Bibliographic record
Abstract
An association between excessive alcohol intake and atrial fibrillation (AF) occurrence has been suspected for a long time. About 40 years ago, several case series revealed a link between excessive alcohol consumption and the occurrence of atrial arrhythmias, mainly AF. One of the investigators at that time coined the term ‘holiday heart syndrome’ for this, and this term is still in use today.1 While research and clinical experience have clearly established a link between excessive alcohol consumption or binge drinking and AF occurrence, many issues remain unclear. Firstly, the absolute risk of an AF episode after an episode of excessive alcohol intake is currently unknown. Secondly, as the initial observations mainly included patients with chronic alcohol abuse and established structural heart disease, it is unclear whether the AF episodes were due to the short-term effects of an acute alcohol intoxication or to the long-term myocardial damage induced by the chronic alcohol abuse. Interestingly, a field study during the Munich Octoberfest using smartphone-based electrocardiogram recordings and breath alcohol concentration measurements suggested a low incidence of acute AF among mainly young individuals, although the breath alcohol concentration was significantly associated with the presence of cardiac arrhythmias overall.2 These data suggest that at least some myocardial substrate damage may be needed in order that excessive alcohol intake can induce an AF episode. Finally, case reports and personal experience suggest that in some patients with paroxysmal AF, a small amount of alcohol can trigger an AF episode. If true, this would suggest that alcohol itself can induce AF episodes in susceptible individuals. However, the importance of triggers to induce AF and other cardiac arrhythmias is difficult to study, and little data are available in this area. More studies are needed to assess which patients are susceptible to the various potential triggers for AF episodes, and how much alcohol is needed to induce arrhythmias in different patients. The risk associations between regular, more moderate alcohol consumption and incident AF is much better studied. We and others have unequivocally shown that elevated alcohol consumption above two standard drinks per day is associated with an increased risk of new-onset AF during follow-up.3 Some studies suggested a threshold effect, with no risk associated with less than two drinks per day, and an increased risk associated with two drinks or more. None of the studies published so far suggests a U-shaped relationship or a protective effect of 1–2 drinks per day, as has been observed for other cardiovascular outcomes. There is no consistent evidence that different types of alcohol confer different risks of incident AF. When combining all published prospective studies into a meta-analysis, the combined data suggest a direct linear relationship between alcohol and incident AF with an ∼8% increase in risk for each drink consumed per day.4,5 Similar risk associations were observed for men and women. However, the absolute increase in risk per drink consumed seems small. Also, it is important to emphasize that definitions and multivariable adjustments for potential confounders were not harmonized in the individual studies included in these meta-analyses. Individual participant data meta-analyses are needed to better evaluate the shape of the relationship at the lower end of the alcohol consumption spectrum, given the small absolute and relative risks involved. The associations between alcohol intake and incident cardiovascular events in the general population are well studied. However, few if any studies are available on the association of alcohol intake and risk of adverse outcomes in patients with established AF. This is an important gap in knowledge, given that alcohol may interact in various ways with the oral anticoagulation prescribed to most patients with AF and additional stroke risk factors. For instance, alcohol may increase the risk of falls and interfere with medication adherence in this patient population, both risk factors for anticoagulation-related adverse outcomes. Also, many doctors recommend low or no alcohol consumption to patients with established AF. Data from large AF cohorts with long-term follow-up are needed to assess the risk of adverse cardiovascular outcomes and unplanned hospitalizations across various categories of alcohol intake. Although randomized trials of alcohol consumption would be ideal to obtain unbiased results, it is unlikely that such trials are going to be feasible in the future. In summary, we have learned much about the relationships between alcohol, incident AF and subsequent outcomes, but there are still many more uncertainties, which makes evidence-based counselling with regard to alcohol intake for our patients with or at risk of AF difficult. If you are willing to accept the potential small increase in AF risk, we should discuss over a glass of wine the studies that are needed to improve the knowledge in the field. Conflict of interest: none declared. References are available as supplementary material at European Heart Journal online.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".