Cholesterol absorption inhibitors as a therapeutic option for hypercholesterolaemia
Bibliographic record
Abstract
The development of cholesterol-lowering drugs (including a variety of statins, bile acid-binding resins and recently discovered inhibitors of cholesterol absorption) has expanded the options for cardiovascular prevention. Recent treatment guidelines emphasise that individuals at substantial risk for atherosclerotic coronary heart disease should meet defined targets for LDL cholesterol concentrations. Combination therapy with drugs that have different or complementary mechanisms of action is often needed to achieve lipid goals. Existing approaches to the treatment of hypercholesterolaemia are still ineffective in halting the progression of coronary artery disease in some patients despite combination therapies. Other patients are resistant to conventional drug treatment and remain at high risk for the development and progression of atherosclerotic cardiovascular disease and alternative approaches are needed. The discovery and development of ezetimibe (a novel, selective and potent cholesterol absorption inhibitor) has advanced the treatment of hypercholesterolaemia. New agents including the phytostanol preparation FM-VP4 and inhibitors of acyl coenzyme A:cholesterol acyltransferase, the apical Na(+)-dependent bile acid transporter and microsomal triglyceride transfer protein may also play a future role in combination therapy. This review focuses on the recent progress in the molecular mechanisms of intestinal cholesterol absorption and transport, and novel therapeutic approaches to inhibit the cholesterol absorption process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".