Lipoprotein(a) has no major impact on calcification activity in patients with mild to moderate aortic valve stenosis
Bibliographic record
Abstract
Objective To assess whether patients with aortic valve stenosis (AS) with elevated lipoprotein(a) (Lp(a)) are characterised by increased valvular calcification activity compared with those with low Lp(a). Methods We performed 18 F-sodium fluoride ( 18 F-NaF) positron emission tomography/CT in patients with mild to moderate AS (peak aortic jet velocity between 2 and 4 m/s) and high versus low Lp(a) (>50 mg/dL vs <50 mg/dL, respectively). Subjects were matched according to age, gender, peak aortic jet velocity and valve morphology. We used a target to background ratio with the most diseased segment approach to compare 18 F-NaF uptake. Results 52 individuals (26 matched pairs) were included in the analysis. The mean age was 66.4±5.5 years, 44 (84.6%) were men, and the mean aortic valve velocity was 2.80±0.49 m/s. The median Lp(a) was 79 (64–117) mg/dL and 7 (5–11) mg/dL in the high and low Lp(a) groups, respectively. Systolic blood pressure and low-density-lipoprotein cholesterol (corrected for Lp(a)) were significantly higher in the low Lp(a) group (141±12 mm Hg vs 128±12 mm Hg, 2.5±1.1 mmol/L vs 1.9±0.8 mmol/L). We found no difference in valvular 18 F-NaF uptake between the high and low Lp(a) groups (3.02±1.26 vs 3.05±0.96, p=0.902). Linear regression analysis showed valvular calcium score to be the only significant determinant of valvular 18 F-NaF uptake (β=0.63; 95% CI 0.38 to 0.88 per 1000 Agatston unit increase, p<0.001). Lp(a) was not associated with 18 F-NaF uptake (β=0.17; 95% CI −0.44 to 0.88, p=0.305 for the high Lp(a) group). Conclusion Among patients with mild to moderate AS, calcification activity is predominantly determined by established calcium burden. The results do not support our hypothesis that Lp(a) is associated with valvular 18 F-NaF uptake.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".