Non-high-density lipoprotein cholesterol versus low-density lipoprotein cholesterol in clinical practice: ANMCO position paper
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bloodstream cholesterol is a central contributor to atherosclerotic cardiovascular diseases. For several decades, low-density lipoprotein cholesterol (LDL-C) has been the main biomarker for the prediction of cardiovascular events and therapeutic target of lipid-lowering treatments. More recently, several findings have supported the greater reliability of non-high-density lipoprotein cholesterol (non-HDL-C) as a predictive factor and possible therapeutic target in refining antiatherogenic treatments, especially among patients with lower LDL-C and higher triglyceride values. This article discusses the limits of current standard methods for assessing LDL-C levels and emphasizes the persistent residual cardiovascular risk in patients treated with lipid-lowering agents on the basis of recommended LDL-C targets. It highlights that patients with controlled LDL-C and non-targeted non-HDL-C have a higher cardiovascular risk. The article focuses on the role of non-HDL-C as a better predictor of atherosclerotic disease as compared with LDL-C and as a therapeutic target. Finally, this article includes an executive summary aimed at refining preventive approaches in atherosclerotic cardiovascular disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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