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Record W4416118393 · doi:10.1136/bmj-2025-085632

Vernakalant versus procainamide for rapid cardioversion of patients with acute atrial fibrillation (RAFF4): randomised clinical trial

2025· article· en· W4416118393 on OpenAlexafffundabout
Ian G. Stiell, Monica Taljaard, Debra Eagles, Krishan Yadav, Alain Vadeboncœur, Corinne M. Hohl, Patrick Archambault, David H. Birnie, Erica Brown, Samuel Campbell, Yutong Chen, Catherine M. Clement, Alexis Cournoyer, Kerstin de Wit, Marcel Émond, Laurent Macle, Andrew D. McRae, Éric Mercier, Judy Morris, Ghadeer Mohamad, Marie‐Joe Nemnom, Stuart G. Nicholls, David Paré, Ratika Parkash, Marco L.A. Sivilotti, Kednapa Thavorn, Jeffrey J. Perry

Bibliographic record

VenueBMJ · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversité LavalSouth Health CampusUniversity of CalgaryQueen's UniversityInstitut universitaire de cardiologie et de pneumologie de QuébecHôpital de l'Enfant-JésusCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalDalhousie UniversityCentre Intégré de Santé et Services Sociaux de Chaudière-AppalacheCentre hospitalier de l'Université LavalMontreal Heart InstituteUniversity of British ColumbiaVancouver Coastal Health Research InstituteVancouver Coastal HealthUniversité de MontréalOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsProcainamideCardioversionAtrial fibrillationClinical trialAnti-Arrhythmia AgentsRandomized controlled trialFibrillation

Abstract

fetched live from OpenAlex

Abstract Objective To conduct a randomised, open label comparison of the effectiveness and safety of intravenous vernakalant and intravenous procainamide for the management of acute atrial fibrillation in the emergency department. Design Randomised clinical trial (RAFF4 trial). Setting 12 tertiary care emergency departments in Canada. Participants Patients with acute atrial fibrillation for whom acute rhythm control was a safe option. Interventions Patients were randomised (1:1) to an intravenous infusion of vernakalant or procainamide; when rapid conversion did not occur, patients were offered electrical cardioversion. Main outcomes and measures The primary outcome was conversion to sinus rhythm within 30 minutes of drug infusion completion. Secondary outcomes included time to conversion to sinus rhythm and whether the patient required electrical cardioversion. Results Of the 350 enrolled eligible patients, baseline characteristics were similar in the procainamide (n=172) and vernakalant (n=178) groups. For the primary outcome of conversion success, vernakalant was more effective (62.4% v 48.3%; adjusted absolute difference 15.0%, 95% confidence interval 4.6% to 25.0%, P=0.005; adjusted odds ratio 1.87, 95% confidence interval 1.2 to 2.9, P=0.006). With vernakalant, time to conversion was faster (21.8 v 44.7 minutes; mean difference −22.9, 95% confidence interval −29.9 to −16.0, P<0.001), and fewer patients underwent attempted electrical cardioversion (33.7% v 44.2%; odds ratio 0.62, 95% confidence interval 0.39 to 0.96, P=0.033). Adverse events were similar in both groups, were generally mild and brief, and most patients were discharged home. Subgroup analysis strongly favoured vernakalant for conversion in patients younger than 70 years (73.3% v 47.2%; adjusted odds ratio 3.1, 95% confidence interval 1.7 to 5.5, P=0.001, interaction P=0.005). Conclusions In this head-to-head comparison, vernakalant was superior to procainamide for patients with higher conversion rates and faster times to conversion. Therefore, vernakalant is a safe and highly effective intravenous alternative for the rapid cardioversion and discharge home of patients with acute atrial fibrillation. Trial registration ClinicalTrials.gov NCT04485195

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)0.003
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.063
GPT teacher head0.395
Teacher spread0.332 · 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 designRandomized trial
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

Citations3
Published2025
Admission routes3
Has abstractyes

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