Catheter ablation as first-line treatment for paroxysmal atrial fibrillation: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy and safety of catheter ablation (CA) compared with antiarrhythmic drugs (AADs) as first-line treatment for symptomatic paroxysmal atrial fibrillation (AF). METHODS: Systematic review and meta-analysis of randomised controlled trials identified using MEDLINE, Cochrane Library and Embase published between 01/01/2000 and 19/03/2021. The primary efficacy endpoint was the first documented recurrence of atrial arrhythmias following the blanking period. The primary safety endpoint was a composite of all serious adverse events (SAEs). RESULTS: From 441 records, 6 studies met the inclusion criteria. 609 patients received CA, while 603 received AAD therapy. 212/609 patients in the CA group had a recurrence of atrial arrhythmias as compared with 318/603 in the AADs group resulting in a 36% relative risk reduction (risk ratio: 0.64, 95% CI 0.51 to 0.80, p<0.01). The risk of all SAEs was not statistically different between CA and AAD (0.87, 0.58 to 1.30, p=0.49); 107/609 SAE in the CA group vs 126/603 in the AAD group. Both recurrence of symptomatic atrial arrhythmias (109/505 vs 186/504) and healthcare utilisation (126/397 vs 185/394) were significantly lower in the CA group (0.53, 0.35 to 0.79 and 0.65, 0.48 to 0.89, respectively). There was a 79% reduction in the crossover rate during follow-up among patients randomised to CA compared with AAD (0.21, 0.13 to 0.32, p<0.01). CONCLUSIONS: First-line treatment with CA is superior to AAD therapy in patients with symptomatic paroxysmal AF, as it significantly reduces the recurrence of any atrial arrhythmias and symptomatic atrial arrhythmias, and healthcare resource utilisation with comparable safety profile.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.030 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".