Evidence map›Paper›PMID 31427780›Full record

ArticleNature biomedical engineering2019

Computationally guided personalized targeted ablation of persistent atrial fibrillation.

Patrick M Boyle, Tarek Zghaib, Sohail Zahid, Rheeda L Ali, Dongdong Deng, William H Franceschi, Joe B Hakim, Michael J Murphy, Adityo Prakosa, Stefan L Zimmerman and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature biomedical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 184 papers.

0numbers the graph read from it
0cells of the map it votes in
184citing papers in PubMed
21.7field-weighted citation impact, top 1% 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

184 citing papers in PubMed, 302 citations in OpenAlex.

  1. Trial
  2. Article
  3. AI-enabled clinical trials.Nature reviews bioengineering · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

124 more citing papers are in PubMed but not listed here.

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

17 authors at 2 institutions in 1 country.

Patrick M BoyleDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Tarek ZghaibDivision of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Sohail ZahidDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Rheeda L AliInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
Dongdong DengInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
William H FranceschiDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Joe B HakimInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
Michael J MurphyDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Adityo PrakosaInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
Stefan L ZimmermanDepartment of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-9422-6742
Hiroshi AshikagaDivision of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0003-3689-6892
Joseph E MarineDivision of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Aravindan KolandaiveluDivision of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Saman NazarianDivision of Cardiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
David D SpraggDivision of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Hugh CalkinsDivision of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Natalia A TrayanovaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. ntrayanova@jhu.edu.ORCID http://orcid.org/0000-0002-8661-063X
Johns Hopkins University · USUniversity of Pennsylvania · US

Funding

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
American Heart Association-American Stroke Association 16SDG30440006NHLBI NIH HHS DP1 HL123271NHLBI NIH HHS R01 HL126802NHLBI NIH HHS U01 HL141074
6 · The paper itself

Abstract

Atrial fibrillation (AF)-the most common arrhythmia-significantly increases the risk of stroke and heart failure. Although catheter ablation can restore normal heart rhythms, patients with persistent AF who develop atrial fibrosis often undergo multiple failed ablations, and thus increased procedural risks. Here, we present personalized computational modelling for the reliable predetermination of ablation targets, which are then used to guide the ablation procedure in patients with persistent AF and atrial fibrosis. First, we show that a computational model of the atria of patients identifies fibrotic tissue that, if ablated, will not sustain AF. Then, we report the results of integrating the target ablation sites in a clinical mapping system and testing its feasibility in ten patients with persistent AF. The computational prediction of ablation targets avoids lengthy electrical mapping and could improve the accuracy and efficacy of targeted AF ablation in patients while eliminating the need for repeat procedures.

Indexed as

Arrhythmias, CardiacAtrial FibrillationCatheter AblationComputational BiologyFeasibility StudiesFibrosisHeart AtriaHumansImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingProspective StudiesSurgery, Computer-Assisted

Identifiers

PMID31427780
PMCPMC6842421
OpenAlexW2969852609

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.