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Record W4385340745 · doi:10.1136/heartjnl-2023-322428

Assessment and management of asymptomatic atrial fibrillation

2023· article· en· W4385340745 on OpenAlexaff
Jason G. Andrade, Marc W. Deyell, Richard G. Bennett, Laurent Macle

Bibliographic record

VenueHeart · 2023
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMontreal Heart InstituteBC Innovation CouncilUniversity of British Columbia
Fundersnot available
KeywordsMedicineAsymptomaticAtrial fibrillationSubclinical infectionCardiologyPopulationIntensive care medicineInternal medicineManagement of atrial fibrillation

Abstract

fetched live from OpenAlex

Atrial fibrillation (AF) is the most common sustained cardiac dysrhythmia encountered in practice. It is currently estimated that AF affects approximately 2% of the general population; however, the true prevalence of AF is likely to be at least 3%-4% when asymptomatic AF is considered. For clinically apparent AF, the investigations and management are relatively well established. The identification of minimally symptomatic patients is challenging, and furthermore, the optimal management is less certain. Although there is some debate about the ideal treatment pathway for asymptomatic AF, in most cases, the investigations and comprehensive management follow the same recommendations as clinically apparent AF. In contrast, beyond risk factor optimisation, the ideal management of subclinical or device-detected AF remains undefined. The purpose of the current review is to discuss the assessment and management of asymptomatic AF.

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)0.003
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.066
GPT teacher head0.386
Teacher spread0.320 · 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

Citations14
Published2023
Admission routes1
Has abstractyes

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