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Record W4233671653 · doi:10.1093/europace/euab246

New evidence: Cryoballoon ablation vs. antiarrhythmic drugs for first-line therapy of atrial fibrillation

2021· article· en· W4233671653 on OpenAlexaff
Jason G. Andrade, Gian‐Battista Chierchia, Malte Kuniss, Oussama M. Wazni

Bibliographic record

VenueEP Europace · 2021
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversité de MontréalMontreal Heart InstituteUniversity of British Columbia
FundersMedtronic
KeywordsMedicineAtrial fibrillationAdverse effectCatheter ablationSinus rhythmCardiologyInternal medicineIntensive care medicineQuality of life (healthcare)Clinical trialAblationRandomized controlled trialClinical PracticePhysical therapy

Abstract

fetched live from OpenAlex

Atrial fibrillation (AF) is a commonly encountered chronic and progressive heart rhythm disorder, characterized by exacerbations and remissions. Contemporary clinical practice guidelines recommend a trial of antiarrhythmic drugs (AADs) as the initial therapy for sinus rhythm maintenance; however, these medications have modest efficacy and are associated with significant adverse effects. Recently, several trials have demonstrated that an initial treatment strategy of cryoballoon catheter ablation significantly improves arrhythmia outcomes (e.g. freedom atrial tachyarrhythmia and reduction in arrhythmia burden), produces clinically meaningful improvements in patient-reported outcomes (e.g. symptoms and quality of life), and significantly reduces subsequent healthcare resource utilization (e.g. hospitalization), without increasing the risk of serious or any adverse events. These findings are relevant to patients, providers, and healthcare systems, helping inform the decision regarding 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.351
Teacher spread0.275 · 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.

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

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

Citations5
Published2021
Admission routes1
Has abstractyes

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