Evidence map›Paper›PMID 42529503›Full record

ArticleJournal of precision medicine (Amsterdam, Netherlands)2026

Towards mechanisms-driven strategy for persistent atrial fibrillation ablation: Leveraging digital twins.

Kensuke Sakata, Natalia A Trayanova

Abstract read
In one paragraph

Article in Journal of precision medicine (Amsterdam, Netherlands), 2026. 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
–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

1 citing paper in PubMed.

  1. 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

2 authors.

Kensuke SakataAlliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St. Hackerman Hall 213, Baltimore, MD, 21218, USA.
Natalia A TrayanovaAlliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St. Hackerman Hall 213, Baltimore, MD, 21218, USA.ORCID 0000-0002-8661-063X

Funding

Artificial intelligence analysis of atrial remodeling evolution in patients with atrial fibrillation: Towards optimal ablation strategiesR01HL166759 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Eugene Kholmovski, David Spragg · 2023 to 2026
$3.2M
NHLBI NIH HHS R01 HL166759
6 · The paper itself

Abstract

Atrial fibrillation (AF) is the most common sustained arrhythmia, affecting 1-2% of the global population, and is a major cause of stroke and heart failure. With the population aging, its prevalence is expected to increase further, imposing a growing burden on healthcare systems. However, the gold standard treatment-pulmonary vein isolation with catheter ablation that primarily prevents pulmonary vein triggers from initiating fibrillatory conduction-has limited efficacy in the persistent form of AF (PsAF), which is characterized by atrial fibrotic remodeling. Thus far, numerous intra-atrial electrogram-based mapping approaches have been developed to identify PsAF arrhythmogenic substrate locations capable of attracting reentries (LRs) and guide substrate modification in clinical practice; however, their clinical effectiveness remains controversial and the optimal ablation strategy remains unclear. Furthermore, extensive substrate ablation may adversely affect patients post-ablation due to scar-related atrial tachycardia or impaired atrial function despite successful AF control. Recently, personalized heart digital twins (DTs) have emerged as a promising technology for precision medicine, enabling non-invasive patient-specific reconstruction of cardiac electrical activity using clinical imaging and electrophysiological data. Personalized DTs allow investigation of patient-specific electrophysiological behavior, prediction of arrhythmia inducibility, and identification of arrhythmogenic substrates pre-procedurally. In this review, we summarize the mechanisms underlying PsAF maintenance, current limitations of PsAF ablation therapy, and recent advances in DT technology, highlighting its potential to facilitate mechanism-driven, personalized ablation planning and improve PsAF patient care.

Indexed as

Digital twinDriverFibrosisPersistent atrial fibrillationSubstrate ablation

Identifiers

PMID42529503
PMCPMC13418435

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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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 Socratic graph.