Effect of treatment with 5‐lipoxygenase inhibitor <scp>VIA</scp>‐2291 (atreleuton) on coronary plaque progression: a serial <scp>CT</scp> angiography study
Bibliographic record
Abstract
Background Inflammation has a key role in the process of atherosclerosis. Production of leukotrienes by 5‐lipoxygenase has been linked to atherosclerotic plaques and cardiovascular events. Hypothesis In this study, a selective 5‐LO inhibitor will slow plaque progression using serial cardiac computed tomographic angiography (CCTA). Methods Patients with recent acute coronary syndrome (ACS) were prospectively assigned to one of 3 VIA‐2291 doses (25 mg, 50 mg, 100 mg) or placebo by oral administration. All groups underwent CCTA at baseline and at 6 months’ follow‐up. Plaque types such as low‐attenuation plaque (LAP), fibro‐fatty tissue (FF), fibro‐calcified plaque (FC), and dense calcium plaque (DC) were measured based upon predefined density threshold, and changes from baseline CCTA were analyzed. Results The final analysis included 54 patients (age, 56 ± 9 years; 85.1% male) with CCTA at baseline and 24 weeks. Evaluating on treatment VIA‐2291 (all 3 doses, n = 37) demonstrated significant reductions in plaque progression compared with placebo (n = 17). VIA‐2291 significantly reduced LAP (5.9 ± 20.7 mm3 vs −9.7 ± 33.3 mm3), FF (11.1 mm3 ± 13.3 mm3 vs −0.9 ± 2.7 mm3), and FC (−0.1 ± 6.22 mm3 vs −14.3 ± 6.2 mm3; all P < 0.05) and retarded the progression of DC (3.9 ± 3.2 mm3 vs 0.2 ± 0.4 mm3) compared with placebo. Conclusions VIA‐2291 resulted in slowed plaque progression compared with placebo across different plaque subtypes in patients with recent ACS ( http://ClinicalTrials.gov NCT00358826).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".