Elevated Lp(a) Levels Correlate with Severe and Multiple Coronary Artery Stenotic Lesions
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Bibliographic record
Abstract
Backgrounds and Aims: The role of Lipoprotein(a) (Lp(a)) in increasing the risk of cardiovascular diseases is reported in several populations. The aim of this study is to investigate the correlation of high Lp(a) levels with the degree of coronary artery stenosis. Methods: Two hundred and sixty-eight patients were enrolled for this study. Patients who underwent coronary artery angiography and who had Lp(a) measurements available were included in this study. Binomial logistic regressions were applied to investigate the association between Lp(a) and stenosis in the four major coronary arteries. The effect of LDL and HDL Cholesterol on modulating the association of Lp(a) with coronary artery disease (CAD) was also evaluated. Multinomial regression analysis was applied to assess the association of Lp(a) with the different degrees of stenosis in the four major coronary arteries. Results: Our analyses showed that Lp(a) is a risk factor for CAD and this risk is significantly apparent in patients with HDL-cholesterol ≥ 35 mg/dL and in non-obese patients. A large proportion of the study patients with elevated Lp(a) levels had CAD even when exhibiting high HDL serum levels. Increased HDL with low Lp(a) serum levels were the least correlated with stenosis. A significantly higher levels of Lp(a) were found in patients with > 50% stenosis in at least two major coronary vessels arguing for pronounced and multiple stenotic lesions. Finally, the derived variant (rs1084651) of the LPA gene was significantly associated with CAD. Conclusion: Our study highlights the importance of Lp(a) levels as an independent biological marker of severe and multiple coronary artery stenosis. Keywords: lipoprotein(a), cardiovascular diseases, stenosis
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it