Carotid intima-medial thickness in patients with severe hypertriglyceridemia
Bibliographic record
Abstract
Background and aims: Severe hypertriglyceridemia (HTG), defined as plasma triglyceride (TG) concentration > 10 mmol/L, is relatively uncommon, and its implications for atherosclerotic cardiovascular disease (ASCVD) risk remain somewhat unclear. We evaluated the association between severe HTG and carotid intima-media thickness (IMT), a marker for ASCVD. Methods: We studied three clinical cohorts: 88 patients with severe HTG (mean TG level 20.6 mmol/L), 271 patients with familial hypercholesterolemia (FH) as a contrast group, and 70 normolipidemic controls. Carotid IMT was measured using standardized ultrasound imaging. Statistical analysis was conducted using one-way analysis of variance (ANOVA) to compare mean IMT values, analysis of covariance (ANCOVA) to adjust for confounding variables, specifically age and sex, as well as Spearman pairwise correlation analysis between variables. Results: Unadjusted mean carotid IMT was greater in severe HTG and FH groups compared to controls, however, this was no longer significant for severe HTG after adjustment for age and sex. In contrast, adjusted carotid IMT remained significantly different between the FH and control groups. Conclusions: Our findings suggest that extreme TG elevations in severe HTG patients are not significantly associated with carotid IMT, in contrast to the increased IMT seen in FH patients. These findings add perspective to the complex relationship between severe HTG and ASCVD risk.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".