Abstract 13938: Relationships Between ‘Mediterranean’ and ‘Western’ Dietary Patterns and Biomarkers Associated With Increased Cardiovascular Risk in Patients With Stable Coronary Heart Disease in the Global STABILITY Trial
Bibliographic record
Abstract
Introduction: In the STabilization of Atherosclerotic plaque By Initiation of darapLadIb TherapY (STABILITY) trial greater adherence to a Mediterranean dietary pattern (MD) was associated with major cardiovascular (CV) events (MACE) but there was no association between a ‘Western Diet Score’ (WDS) and MACE. The lowest mortality and MACE was in patients with a MD score (MDS) ≥15. Hypothesis: Low adherence to a MD may be associated with higher plasma levels of biomarkers known to predict adverse CV events. Methods: At baseline, 15,482 (97.8%) trial participants completed a lifestyle questionnaire. MDS was calculated for increasing consumption of whole grains, fruits, vegetables, legumes, fish, and alcohol, and for less meat. WDS was calculated for increasing consumption of refined grains, sweets and desserts, sugared drinks, and deep-fried foods. In 15,287 of these participants hs C-reactive protein (hs-CRP), hs troponin T (hs-TnT), N-terminal B type natriuretic peptide (NT-proBNP), interleukin-6 (IL-6), cystatin-C, growth differentiation factor-15 (GDF-15) and lipoprotein-associated phospho-lipase A 2 (Lp-PLA 2 ) were measured from stored plasma samples taken at baseline. The ratios of the geometric mean level of each biomarker by diet group are reported adjusted for age, gender, darapladib treatment, geographic region, markers of disease severity, and CV risk factors including body mass index, diabetes, hypertension, and low and high-density lipoprotein cholesterol. Results: Lower MDS (13-14/ ≥15 and ≤12/ ≥15 respectively) was associated with higher hs-CRP 1.12 (95%CI 1.05; 1.19), 1.18 (1.11; 1.25), cystatin-C 1.01 (1.00; 1.02), 1.03 (1.01; 1.04), GDF-15 1.05 (1.02; 1.07), 1.06 (1.04; 1.09) and LpPLA2 1.02 (1.01; 1.04), 1.04 (1.02; 1.06) after adjusting for all co-variables (p<0.01 for all). IL-6, hs-TnT and NT-proBNP were not independently associated with MDS. WDS was not independently associated with higher plasma levels of any biomarkers. Conclusions: MD may be associated with lower CV risk in part by effects on inflammatory activity and pathways of cellular function independent of plasma lipids. Greater consumption of food in the WDS was not associated with adverse CV events or with biomarkers known to be associated with risk.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".