Chronic heavy drinking and ischaemic heart disease: a systematic review and meta-analysis
Bibliographic record
Abstract
Previous meta-analyses have reported either a protective, neutral or detrimental association from chronic heavy drinking in relation to ischaemic heart disease (IHD). We investigated the potential for systematic error because of study design. Using MOOSE guidelines, studies were identified through MEDLINE, EMBASE and Web of Science up to end of March, 2014. Epidemiological studies reporting on chronic heavy drinking and IHD risk in population studies and samples of people with alcohol use disorder (AUD) were included. Random-effects meta-analysis was used to pool eligible studies. The I(2) statistic was used to assess heterogeneity across studies. In total, 34 observational studies with 110 570 chronic heavy drinkers and 3086 IHD events were identified. In population studies among men, the pooled risk for IHD incidence (fatal+non-fatal events) among chronic heavy drinkers (on average ≥60 g pure alcohol/day) in comparison to lifetime abstainers (n=11 studies) was relative risk (RR)=1.04 (95% CI 0.83 to 1.31, I(2)=54%). Few studies were available for women. In patients with AUD, the risk of IHD mortality in comparison to the general population was elevated with a RR=1.62 (95% CI 1.34 to 1.95, I(2)=81%) in men and RR=2.09 (95% CI 1.28 to 3.41, I(2)=67%) in women. There was a general lack of adjustment other than sex and age in studies among patients with AUD. There is no systematic evidence for a protective association from any type of chronic heavy drinking on IHD risk. Patients with AUD were at higher risk for IHD mortality, but better quality evidence is needed with regard to potential confounding.
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 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.043 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".