Bayesian network meta‐analysis comparing cryoablation, radiofrequency ablation, and antiarrhythmic drugs as initial therapies for atrial fibrillation
Bibliographic record
Abstract
BACKGROUND: Antiarrhythmic drugs (AADs) and catheter ablation are first line treatments of paroxysmal atrial fibrillation (PAF), however, there exists a paucity of data regarding the potential benefit of different catheter ablation technologies versus AADs as an early rhythm strategy. OBJECTIVE: To assess the safety and efficacy of cryoablation versus radiofrequency ablation (RFA) versus AADs as a first line therapy of PAF. METHODS: MEDLINE, Embase, Scopus and CENTRAL were searched to retrieve randomized clinical trials (RCTs) comparing cryoablation, RFA or AADs to one another as first line therapies for atrial fibrillation (AF). The primary outcome was overall freedom from arrhythmia recurrence (AF, atrial flutter [AFL], atrial tachycardia). Secondary outcomes included freedom from symptomatic arrhythmia recurrence, hospitalization, and serious adverse events. A random-effects Bayesian network meta-analysis was used to calculate odds ratios (OR) and 95% credible intervals (CrI). RESULTS: Six RCTs (N = 1212) met the inclusion criteria (605 AADs, 365 Cryoablation, and 245 RFA). Compared with AADs, overall recurrence was reduced with RFA (OR: 0.31; 95% CrI: 0.10-0.71) and cryoablation (OR: 0.39; 95% CrI: 0.16-1.00). Comparing ablation (cryoablation and RFA) with AADs in respect to freedom from symptomatic AF recurrence, neither cryoablation (OR: 0.35; 95% CrI: 0.06-1.96) nor RFA (OR: 0.34; 95% CrI: 0.07-1.27) resulted in statistically significant reductions individually compared to AADs, though pooled ablation with both technologies showed lower odds of arrhythmia recurrence (OR: 0.35; 95% CrI: 0.13-0.79). In terms of serious adverse events rates, neither cryoablation (OR: 0.77; 95% CrI: 0.44-1.39) nor RFA (OR: 1.45; 95% CrI: 0.67-3.23) were significantly different to AADs. RFA resulted in a statistically significant reduction in hospitalizations compared to AAD (OR: 0.08; 95% CrI: 0.01-0.99), whereas cryoablation did not (OR: 0.77; 95% CrI: 0.44-1.39). The surface under the cumulative ranking curve showed RFA to be the most effective treatment at reducing overall rates of recurrence, symptomatic recurrence and hospitalizations; whereas cryoablation was most likely to reduce serious adverse events. CONCLUSION: Cryoablation and RFA are both effective and safe first line therapies for AF compared to AADs, with RFA being the most effective at reducing recurrences.
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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 | 0.027 | 0.057 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.049 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".