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.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".