Abstract P042: Coffee Intake and the Risk of Subclinical Myocardial Damage, Cardiovascular Events and All-cause Mortality
Bibliographic record
Abstract
Introduction: Whether coffee intake is protective against cardiovascular disease (CVD) risk and mortality is controversial and putative mechanisms are incompletely understood, but prior studies may be confounded by a “healthy user” effect. Hypothesis: Habitual coffee consumption would not be associated with subclinical myocardial damage assessed using high-sensitivity cardiac troponin T (hs-cTnT), CVD events (coronary heart disease, heart failure or stroke) and all-cause mortality, after adjustment for rigorously measured confounders. Methods: We evaluated 11,281 ARIC participants free of CVD at baseline (Visit 2, 1990-1992). Coffee consumption was assessed via a modified food frequency questionnaire at Visit 2 and categorized according to number of cups/day. We used logistic regression models adjusted for demographic characteristics, smoking status and traditional CVD risk factors to test the cross-sectional associations with hs-cTnT, and adjusted Cox models for incident CVD events and mortality. Results: Mean age of participants was 57 years, 58% were women and 24% black. In cross-sectional analyses, compared to individuals reporting “almost never” having consumed coffee, no significant association was found between higher levels of coffee consumption and elevated hs-cTnT (OR for ≥6 cups/day vs. almost never 0.69; 95% CI 0.39, 1.21; Table). In prospective analyses, the association between coffee and incident CVD was not significant (HR for ≥6 cups/day vs. almost never: 1.15; 95% CI 0.99, 1.34; Table). Compared to almost never consuming coffee, 2-3 cups/day was associated with reduced risk of all-cause mortality and ≥6 cups/day with elevated risk of all-cause mortality (Table). Conclusion: In this bi-racial cohort of middle-aged adults, coffee intake was not associated with subclinical myocardial damage or CVD. However, moderate coffee consumption may be associated with a modestly reduced risk of all-cause mortality and very high coffee consumption with a mild increase in all-cause mortality.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".