Bibliographic record
Abstract
PURPOSE OF REVIEW: We provide an overview of recent advances in the therapy of hypertriglyceridemia, focusing on several new therapies with potential for treating of familial chylomicronemia, other forms of hypertriglyceridemia, and for triglyceride-lowering in patients with other lipid disorders. RECENT FINDINGS: Newer triglyceride-lowering modalities under evaluation include gene therapy for lipoprotein lipase deficiency (alipogene tiparvovec), and antisense oligonucleotides against mRNA for apolipoproteins B (mipomersen) and C3 (volanesorsen, ISIS 304801). Other potential therapies include small molecule inhibitors of microsomal triglyceride transfer protein (lomitapide) and diacylglycerol acyltransferase-1 (pradigastat), and a monoclonal antibody against angiopoietin-like protein 3 (REGN1500). There is also renewed interest in omega-3 fatty acids, and in developing potent and selective agonists of peroxisome proliferator-activated receptors. SUMMARY: Several promising triglyceride-lowering therapies are at various stages of development; a few are even available in some markets. Although existing data suggest good biochemical efficacy, data on long-term clinical outcomes are still limited. For some therapies, cost will be an important consideration, and use will likely be restricted to orphan indications, for example very severe cases of hypertriglyceridemia as seen in familial chylomicronemia syndrome, although some therapies could theoretically be more broadly used one day for cardiovascular disease prevention.
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.
How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".