Vernakalant and electrical cardioversion for AF – Safe and effective
Bibliographic record
Abstract
AIMS: Rapid restoration of sinus rhythm is an integral part of the management of recent-onset atrial fibrillation. We aimed to assess safety and efficacy of vernakalant, a multi-channel blocking agent, in combination with external electrical cardioversion. METHODS: This prospective cohort study comprised 230 patients (female 35%; median age 50 IQR 42-55) with recent-onset AF presenting to a university tertiary care center during a 6-year period. Management included intravenous vernakalant followed by electrical cardioversion in case of pharmacological failure. RESULTS: Within 11 min (IQR 8-29), sinus rhythm could be restored by sole pharmacological management in 167 patients (73%). A left ventricular function lower than 55% (OR 3.51 (1.45-8.52)) and prior atrial fibrillation episodes being classified as persistent (OR 2.33 (1.13-4.80)) were significant predictors for non-response to vernakalant. Electrical cardioversion was successful in all patients but one within 196 min (IQR 149-300) of administration of first dosage of vernakalant. No serious adverse events could be observed. 3 patients needed further in-patient care. CONCLUSION: Management of recent-onset atrial fibrillation consisting of intravenous vernakalant followed by electrical cardioversion in case of failure appears safe and efficacious. Achieving a rapid conversion, this approach could potentially save resources and costs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".