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Enregistrement W4387117193 · doi:10.3389/fcvm.2023.1280925

Editorial: Atrial fibrillation: insights on mechanisms, mapping and catheter ablation

2023· editorial· en· W4387117193 sur OpenAlexaff
Sergio Conti, Atul Verma, Andrea Natale, Claudio Tondo

Notice bibliographique

RevueFrontiers in Cardiovascular Medicine · 2023
Typeeditorial
Langueen
DomaineMedicine
ThématiqueAtrial Fibrillation Management and Outcomes
Établissements canadiensMcGill University Health Centre
Organismes subventionnairesnon disponible
Mots-clésAtrial fibrillationCatheter ablationMedicineCardiologyAblationInternal medicine

Résumé

récupéré en direct d'OpenAlex

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia and is associated with an increased risk of stroke, heart failure, and mortality [1]. The number of patients affected is expected to grow continuously in the following years, owing to extended longevity in the general population and intensifying screening for undiagnosed AF [1]. In recent years, significant progress has been made regarding identifying and treating risk factors, evaluating electrical and structural remodeling, preprocedural imaging, understanding electrophysiological mechanisms and substrates underlying AF, and ablation strategies and technologies. The main "players" widely recognized as the mechanisms underlying AF are the pulmonary veins (PVs) and extra-PVs triggers and their interaction with the left atrial substrate. A better understanding of these mechanisms has influenced AF's mapping and ablation strategies. In particular, technological and technical improvements of catheter ablation are highly impressive. Indeed, the continuous implementation of new technologies has made AF ablation faster, more effective, and safer. Within the last years, high-definition mapping technologies, additional improvements with novel point-by-point radiofrequency (RF), and single-shot devices have captured the interest of most of the scientific community. The most important innovation, however, seems to be the introduction of pulsed-field ablation (PFA) technology.In addition, research is rich in new publications focusing on the timing of AF treatment. The findings of the EAST-AFNET 4 are giving further impulse to the electrophysiology community to propose a prompt treatment of atrial fibrillation [2]. Since the late 90s, catheter ablation emerged as a promising treatment strategy for patients with AF. After the seminal work of Haissaguerre et al. [3] led to the development of pulmonary vein isolation (PVI), aiming at electrical disconnection of the PVs, nowadays catheter ablation is a well-established treatment for patients with symptomatic, drug-refractory AF. Recent guidelines clearly state that the cornerstone of any AF ablation procedure is the complete isolation of the PVs by linear lesions around their antrum, either using pointby-point RF ablation or single-shot ablation devices, irrespective of the AF type [1]. However, there is still a lack of consensus regarding the ablation strategy to be adopted, especially in specific sets of patients.Through contributions from leading experts in the field, the present Special Issue presents a contemporary perspective on AF mechanisms, mapping, and catheter ablation. In recent years, several studies focused on defining the substrate of the left atrium in patients with AF. The ERASE-AF trial recently showed that ablation of fibrotic tissue determined by mapping low-voltage areas improved the outcome in patients with persistent AF [4]. In this Issue, Shao et al. evaluated the role of left atrial epicardial adipose tissue and low-voltage areas. Moreover, two reviews have been included in the Issue focused on how to deal with and manage atrial fibrotic tissue. In the RF field, after contact force sensing catheters, the introduction of more advanced lesion parameters, such as the Ablation Index (AI) and Lesion1 Index (LSI), allowed operators to perform ablation procedures more safely and efficiently. The reader of the Issue will find insights on the lesion durability of LSIguided PVI and the risk factors for late reconnections of PVs in the paper of Mujovic et al. Liu et al. compared the role of AI in guiding AF ablation using high-power versus low-power settings. Beyond PVI, the optimal ablation strategy remains a matter of debate. The role of the vein of Marshall has been assessed in the VENUS randomized clinical trial and, more recently, in the prospective single-center Marshall-PLAN [5,6]. Langmuur et al. reported an accurate method to localize the ligament of Marshall by using unipolar electrograms in activation and voltage maps.Finally, what can be a real game-changer in the treatment of AF, or at least it has been expected, is the introduction in the clinical practice of PFA. An increasing body of evidence confirms the more than promising outcomes of this new technology. The PULSED AF Pivotal trial reported that PFA was successful at treating AF at 12 months in 66.2% of patients with paroxysmal AF and 55.1% with persistent AF [7]. In this Issue, Magni et al. reported their initial experience on a large population undergoing AF ablation using PFA.There is no doubt that more has to come from ongoing and future research, particularly in the field of tailored approaches in persistent and long-standing persistent AF patients, imaging and substrate mapping integration, comparison between different technologies, and evaluation of long-term outcomes. In the meantime, we hope the Frontiers in Cardiovascular Medicine readers will find the current Special Issue interesting and helpful in broadening their knowledge of current state-of-the-art AF research.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,019
Score d'incertitude au seuil0,062

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,017
Méta-épidémiologie (sens strict)0,0050,001
Méta-épidémiologie (sens large)0,0050,003
Bibliométrie0,0040,001
Études des sciences et des technologies0,0020,003
Communication savante0,0060,006
Science ouverte0,0040,001
Intégrité de la recherche0,0120,016
Charge utile insuffisante (le modèle a refusé de juger)0,0190,018

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,024
Tête enseignante GPT0,277
Écart entre enseignants0,253 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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