Therapeutic Targets to Raise HDL in Patients at Risk or with Coronary Artery Disease
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
The plasma levels of high-density lipoprotein (HDL) cholesterol are inversely related to cardiovascular risk. Traditional HDL-raising therapies, like fibrates, PPAR-γ agonists, and nicacin, among others, are associated with undesirable side effects, limited efficacy, or have not yet been shown to improve morbidity and mortality on top of statins in clinical outcome trials. A novel pharmacological target for raising circulating HDL-C levels is the cholesterol ester transfer protein (CETP), an enzyme that facilitates the transport of cholesteryl esters and triglycerides between the lipoproteins. Four pharmacological small-molecule inhibitors of CETP, i.e. torcetrapib (Pfizer), dalcetrapib (JTT-705; Roche), anacetrapib (Merck), and evacetrapib (Eli Lilly) have been developed. Notwithstanding a marked increase in HDL, torcetrapib was associated with an increase in all-cause mortality in the ILLUMINATE trial and raised safety concerns related to the off-target effects of CETP inhibition. Most recently, development of dalcetrapib was abruptly stopped due to a lack of clinically meaningful efficacy. Thus, it will be of utmost importance to demonstrate that the remaining CETP inhibitors in development not only increase HDL-C levels in plasma, but also improve HDL-function in patients with coronary disease or an acute coronary syndrome.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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