Adherence to the Mediterranean Diet in Preventing Major Cardiovascular Events in Patients with Ischemic Heart Disease: The EVA Study
Bibliographic record
Abstract
Background: Adherence to healthy dietary patterns, such as the Mediterranean diet (Med-diet), is recommended for the maintenance of cardiovascular health. The determinants for adherence to Med-diet and its importance in secondary cardiovascular disease prevention are still unclear. The aim of the study was to evaluate the influence of sex- and psycho-socio-cultural (i.e., gender-related) factors on Med-diet adherence and its role in preventing major cardiovascular events (MACEs) in patients with ischemic heart disease (IHD). Methods: Med-diet adherence was evaluated among 503 consecutive adults with IHD. MACEs were collected during a long-term follow-up. Results: Male Bem Sex-Role Inventory score (i.e., male personality traits) and physical functional capacity were associated with higher adherence, while cohabitation with a smoker and physical inactivity with poorer adherence. During a median follow-up of 22 months, 48 participants experienced MACEs (17.5%, 8.1%, and 3.9% of patients with low, medium, and high adherence, respectively; p = 0.016). At multivariate Cox--regression analysis, a greater adherence remained inversely associated with MACEs (HR: 0.49; 95% CI: 0.29–0.82; p = 0.006) after adjusting for confounding factors. Conclusion: The study suggests that gender-related factors have a role in maintaining a healthy dietary pattern. Improving Med-diet adherence may lower the risk of recurring cardiovascular events.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".