine requirements for compounds targeting AF rhythm control, with emphasis on delimiting mechanisms that promote AF triggers from those providing substrate or supporting reentry. We then describe modeling approaches that have been used to assess the outcomes of drugs acting on established AF targets, as well as on novel promising targets including the ultra-rapidly activating delayed rectifier potassium current, the acetylcholine-activated potassium current and the small conductance calcium-activated potassium channel. Finally, we describe how heterogeneity and variability are being incorporated into AF-specific models, and how these approaches are yielding novel insights into the basic physiology of disease, as well as aiding identification of the important molecular players in the complex AF etiology.

Indexed as

atrial fibrillationcomputational modelingdrug therapiesin silico drug screeningpathophysiologypharmacodynamicspharmacology

Identifiers

PMID30233399
PMCPMC6131668
OpenAlexW2892204555

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.