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Record W3165515891 · doi:10.1093/cvr/cvab170

Challenges and opportunities in improving the management of atrial fibrillation: recent research advances and their clinical translation

2021· editorial· en· W3165515891 on OpenAlexafffund
Stanley Nattel, Gregory Y.H. Lip, David Filgueiras‐Rama, Dobromir Dobrev

Bibliographic record

VenueCardiovascular Research · 2021
Typeeditorial
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversité de MontréalMcGill UniversityMontreal Heart Institute
FundersNational Institutes of HealthDeutsche ForschungsgemeinschaftEuropean CommissionInstituto de Salud Carlos IIICanadian Institutes of Health ResearchNational Institute for Health and Care ResearchMinisterio de Ciencia e InnovaciónNational Heart, Lung, and Blood InstituteCentro Nacional de Investigaciones CardiovascularesHeart and Stroke Foundation of Canada
KeywordsAtrial fibrillationMedicineTranslation (biology)CardiologyIntensive care medicineInternal medicineBiology

Abstract

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Atrial fibrillation (AF) is a problem of major clinical importance, accounting for about 9 million cases in the European Union in 2010 with projections for an almost doubling by 2060.1 The worldwide economic burden of AF was estimated at 6 million disability-adjusted life-years of lost productivity in 2017.2 The average 3-year societal cost per patient in Denmark attributable to AF over the period 2001–2012 was estimated to be of the order of 25 000 Euros ($30 000), providing an overall cost burden in Europe of the order of 10 billion Euros.3 Clearly, AF is a major issue at the level of public health and economic burden, motivating the regular establishment of detailed society guidelines, including two in the last year.4,5 Not only is AF a substantial public health problem at the moment, but its impact is projected to increase in the future. The prevalence of AF increases exponentially with advancing age6 and with population-ageing projections point to an almost 90% increase in the number of elderly AF patients in the European Union by 2060.7 Modelling of UK data illustrate major projected increases in AF-related healthcare costs over the next decades, largely from hospitalizations.8 Improving the management of AF is an important goal that has motivated major investigative efforts, but substantial challenges remain.9 Improvements in understanding the basic mechanisms of AF and translating them clinically with rapidly advancing technologies are key to combating AF and its human/ societal/ economic consequences. Recognizing the importance of this area and the active efforts being made in the field, the Editorial Board of Cardiovascular Research decided to create an issue of the journal focused on the problem of effective clinical translation of advances in basic AF research. The issue includes nine invited review articles, as illustrated in Figure 1. Lin et al. discuss the use of multiomic approaches, including genomics, epigenomics, transcriptomics, metabolomics, and their integration for the discovery of novel biomarkers that can be used to stage AF, follow its course and evaluate the results of its management. Kany et al. have provided a state-of-the-art paper on AF genetics, dealing with their practical application to guiding the management of AF and priorities/prospects for future development. Lip et al. deal with the rapidly evolving area of artificial intelligence and machine-learning, discussing its enormous capacity to identify novel ways to diagnose, characterize, prevent, and treat AF. The classification and characterization of AF and its response to treatment is an important challenge; Boriani et al. analyse the use of novel non-invasive criteria, particularly the quantification of AF burden, as indices of the arrhythmia. Aguilar et al. review the highly significant but often underappreciated subject of endocrine control of AF. In addition to the fundamental mechanisms and clinical aspects of the atrial effects of well-recognized endocrine factors like diabetes, abnormalities in thyroxin production, obesity, the renin-angiotensin system, and sex hormones, they discuss recent insights into the role of natriuretic peptides, adrenal cortical and medullary products, hypothalamic-pituitary hormones, and the thyroid hormone calcitonin in AF control. A schematic illustration of the clinical importance of AF, along with the various topics dealt with in the invited review articles of the present issue. The principal consequences of AF that are illustrated include associated morbidity, mortality, and economic costs. The double-line surrounding AF and its consequences indicates the difficulty of making a significant impact by innovations in diagnosis, prevention, and therapy. Eight of the review articles deal with specific themes of AF research and one review paper discusses in a more general way the challenges and obstacles to clinical translation of novel basic research insights, as well as some potential solutions. AF, atrial fibrillation. A schematic illustration of the clinical importance of AF, along with the various topics dealt with in the invited review articles of the present issue. The principal consequences of AF that are illustrated include associated morbidity, mortality, and economic costs. The double-line surrounding AF and its consequences indicates the difficulty of making a significant impact by innovations in diagnosis, prevention, and therapy. Eight of the review articles deal with specific themes of AF research and one review paper discusses in a more general way the challenges and obstacles to clinical translation of novel basic research insights, as well as some potential solutions. AF, atrial fibrillation. Ablation has emerged as the single most effective approach to maintaining normal sinus rhythm in patients who have experienced AF. Filgueiras-Rama et al. deal with this important area, reviewing in detail the prospects for materially improving the success of these important procedures by targeting the basic mechanisms underlying AF initiation and maintenance, with the exploitation of new knowledge and technologies. These authors also describe practical challenges that scientists and clinicians face when attempting to implement novel mapping methods into regular clinical practice. It has long been known that the autonomic nervous system (ANS) plays a key role in AF occurrence.10 Shivkumar et al. discuss the active research being performed to harness interventions acting via ANS modulation to suppress AF and prevent its recurrence and maintenance. Research in AF generates a wide range of information at the molecular, subcellular, cellular, tissue, organ, organismal, human-subject, and population levels. These disparate sets of data need to be integrated in order to realistically determine their implications for arrhythmia likelihood and burden. Heijman et al. discuss a critical tool in the integration, validation, and application of research discoveries, the use of computational modelling. Rapid advances in computing technology have permitted the analysis of massive amounts of data and the creation of integrative and population models that permit the quantitative testing of important hypotheses about AF risk and its mechanisms, predictors, and modifiers. Finally, once all of these discoveries are made, they need to be converted into effective, safe, and practical clinical tools to improve the management of AF patients, a process often called ‘clinical translation’. Nattel et al. provide an overview of the challenges to translating basic research discoveries to clinically applicable innovations in AF management, dealing with such issues as the consequences of the regulatory and commercial landscape, the need for, availability and limitations of animal models, the alternatives to animal models (like heart cells and engineered tissue derived from human induced pluripotent stem cells), and possible paths forward to overcome impasses in therapeutic development and implementation. In addition, the issue contains a number of highly innovative original articles presenting new research findings in this area. These articles deal with topics like the role of the NLRP3 (NOD-, LRR-, and pyrin domain-containing protein 3) as a mediator of the AF-promoting effects of obesity, the effects of a molecule that promotes the resolution of inflammatory changes in a rat model of AF associated with right heart disease, the transcriptomic and proteomic landscape of AF progression in a chronic sheep model, and the involvement of calcium-handling abnormalities in post-operative AF. We are very excited about this issue, which we hope will both inform readers of Cardiovascular Research interested in this area and stimulate further research and development to tackle this important problem. This work was supported by the Canadian Institutes of Health Research and the Quebec Heart and Stroke Foundation (to S.N.), the National Institutes of Health (R01-HL131517, R01-HL136389, and R01-HL089598 to D.D.), the European Union (large-scale network project MAESTRIA, No. 965286 to D.D. and D.F-R.), the German Research Foundation (DFG, Do 769/4-1 to D.D.), the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia e Innovación, and the Pro CNIC Foundation, the Severo Ochoa Center of Excellence (SEV-2015-0505 to D.F.-R.), and the Spanish Ministry of Science and Innovation (to D.F-R., PID2019-109329RB-I00). Conflict of interest: S.N.: Consultant for LQTS Therapeutics. G.Y.H.L.: Consultant and speaker for BMS/Pfizer, Boehringer Ingelheim, and Daiichi-Sankyo. No fees are received personally. D.F.-R.: Co-inventor on a patent (Patent#EP3636147A1) related to a method for the identification of cardiac fibrillation drivers and the footprint of rotational activations. D.D.: Scientific advisory board member for OMEICOS Therapeutics GmbH and Acesion Pharma. The opinions expressed in this article are not necessarily those of the Editors of Cardiovascular Research or of the European Society of Cardiology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.017
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.067
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0040.003
Science and technology studies0.0020.003
Scholarly communication0.0090.007
Open science0.0030.002
Research integrity0.0110.017
Insufficient payload (model declined to judge)0.0100.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.477
GPT teacher head0.483
Teacher spread0.005 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2021
Admission routes2
Has abstractyes

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