Ischemic Heart Disease Mortality and Morbidity Rates in Former Drinkers: A Meta-Analysis
Bibliographic record
Abstract
Current abstainers from alcohol have been identified as an inadequate reference group in epidemiologic studies of the effects of alcohol, because inclusion of former drinkers might lead to overestimation of the protective effects and underestimation of the detrimental effects of drinking alcohol. The authors' objective in the current study was to quantify this association for ischemic heart disease (IHD). Electronic databases were systematically searched for relevant case-control or cohort studies published from 1980 to 2010. Thirty-eight articles fulfilled the inclusion criteria, contributing a total of 5,613 IHD events and 12,097 controls among case-control studies and 1,387 events with combined endpoints and 7,183 events stratified by endpoint among 232,621 persons at risk among cohort studies. Pooled estimates for the subset stratified by sex and endpoint showed a significantly increased risk among former drinkers compared with long-term abstainers for IHD mortality ( among men; relative risk = 1.25, 95% confidence interval: 1.15, 1.36; among women relative risk = 1.54, 95% confidence interval: 1.17, 2.03). For IHD morbidity, the estimates for both sexes were close to unity and not statistically significant. Results were robust in several sensitivity analyses. In future studies, researchers should separate former drinkers from the reference category to obtain unbiased effect estimates. Implications for the overall beneficial and detrimental effects of alcohol consumption on IHD are discussed below.
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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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.053 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".