Lipoprotein(a), Oxidized Phospholipids, and Aortic Valve Microcalcification Assessed by 18F-Sodium Fluoride Positron Emission Tomography and Computed Tomography
Bibliographic record
Abstract
Background Lipoprotein(a) (Lp[a]) is the preferential lipoprotein carrier of oxidized phospholipids (OxPLs) and a well-established genetic risk factor for calcific aortic valve stenosis (CAVS). Whether Lp(a) predicts aortic valve microcalcification in individuals without CAVS is unknown. Our objective was to estimate the prevalence of elevated Lp(a) and OxPL levels in patients with CAVS and to determine if individuals with elevated Lp(a) but without CAVS have higher aortic valve microcalcification. Methods We recruited 214 patients with CAVS from Montreal and 174 patients with CAVS and 108 controls from Québec City, Canada. In a second group of individuals with high (≥75 nmol/L, n = 27) or low (<75 nmol/L, n = 28) Lp(a) levels, 18F-sodium fluoride positron emission tomography/computed tomography was performed to determine the difference in mean tissue-to-background ratio (TBR) of the aortic valve. Results Patients with CAVS had 62.0% higher Lp(a) (median = 28.7, interquartile range [8.2-116.6] vs 10.9 [3.6-28.8] nmol/L, P < 0.0001), 50% higher OxPL-apolipoprotein-B (2.2 [1.3-6.0] vs 1.1 [0.7-2.6] nmol/L, P < 0.0001), and 69.9% higher OxPL-apolipoprotein(a) (7.3 [1.8-28.4] vs 2.2 [0.8-8.4] nmol/L, P < 0.0001) levels compared with individuals without CAVS (all P < 0.0001). Individuals without CAVS but elevated Lp(a) had 40% higher mean TBR compared with individuals with low Lp(a) levels (mean TBR = 1.25 ± 0.23 vs 1.15 ± 0.11, P = 0.02). Conclusions Elevated Lp(a) and OxPL levels are associated with prevalent CAVS in patients studied in an echocardiography laboratory setting. In individuals with elevated Lp(a), evidence of aortic valve microcalcification by 18F-sodium fluoride positron emission tomography/computed tomography is present before the development of clinically manifested CAVS.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".