Evidence map›Paper›PMID 34571716›Full record

ArticleBiology2021

Personalized Evaluation of Atrial Complexity of Patients Undergoing Atrial Fibrillation Ablation: A Clinical Computational Study.

Ana María Sánchez de la Nava, Ana González Mansilla, Esteban González-Torrecilla, Pablo Ávila, Tomás Datino, Javier Bermejo, Ángel Arenal, Francisco Fernández-Avilés, Felipe Atienza

Open access · goldAbstract read
In one paragraph

Article in Biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Discovery ofBiology · 2023
    Article
  3. 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

9 authors at 4 institutions in 1 country.

Ana María Sánchez de la NavaDepartment of Cardiology, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain.
Ana González MansillaDepartment of Cardiology, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain.
Esteban González-TorrecillaDepartment of Cardiology, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain.
Pablo ÁvilaDepartment of Cardiology, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain.
Tomás DatinoDepartment of Cardiology, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain.
Javier BermejoDepartment of Cardiology, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain.
Ángel ArenalDepartment of Cardiology, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain.
Francisco Fernández-AvilésDepartment of Cardiology, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain.
Felipe AtienzaDepartment of Cardiology, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Hospital General Universitario Gregorio Marañón, 28009 Madrid, Spain.
Hospital General Universitario Gregorio Marañón · ESCentro de Investigación en Red en Enfermedades Cardiovasculares · ESUniversidad Complutense de Madrid · ESCentro de Investigación Biomédica en Red · ES

Funding

EIT Health 19600 AFFINEInstituto de Salud Carlos III DTS16/0160Instituto de Salud Carlos III PI16/01123Instituto de Salud Carlos III PI17/010559Instituto de Salud Carlos III PI17/01106Instituto de Salud Carlos III PI20/01618Ministerio de Ciencia e Innovación CIBER-CV
6 · The paper itself

Abstract

Current clinical guidelines establish Pulmonary Vein (PV) isolation as the indicated treatment for Atrial Fibrillation (AF). However, AF can also be triggered or sustained due to atrial drivers located elsewhere in the atria. We designed a new simulation workflow based on personalized computer simulations to characterize AF complexity of patients undergoing PV ablation, validated with non-invasive electrocardiographic imaging and evaluated at one year after ablation. We included 30 patients using atrial anatomies segmented from MRI and simulated an automata model for the electrical modelling, consisting of three states (resting, excited and refractory). In total, 100 different scenarios were simulated per anatomy varying rotor number and location. The 3 states were calibrated with Koivumaki action potential, entropy maps were obtained from the electrograms and compared with ECGi for each patient to analyze PV isolation outcome. The completion of the workflow indicated that successful AF ablation occurred in patients with rotors mainly located at the PV antrum, while unsuccessful procedures presented greater number of driving sites outside the PV area. The number of rotors attached to the PV was significantly higher in patients with favorable long-term ablation outcome (1-year freedom from AF: 1.61 ± 0.21 vs. AF recurrence: 1.40 ± 0.20;

Indexed as

ablationatrial fibrillationcomputational modelspersonalized models

Identifiers

PMID34571716
PMCPMC8469429
OpenAlexW3197933712

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.