Cardiovascular Disease in Systemic Lupus Erythematosus: The Role of Traditional and Lupus Related Risk Factors
Bibliographic record
Abstract
Atherosclerosis is a chronic inflammatory disorder characterized by immune cell activation, inflammation driven plaque formation and subsequent destabilization. In other disorders of an inflammatory nature, the chronic inflammatory state per se has been linked to acceleration of the atherosclerotic process which is underlined by an increased incidence of cardiovascular disease (CVD) in disorders such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA) and antiphopholipid (Hughes) syndrome (APS). SLE is an autoimmune disease that may affect any organ. Premature coronary heart disease has emerged as a major cause of morbidity and mortality in SLE. In addition to mortality, cardiovascular morbidity is also markedly increased in these patients, compared with the general population. The increased cardiovascular risk can be explained only partially by an increased prevalence of classical risk factors for cardiovascular disease; it also appears to be related to inflammation. Inflammation is increasingly being considered central to the pathogenesis of atherosclerosis and an important risk factor for vascular disease. Recent epidemiologic and pathogenesis studies have suggested a great deal in common between the pathogenesis of prototypic autoimmune disease such as SLE and that of atherosclerosis.We will review traditional risk factors for CVD in SLE. We will also discuss the role of inflammation in atherosclerosis, as well as possible treatment strategies in these 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".