Anti-inflammatory drugs and atherosclerosis
Bibliographic record
Abstract
PURPOSE OF REVIEW: Inflammation contributes to the formation and progression of atherosclerosis and the therapeutic potential of some anti-inflammatory drugs has been evaluated for possible antiatherosclerotic effects. This review will briefly describe the mechanisms underlying the inflammation-atherosclerosis connection, the effect of various anti-inflammatory therapies on atherosclerotic disease and a sampling of the potential targets and agents under evaluation. RECENT FINDINGS: Some agents with anti-inflammatory properties appear to have beneficial effects on atherosclerosis or subsequent risk for cardiovascular events, while others have been disappointing. The anti-inflammatory actions of statins have been linked retrospectively with their favorable effects on atherosclerosis progression and clinical outcomes. The cardiovascular safety of COX-2 inhibitors is being assessed prospectively in patients with atherosclerosis. Potential new therapeutic agents targeting other inflammatory mechanisms and oxidative stress are being evaluated in animal models and clinical trials. SUMMARY: Due to the contributory inflammatory pathways in atherosclerosis, the properties of existing and novel anti-inflammatory agents are being carefully and actively evaluated in cardiovascular disease. Advances in our understanding of both atherosclerosis and the inflammatory contributors may play an important role in future strategies to decrease the incidence of atherosclerotic cardiovascular disease.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".