Lipoprotein(a) Levels, Genotype, and Incident Aortic Valve Stenosis
Bibliographic record
Abstract
BACKGROUND: Although a previous study has suggested that a genetic variant in the LPA region was associated with the presence of aortic valve stenosis (AVS), no prospective study has suggested a role for lipoprotein(a) levels in the pathophysiology of AVS. Our objective was to determine whether lipoprotein(a) levels and a common genetic variant that is strongly associated with lipoprotein(a) levels are associated with an increased risk of developing AVS. METHODS AND RESULTS: Serum lipoprotein(a) levels were measured in 17 553 participants of the European Prospective Investigation into Cancer (EPIC)-Norfolk study. Among these study participants, 118 developed AVS during a mean follow-up of 11.7 years. The rs10455872 genetic variant in LPA was genotyped in 14 735 study participants, who simultaneously had lipoprotein(a) level measurements, and in a replication study of 379 patients with echocardiography-confirmed AVS and 404 controls. In EPIC-Norfolk, compared with participants in the bottom lipoprotein(a) tertile, those in the top lipoprotein(a) tertile had a higher risk of AVS (hazard ratio, 1.57; 95% confidence interval, 1.02-2.42) after adjusting for age, sex, and smoking. Compared with rs10455872 AA homozygotes, carriers of 1 or 2 G alleles were at increased risk of AVS (hazard ratio, 1.78; 95% confidence interval, 1.11-2.87, versus hazard ratio, 4.83; 95% confidence interval, 1.77-13.20, respectively). In the replication study, the genetic variant rs10455872 also showed a positive association with AVS (odds ratio, 1.57; 95% confidence interval, 1.10-2.26). CONCLUSIONS: Patients with high lipoprotein(a) levels are at increased risk for AVS. The rs10455872 variant, which is associated with higher lipoprotein(a) levels, is also associated with increased risk of AVS, suggesting that this association may be causal.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".