Evidence mapPaperPMID 40860356Full record

ReviewFrontiers in cardiovascular medicine2025

Animal and cellular models of atrial fibrillation: a review.

Qiuying Wu, Xize Wu, Teng Feng, Feiyu Chen, Jiaqi Ren, Shan Gao, Bo Wang, Yue Li, Lihong Gong

Abstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

9 authors.

Qiuying Wu *The First Clinical College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Xize Wu *The First Clinical College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Teng Feng *The First Clinical College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Feiyu ChenThe First Clinical College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Jiaqi RenThe First Clinical College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Shan GaoThe First Clinical College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Bo WangThe First Clinical College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Yue LiDepartment of Cardiology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.
Lihong GongDepartment of Cardiology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modeling atrial fibrillation (AF) is crucial for investigating its pathogenesis and developing new therapeutic strategies. To better explore the mechanisms underlying AF and promote the progress of basic research, it is particularly important to develop accurate animal models that closely simulate the progression of clinical disease. This review summarizes the methods and evaluation criteria for establishing animal and cellular AF models over the past decade, highlighting the advantages and limitations of various models to provide a reference for basic research and treatment of AF. Current experimental animals are primarily categorized into small animals (mice, rats, rabbits), large animals (dogs, pigs, sheep, horses), and model organisms (zebrafish), with modeling methods including electrophysiological induction, chemical induction, trauma induction, and genetic editing. Cellular models commonly use primary cultured cardiomyocytes, the HL-1 cell line, hiPSC-CMs, and H9c2 cells as subjects of study. However, due to the lack of standardized modeling protocols, researchers evaluate AF models based on electrophysiological properties, atrial functional metrics, and biomarkers. Three-dimensional engineered tissues and artificial intelligence, as emerging fields, play an important role in the diagnosis, treatment, and prognostic monitoring of AF. This paper not only summarizes the current progress in AF model research but also points out the deficiencies of existing models, offering guidance for future research directions.

Indexed as

animal modelatrial fibrillationbiomarkerscellular modelreview

Identifiers

PMID40860356
PMCPMC12375624

What Socratic 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 Socratic graph.