The Importance of Hypertriglyceridemia: Risk of Atherosclerosis and Available Treatments
Bibliographic record
Abstract
Serum triglycerides are derived from both exogenous and endogenous sources. Exogenous triglycerides are obtained through the diet and circulate post prandially within large, intestinally-derived chylomicron particles, which are normally cleared within 3 to 4 hours after eating. Endogenous triglycerides are hepatically produced and circulate in smaller very low density lipoprotein (VLDL) particles, which are remodelled in plasma to form even smaller triglyceride-depleted low density lipoprotein (LDL) particles. While the atherogenic impact of LDL and its cholesterol content are well appreciated, the atherogenic role of triglyceride-rich lipoprotein particles, including VLDL and various remnant lipoprotein species, had only recently come into focus. Approximately 25% of the population has mild-to-moderate hypertriglyceridemia, characterized by triglyceride levels ranging from 2 to 9.9 mmol/L, while approximately 1 in 500 has severe hypertriglyceridemia, defined as triglyceride levels >10 mmol/L. Pathogenic DNA variants within the gene encoding the triglyceride clearing enzyme lipoprotein lipase (LPL) or one of its co-factors (APOC2, APOA5, GPIHBP1 or LMF1) can cause severe hypertriglyceridemia, that presents in childhood. Adults with milder forms of genetic predisposition in combination with secondary factors, can also express triglyceride levels this high.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".