Vulnerable plaques and patients: state-of-the-art
Bibliographic record
Abstract
Despite advanced understanding of the biology of atherosclerosis, coronary heart disease remains the leading cause of death worldwide. Progress has been challenging as half of the individuals who suffer sudden cardiac death do not experience premonitory symptoms. Furthermore, it is well-recognized that also a plaque that does not cause a haemodynamically significant stenosis can trigger a sudden cardiac event, yet the majority of ruptured or eroded plaques remain clinically silent. In the past 30 years since the term 'vulnerable plaque' was introduced, there have been major advances in the understanding of plaque pathogenesis and pathophysiology, shifting from pursuing features of 'vulnerability' of a specific lesion to the more comprehensive goal of identifying patient 'cardiovascular vulnerability'. It has been also recognized that aside a thin-capped, lipid-rich plaque associated with plaque rupture, acute coronary syndromes (ACS) are also caused by plaque erosion underlying between 25% and 60% of ACS nowadays, by calcified nodule or by functional coronary alterations. While there have been advances in preventive strategies and in pharmacotherapy, with improved agents to reduce cholesterol, thrombosis, and inflammation, events continue to occur in patients receiving optimal medical treatment. Although at present the positive predictive value of imaging precursors of the culprit plaques remains too low for clinical relevance, improving coronary plaque imaging may be instrumental in guiding pharmacotherapy intensity and could facilitate optimal allocation of novel, more aggressive, and costly treatment strategies. Recent technical and diagnostic advances justify continuation of interdisciplinary research efforts to improve cardiovascular prognosis by both systemic and 'local' diagnostics and therapies. The present state-of-the-art document aims to present and critically appraise the latest evidence, developments, and future perspectives in detection, prevention, and treatment of 'high-risk' plaques occurring in 'vulnerable' patients.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".