Comparison of the efficacy of fibrates on hypertriglyceridemic phenotypes with different genetic and clinical characteristics
Bibliographic record
Abstract
UNLABELLED: Hypertriglyceridemia is a frequent and heterogeneous clinical trait, which modulates the risk of disease. Fibrates constitute an effective class of triglyceride-lowering agents. OBJECTIVE: To evaluate the effect of fibrates on fasting plasma triglycerides and other lipids levels in hypertriglyceridemia phenotypes with different genetic and clinical characteristics. METHODS: This study included 146 fasting adults: 15 with lactescent plasma and severe hypertriglyceridemia (triglyceride ≥ 10 mmol/l) and 131 with clear plasma and moderate hypertriglyceridemia (2 ≤ triglycerides <10 mmol/l). Expost comparisons of the effect of fibrates on fasting triglycerides and other lipids were made using Student's paired two-tailed t-test. RESULTS: Response to these fibrates differed significantly across the studied hypertriglyceridemia subtypes: patients with severe hypertriglyceridemia because of lipoprotein lipase deficiency and those with moderate hypertriglyceridemia because of glycerol kinase deficiency did not respond at all, whereas patients with palmar xanthomas and severe or moderate hypertriglyceridemia because of apolipoprotein (apo) E resistance (type-III dysbetalipoproteinemia, most often associated with the apo E2 allele) responded significantly better (P<0.001) than all other subtypes on several lipid fractions. CONCLUSION: These results indicate that genetic factors known to contribute to the etiology and clinical expression of hypertriglyceridemia subtypes also modulate the response to triglyceride-lowering drugs.
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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 | 0.000 | 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) | 0.001 | 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 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".