Evidence map›Paper›PMID 30755334›Full record

ReviewInternational journal of cardiology2019

The role of personalized atrial modeling in understanding atrial fibrillation mechanisms and improving treatment.

Konstantinos N Aronis, Rheeda Ali, Natalia A Trayanova

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in International journal of cardiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Review
  15. Review
  16. Review
  17. Article
  18. Review
  19. 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.

Konstantinos N AronisDepartment of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA; Division of Cardiology, Johns Hopkins Hospital, Baltimore, MD, USA.
Rheeda AliDepartment of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
Natalia A TrayanovaDepartment of Biomedical Engineering and the Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA. Electronic address: ntrayanova@jhu.edu.

Funding

PATHOPHYSIOLOGY OF MYOCARDIAL DISEASEST32HL007227 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Chulan Kwon, WENDY S POST · 1985 to 2026
$21.2M
Virtual Electrophysiology LaboratoryDP1HL123271 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TRAYANOVA, NATALIA A. · 2013 to 2017
$4.0M
Simulation Guidance of Ablation Therapy for Persistent Atrial FibrillationU01HL141074 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI CALKINS, HUGH G, TRAYANOVA, NATALIA A. · 2018 to 2021
$3.1M
Exploration of Arrhythmogenic Triggers and Substrates in Heart FailureR01HL126802 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI EFIMOV, IGOR R, GORELIK, JULIA · 2016 to 2019
$2.8M
Implications of Intra-Myocardial Fat Deposition upon Propensity for Malignant ArrhythmiaR01HL142893 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI NAZARIAN, SAMAN, TRAYANOVA, NATALIA A. · 2018 to 2021
$2.5M
NHLBI NIH HHS DP1 HL123271NHLBI NIH HHS R01 HL126802NHLBI NIH HHS R01 HL142893NHLBI NIH HHS T32 HL007227NHLBI NIH HHS U01 HL141074
6 · The paper itself

Abstract

Atrial fibrillation is the most common arrhythmia in humans and is associated with high morbidity, mortality and health-related expenses. Computational approaches have been increasingly utilized in atrial electrophysiology. In this review we summarize the recent advancements in atrial fibrillation modeling at the organ scale. Multi-scale atrial models now incorporate high level detail of atrial anatomy, tissue ultrastructure and fibrosis distribution. We provide the state-of-the art methodologies in developing personalized atrial fibrillation models with realistic geometry and tissue properties. We then focus on the use of multi-scale atrial models to gain mechanistic insights in AF. Simulations using atrial models have provided important insight in the mechanisms underlying AF, showing the importance of the atrial fibrotic substrate and altered atrial electrophysiology in initiation and maintenance of AF. Last, we summarize the translational evidence that supports incorporation of computational modeling in clinical practice for development of personalized treatment strategies for patients with AF. In early-stages clinical studies, AF models successfully identify patients where pulmonary vein isolation alone is not adequate for treatment of AF and suggest novel targets for ablation. We conclude with a summary of the future developments envisioned for the field of atrial computational electrophysiology.

Indexed as

Atrial FibrillationComputer SimulationModels, CardiovascularCatheter AblationHeart AtriaHumansImaging, Three-DimensionalMagnetic Resonance Imaging, CineTomography, X-Ray Computed

Identifiers

PMID30755334
PMCPMC6513696

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.