Chronic heavy drinking and ischaemic heart disease: a systematic review and meta-analysis
Why this work is in the frame
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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.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it