apoB/apoA‐I Ratio and Lp(a) Associations With Aortic Valve Stenosis Incidence: Insights From the EPIC‐Norfolk Prospective Population Study
Bibliographic record
Abstract
Background Apolipoprotein B/apolipoprotein A-I (apoB/apoA-I) ratio and lipoprotein(a) (Lp[a]) are associated with aortic valve stenosis (AVS) disease progression. Clinical characteristics such as age, sex, and presence of concomitant coronary artery disease may strongly modify these associations; however, these effects have not been well defined in longitudinal studies. We set out to assess these associations between apoB/apoA-I ratio, Lp(a), and AVS incidence in a large population study. Methods and Results We analyzed data from 17 745 participants (mean age, 59.2±9.1 years; men, 44.9%) in the EPIC-Norfolk (European Prospective Investigation Into Cancer in Norfolk Prospective Population Study) population study in whom apoB/apoA-I and Lp(a) levels were measured. Participants were identified as having incident AVS if they were hospitalized or died with AVS as an underlying cause. After a median follow-up of 19.8 years (17.9-21.0 years) there were 403 (2.2%) incident cases of AVS. The hazard ratio for AVS risk was 1.30 (95% CI, 1.19-1.41; P<0.001) per SD increase in apoB/apoA-I. Adjusting for age, sex, and coronary artery disease, there was no significant association between apoB/apoA-I and AVS incidence (hazard ratio, 1.06; 95% CI, 0.97-1.17 [P=0.215]). Elevated Lp(a) (>50 mg/dL) remained an independent risk factor for AVS after adjustment for age, sex, low-density lipoprotein cholesterol, and concomitant coronary artery disease (hazard ratio, 1.70; 95% CI, 1.33-2.19 [P<0.001]). Conclusions In this population study, apoB/apoA-I ratio was associated with risk of AVS incidence, especially in younger and female participants and those without concomitant coronary artery disease. Lp(a) was an independent risk factor for AVS incidence. Interventional trials are needed to investigate whether modulating apoB/apoA-I or lowering Lp(a) can prevent or slow down AVS.
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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 | 0.003 |
| 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 | 0.001 | 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".