An overview of persistent chylomicronemia: much more than meets the eye
Bibliographic record
Abstract
PURPOSE OF REVIEW: The aim of this review is to provide an overview of severe hypertriglyceridemia presenting in the form of chylomicronemia that persists despite treatment of secondary causes and the use of conventional lipid-lowering treatment. RECENT FINDINGS: Persistent chylomicronemia is a rare syndromic disorder that affects carriers of bi-allelic combinations of pathogenic gene variants impairing lipoprotein lipase (LPL) activity, as well as a significant number of individuals who do not meet this genetic criterion. It is associated with a high risk of acute pancreatitis and other morbidities. Effective innovative treatments for severe hypertriglyceridemia are being developed and are becoming available. Patients with persistent chylomicronemia of any cause respond equally to next-generation therapies with LPL-independent mechanisms of action and do not generally respond to conventional LPL-dependent treatments. SUMMARY: Not all individuals with persistent chylomicronemia carry a proven pathogenic combination of gene variants that impair LPL activity. Documenting the clinical characteristics of people with persistent chylomicronemia and their response to emerging therapies is essential to correctly establish their risk trajectory and ensure equitable access to personalized treatment.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".