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Record W4385303023 · doi:10.15420/ecr.2023.04

Ablation as First-line Therapy for Atrial Fibrillation

2023· review· en· W4385303023 on OpenAlexaff
Jason G. Andrade

Bibliographic record

VenueEuropean Cardiology Review · 2023
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversité de MontréalStornoway Diamond (Canada)Centre for Social InnovationMontreal Heart InstituteUniversity of British Columbia
FundersBiosense Webster
KeywordsMedicineCatheter ablationAtrial fibrillationSinus rhythmAdverse effectAblationCardiologyInternal medicineAblation TherapyQuality of life (healthcare)Intensive care medicineDiseaseCancer

Abstract

fetched live from OpenAlex

AF is a chronic and progressive heart rhythm disorder characterised by exacerbations and remissions. Contemporary guidelines recommend antiarrhythmic drugs (AADs) as the initial therapy for the maintenance of sinus rhythm. However, these medications have modest efficacy and are associated with significant adverse effects. Several recent trials have evaluated catheter ablation as an initial therapy for AF, demonstrating that cryoballoon catheter ablation significantly improves arrhythmia outcomes (e.g. atrial tachyarrhythmia recurrence and arrhythmia burden), produces clinically meaningful improvements in patient-reported outcomes (e.g. symptoms and quality of life), and significantly decreases healthcare resource usage (e.g. hospitalisation), without increasing the risk of serious adverse events. Moreover, in contrast to antiarrhythmic drugs, catheter ablation appears to be disease-modifying, significantly reducing the progression of disease. These findings are relevant to patients, providers, and healthcare systems, helping inform the initial choice of rhythm-control therapy in patients with treatment-naïve 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.254
GPT teacher head0.440
Teacher spread0.185 · 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 teacher head, not a consensus.

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

Citations17
Published2023
Admission routes1
Has abstractyes

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