Relationship Between Healthy Diet and Risk of Cardiovascular Disease Among Patients on Drug Therapies for Secondary Prevention
Bibliographic record
Abstract
BACKGROUND: Diet quality is strongly related to cardiovascular disease (CVD) incidence, but little is known about its impact on CVD events in older people at high risk of CVD and receiving effective drugs for secondary prevention. This study assessed the association between diet quality and CVD events in a large population of subjects from 40 countries with CVD or diabetes mellitus with end-organ damage receiving proven medications. METHODS AND RESULTS: Overall, 31 546 women and men 66.5±6.2 years of age enrolled in 2 randomized trials, the Ongoing Telmisartan Alone and in Combination With Ramipril Global End Point Trial (ONTARGET) and the Telmisartan Randomized Assessment Study in ACEI Intolerant Subjects With Cardiovascular Disease (TRANSCEND), were studied. We used 2 dietary indexes: the modified Alternative Healthy Eating Index and the Diet Risk Score. The association between diet quality and the primary composite outcome of CV death, myocardial infarction, stroke, or congestive heart failure was assessed with Cox proportional hazard regression with adjustment for age, sex, trial enrollment allocation, region, and other known confounders. During the 56-month follow-up, there were 5190 events. Patients in the healthier quintiles of modified Alternative Healthy Eating Index scores had a significantly lower risk of CVD (hazard ratio, 0.78; 95% confidence interval, 0.71-0.87, top versus lowest quintile of modified Alternative Healthy Eating Index). The reductions in risk for CV death, myocardial infarction, and stroke were 35%, 14%, and 19%, respectively. The protective association was consistent regardless of whether patients were receiving proven drugs. CONCLUSIONS: A higher-quality diet was associated with a lower risk of recurrent CVD events among people ≥55 years of age with CVD or diabetes mellitus. Highlighting the importance of healthy eating by health professionals would substantially reduce CVD recurrence and save lives globally.
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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 | 0.000 | 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".