The modified stepwise ablation guided by low-dose ibutilide in chronic atrial fibrillation trial (The MAGIC-AF Study)
Bibliographic record
Abstract
AIMS: Complex fractionated atrial electrograms (CFAE) are targeted during persistent atrial fibrillation (AF) ablation. However, many CFAE sites are non-specific resulting in extensive ablation. Ibutilide has been shown to reduce left atrial surface area exhibiting CFAE. We hypothesized that ibutilide administration prior to CFAE ablation would identify sites critical for persistent AF maintenance allowing for improved procedural efficacy and long-term freedom from atrial arrhythmias. METHODS AND RESULTS: Two hundred patients undergoing a first-ever persistent AF catheter ablation procedure were randomly assigned to receive either 0.25 mg of intravenous ibutilide or saline placebo upon completion of pulmonary vein isolation. Complex fractionated atrial electrogram sites were then targeted with ablation. The primary efficacy endpoint was the 1-year single procedure freedom from atrial arrhythmia off anti-arrhythmic drugs. Similar procedural characteristics (procedure, fluoroscopy, and ablation times) were observed with both strategies despite a greater reduction in left atrial surface area with CFAE sites (8 vs. 1%, P < 0.0001) and AF termination during CFAE ablation with ibutilide compared with placebo (75 vs. 57%, P = 0.007). The primary efficacy endpoint was achieved in 56% of patients receiving ibutilide and 49% receiving placebo (P = 0.35). No significant differences in peri-procedural complications were observed in both groups. CONCLUSION: Despite a reduction in CFAE area and greater AF termination during CFAE ablation, procedural characteristics and clinical outcomes were unchanged when CFAE ablation was guided by ibutilide administration. CLINICAL TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov number: NCT01014741.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".