Managing Cardiovascular Risk in Systemic Lupus Erythematosus: Considerations for the Clinician
Bibliographic record
Abstract
Teresa Semalulu,1 Achieng Tago,2 Kevin Zhao,3 Konstantinos Tselios1 1Division of Rheumatology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada; 2Division of Cardiology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada; 3Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, CanadaCorrespondence: Konstantinos Tselios, Division of Rheumatology, Department of Medicine, McMaster University, 1280 Main St W, HSC 3H1B, Hamilton, Ontario, L8S 4K1, Canada, Tel +1 905 521 2100 Ext. 76714, Fax +1 905 521 4971, Email tseliosk@mcmaster.caAbstract: A significant improvement in the survival of patients with systemic lupus erythematosus (SLE) over recent decades is largely attributed to the impact of disease-modifying therapies on end-organ damage. Thus, cardiovascular disease now represents the leading cause of mortality in SLE. Various disease-specific mechanisms are responsible for advanced atherosclerosis, as they lead to premature endothelial dysfunction, arterial stiffness, arterial wall thickening, and plaque formation. Consequently, in the assessment of cardiovascular risk in SLE, we must not only consider traditional risk factors (ie, age, gender, dyslipidemia) but also the additional role of non-traditional risk factors such as persistent disease activity and prolonged corticosteroid use. Cardiovascular risk assessment incorporates general cardiovascular screening, as existing risk prediction scores underestimate cardiovascular risk in this patient population. There is also an expanding role of imaging modalities in screening. Risk reduction strategies integrate unique considerations for the use of low-dose aspirin and more stringent hypertension targets. Hydroxychloroquine is the only disease-modifying therapy with known cardiovascular benefit in SLE, though this is a promising area of study.Keywords: cardiovascular disease, atherosclerosis, endothelial dysfunction, coronary artery disease, risk stratification, prevention
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.013 | 0.023 |
| Insufficient payload (model declined to judge) | 0.005 | 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".