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Record W4232625330 · doi:10.1161/circep.118.007142

Year in Review in Cardiac Electrophysiology

2019· review· en· W4232625330 on OpenAlexafffund
Wendy S. Tzou, Ayman A. Hussein, Malini Madhavan, Mohan Viswanathan, Benjamin A. Steinberg, Scott R. Ceresnak, Darryl R. Davis, David Park, Paul J. Wang, Suraj Kapa

Bibliographic record

VenueCirculation Arrhythmia and Electrophysiology · 2019
Typereview
Languageen
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsUniversity of Ottawa
FundersYork UniversityUniversity of OttawaCleveland Clinic
KeywordsCardiac electrophysiologyElectrophysiologyMedicineNeuroscienceInternal medicinePsychology

Abstract

fetched live from OpenAlex

In the past year, our field has seen publication of a number of studies that have potential immediate and far-reaching impact on our practice.Whether considering novel forms of achieving cardiac resynchronization via His bundle pacing (HBP), randomized clinical trials validating the utility of wearable technologies or atrial fibrillation (AF) ablation, or emerging techniques for management of ventricular fibrillation, publications from several investigators, teams, and multicenter collaborations have served to further our understanding of existing disease and consider new opportunities.In putting together this list of key articles from the past year, in addition to picking the top 25 articles from Circulation: Arrhythmia and Electrophysiology, we have also focused on major studies across the published literature.Although in this review we have sought to prioritize the highest impact research, we feel it is also important to highlight several evolving areas of study that may affect the rapidity, scope, and approach to research within our field.Augmented and virtual reality integration into the electrophysiology laboratory, artificial intelligence, and rapidly miniaturizing wearable technologies have the potential to exponentially alter our field, whether in the way we practice or the way we come to new understanding of disease and its management.Given the paucity of high-impact electrophysiology-related research published in these areas to date, but the equal importance for our readership to be aware of what may be on the horizon, we have included a brief discussion of these evolving techniques and associated publications in the Data Supplement. BASIC CARDIAC ELECTROPHYSIOLOGYThere were many advances in areas of basic cardiac electrophysiology ranging from application of genetic tools to better understanding electrophysiological disease to identifying potentially targetable molecular and protein mechanisms of arrhythmogenesis to characterizing the noncardiac milieu that drives evolution of substrate in a variety of different myocardial processes.Here, we focus on 2 publications that may have future consequences in clinical practice.Understanding the ionic basis of rhythm disease in the failing heart is essential if pharmacotherapeutics are to be effective.To this end, Hegyi et al 1 presented an elegant study that delves into the ionic mechanisms mediating the arrhythmic substrate in ischemic cardiomyopathy.Using a porcine postmyocardial infarct heart failure model, the authors studied the behavior of 8 ionic currents during the action potential of ventricular myocytes from the infarct border zone and a remote site.The summation of inward and outward currents occurred differently depending on location, with border-zone myocytes exhibiting action potential shortening and remote-zone myocytes displaying action potential prolongation.It follows that differential electrical remodeling increases proarrhythmia susceptibility by

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)0.001
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0260.010

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 head0.028
GPT teacher head0.337
Teacher spread0.309 · 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
GenreReview

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

Citations3
Published2019
Admission routes2
Has abstractyes

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