Abstract 12680: Alcohol Consumption and Arrhythmia Recurrence After Atrial Fibrillation Ablation: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Whether alcohol consumption increases the risk of atrial fibrillation (AF) recurrence following catheter ablation for AF remains unclear. We aimed to systematically review the medical literature to assess the impact of alcohol consumption on the recurrence of AF following AF Hypothesis: Elevated levels of alcohol consumption are associated with increased rates of AF recurrence following AF ablation. Methods: A structured electronic database search (MEDLINE, EMBASE, CONTROL; inception - December 2021) of the scientific literature was performed for studies reporting rates of AF recurrence following catheter ablation stratified by patients’ level of alcohol consumption. Alcohol use was dichotomized into categories which represented moderate-heavy alcohol use or those that represented abstention or rare alcohol use. Study specific odds rations (ORs) were meta-analyzed using a random effects model. Risk of bias was evaluated using the ROBINS-I tool. Results: A total of nine observational studies were identified, which included 5436 patients undergoing catheter ablation. There was substantial variation in the categories used to stratify alcohol consumption. Compared to patients consuming little to no alcohol, patients consuming moderate to high amounts of alcohol had a greater odds of AF recurrence (OR 1.45 [95% CI: 1.06-1.99, p = 0.02]; I 2 = 79%). This relationship remained significant after exclusion of studies with < 100 participants (OR 1.40, 95% CI 1.03-1.90, p = 0.03) and when abstract-only publications were excluded (OR 1.84, 95% CI 1.21-2.80, p = 0.004). All included studies were found to be at serious risk of bias, mainly due to confounding. There was no evidence of publication bias. Conclusions: Increased alcohol consumption is associated with increased rates of AF recurrence following catheter ablation for AF. Reduction of alcohol consumption post ablation may reduce AF recurrence.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.027 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".