Mechanisms and Therapeutic Opportunities in Atrial Fibrillation in Relationship to Alcohol Use and Abuse
Bibliographic record
Abstract
Excessive drinking has detrimental effects on the cardiovascular system. Atrial fibrillation (AF) after alcohol binge drinking, also named "holiday heart syndrome," is well established. However, chronic lower levels of alcohol intake also may increase AF risk. In this review, we aim to provide a comprehensive overview of the epidemiology and pathophysiology by which alcohol may be responsible for AF and discuss whether alcohol abstinence is required for optimal rhythm control as well as to maintain sinus rhythm in patients with AF. The pathophysiologic mechanisms responsible for the relationship between alcohol consumption and AF may include both direct and chronic effects increasing AF burden. Acute effects may include arrhythmogenic changes (such as shortening in atrial refractoriness, slowing in conduction velocity, and increased atrial ectopy) and an autonomic imbalance. Chronic changes contributing to the development of an arrhythmogenic substrate involve atrial structural and functional remodelling processes due to atrial dilation, elevated pressures, and fibrosis formation. In addition, alcohol consumption contributes to developing concomitant AF risk factors such as obesity, sleep-disordered breathing, and hypertension. Alcohol abstinence is associated with a reduction in AF recurrence and overall burden and moreover improves AF risk factor development such as obesity, hypertension, sleep apnea, and AF-related consequences such as stroke. In conclusion, alcohol consumption is associated with atrial arrhythmia and a wide range of cardiovascular comorbidities. Although further evidence is needed, current knowledge indicates that there might not be a safe level of alcohol consumption that does not increase AF risk.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".