The cardioprotective association of average alcohol consumption and ischaemic heart disease: a systematic review and meta‐analysis
Bibliographic record
Abstract
AIMS: Most, but not all, epidemiological studies suggest a cardioprotective association for low to moderate average alcohol consumption. The objective was to quantify the dose-response relationship between average alcohol consumption and ischaemic heart disease (IHD) stratified by sex and IHD end-point (mortality versus morbidity). METHODS: A systematic search of published studies using electronic databases (1980-2010) identified 44 observational studies (case-control or cohort) reporting a relative risk measure for average alcohol intake in relation to IHD risk. Generalized least-squares trend models were used to derive the best-fitting dose-response curves in stratified continuous meta-analyses. Categorical meta-analyses were used to verify uncertainty for low to moderate levels of consumption in comparison to long-term abstainers. RESULTS: The analyses used 38,627 IHD events (mortality or morbidity) among 957,684 participants. Differential risk curves were found by sex and end-point. Although some form of a cardioprotective association was confirmed in all strata, substantial heterogeneity across studies remained unexplained and confidence intervals were relatively wide, in particular for average consumption of one to two drinks/day. CONCLUSIONS: A cardioprotective association between alcohol use and ischaemic heart disease cannot be assumed for all drinkers, even at low levels of intake. More evidence on the overall benefit-risk ratio of average alcohol consumption in relation to ischaemic heart disease and other diseases is needed in order to inform the general public or physicians about safe or low-risk drinking levels.
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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".