Health-Related Quality of Life in Patients With Atrial Fibrillation Treated With Catheter Ablation or Antiarrhythmic Drug Therapy: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background Catheter ablation (CA) is performed in patients with atrial fibrillation (AF) to reduce symptoms and improve health-related quality of life (HRQL). Methods This systematic review and meta-analysis of randomized controlled trials (RCTs) evaluated CA of any energy modality compared with antiarrhythmic drugs (AADs) using inverse-variance random-effects models. We searched for RCTs reporting HRQL and AF-related symptoms at 3, 6, 12, 24, 48, and 60 months after treatment as well as the number of repeat ablations. Results Of 15,878 records, we included 13 RCTs of CA vs AADs for the analyses of HRQL, 7 RCTs for the analyses of AF-related symptoms, and 13 RCTs for the number of repeat ablations. For the HRQL analyses at 3 months, there were significant increases in both the Physical Component Summary score (3 months' standardized mean difference = 0.58 [0.39-0.78]; P < 0.00001, I 2 = 6%, 3 trials, n = 443) and the Mental Component Summary score (3 months' standardized mean difference = 0.57 [0.37-0.77]; P < 0.00001, I 2 = 0%, 3 trials, n = 443), favouring CA over AADs. These differences were sustained at 12 months but not >24 months after randomization. Similar results were seen for AF-related symptoms. The number of repeat ablations and success rates after procedure varied considerably across trials. Conclusions Evidence from few trials suggests that CA improves physical and mental health and AF-related symptoms in the short term, but these benefits decrease with time. More trials, reporting both HRQL and AF-related symptoms, at consistent time points are needed to assess the effectiveness of CA for the treatment of AF.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.006 | 0.007 |
| 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".