Dietary patterns and the risk of major adverse cardiovascular events in a global study of high-risk patients with stable coronary heart disease
Bibliographic record
Abstract
OBJECTIVES: To determine whether dietary pattern assessed by a simple self-administered food frequency questionnaire is associated with major adverse cardiovascular events (MACE) in high-risk patients with stable coronary artery disease. BACKGROUND: A Mediterranean dietary pattern has been associated with lower cardiovascular (CV) mortality. It is less certain whether foods common in western diets are associated with CV risk. METHODS: At baseline, 15 482 (97.8%) patients (mean age 67 ± 9 years) with stable coronary heart disease from 39 countries who participated in the Stabilisation of atherosclerotic plaque by initiation of darapladib therapy (STABILITY) trial completed a life style questionnaire which included questions on common foods. A Mediterranean diet score (MDS) was calculated for increasing consumption of whole grains, fruits, vegetables, legumes, fish, and alcohol, and for less meat, and a 'Western diet score' (WDS) for increasing consumption of refined grains, sweets and deserts, sugared drinks, and deep fried foods. A multi-variable Cox proportional hazards models assessed associations between MDS or WDS and MACE, defined as CV death, non-fatal myocardial infarction, or non-fatal stroke. RESULTS: After a median follow-up of 3.7 years MACE occurred in 7.3% of 2885 subjects with an MDS ≥15, 10.5% of 4018 subjects with an MDS of 13-14, and 10.8% of 8579 subjects with an MDS ≤12. A one unit increase in MDS >12 was associated with lower MACE after adjusting for all covariates (+1 category HR 0.95, 95% CI 0.91, 0.98, P = 0.002). There was no association between WDS (adjusted model +1 category HR 0.99, 95% CI 0.97, 1.01) and MACE. CONCLUSION: Greater consumption of healthy foods may be more important for secondary prevention of coronary artery disease than avoidance of less healthy foods typical of Western diets.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 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 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".