Prophylactic ablation during cardiac surgery in patients without atrial fibrillation: a systematic review and meta-analysis of randomized trials
Bibliographic record
Abstract
OBJECTIVES: Atrial fibrillation is the most common complication of cardiac surgery and occurs frequently in patients without a history of the arrhythmia. We conducted a systematic review and meta-analysis of randomized controlled trials to assess whether prophylactic ablation during cardiac surgery in patients without a history of atrial fibrillation prevents atrial fibrillation. METHODS: We searched CENTRAL, MEDLINE and Embase from inception to August 2024. We included randomized trials of adults without a history of atrial fibrillation undergoing cardiac surgery. The intervention of interest was ablation during surgery. We pooled data using random-effects models. The primary outcome was new-onset early postoperative atrial fibrillation within 30 days following surgery. The key secondary outcome was incident clinical atrial fibrillation at follow-up (minimum 6 months). We assessed risk of bias using the Cochrane Collaboration's risk of bias tool v.2 and evidence quality using Grading of Recommendations, Assessment, Development and Evaluation (GRADE). RESULTS: We included 7 trials (n = 687). The intervention was pulmonary vein isolation in 6 trials and ganglion plexi ablation in 1. Patients who received prophylactic ablation were less likely to have early postoperative atrial fibrillation (21% vs 37%, risk ratio [RR] 0.5, 95% confidence interval 0.3-0.8, I2 = 64%) and incident clinical atrial fibrillation at longest follow-up (range 6 months-2 years; 3% vs 10%, RR 0.3, 95% confidence interval 0.2-0.7, I2 = 0%). The quality of evidence was low. CONCLUSIONS: Prophylactic ablation during cardiac surgery may prevent atrial fibrillation in patients without a history of the arrhythmia. A definitive randomized trial is needed to confirm effects and safety.
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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 | 0.018 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.038 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".