Abstract P158: Systematic Review and Meta-analysis of Acute Effects of Alcohol Consumption on Risk of Cardiovascular Events
Bibliographic record
Abstract
Introduction: Although considerable research describes the cardiovascular effects of habitual moderate and heavy alcohol consumption, the acute risks following alcohol intake have not been well characterized. Based on its physiological effects, alcohol may have markedly different effects on acute and long-term risk. We assessed the hypothesis that moderate alcohol consumption is associated with an immediately higher risk of cardiovascular events that becomes protective after 24 hours, whereas heavy alcohol drinking is associated with higher cardiovascular risk both immediately and in the following days. Methods: We searched CINAHL, Embase, PubMed and PsycINFO from inception to March 12 2015, supplemented with manual screening for observational studies assessing the association between alcohol intake and cardiovascular events in the following hours and days. We calculated pooled relative risks (RRs) and 95% confidence intervals (CIs) for the association between alcohol intake and myocardial infarction (MI), ischemic stroke (IS) and hemorrhagic stroke (HS) using DerSimonian and Laird random-effects models to model any alcohol intake or dose-response relationships of alcohol intake and cardiovascular events. Results: Among 1056 citations and 37 full-text articles reviewed, 23 studies (29457 participants) were included. Moderate alcohol consumption was associated with an acutely higher cardiovascular risk that was attenuated after 24 hours and even protective for MI and HS (≈2-4 drinks: RR=30% lower risk), and protective against IS within one week (≈6 drinks: RR=19% lower risk). In contrast, heavy alcohol drinking was associated with higher cardiovascular risk in the following day (≈6-9 drinks: RR=1.3-2.3) and week (≈19-30 drinks: RR=2.25-6.2). Conclusions: In conclusion, there appears to be a consistent finding of an acutely higher cardiovascular risk following any alcohol consumption but by 24 hours, only heavy alcohol intake conferred continued 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 | 0.011 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.023 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".