Association Between Depression and Vascular Disease in Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease with increased prevalence of cardiovascular disease (CVD) and depression. Although depression may contribute to CVD risk in population-based studies, its influence on cardiovascular morbidity in SLE has not been evaluated. We evaluated the association between depression and vascular disease in SLE. METHODS: A cross-sectional study was conducted from 2002-2005 in 161 women with SLE and without CVD. The primary outcome measure was a composite vascular disease marker consisting of the presence of coronary artery calcium and/or carotid artery plaque. RESULTS: In total, 101 women met criteria for vascular disease. In unadjusted analyses, several traditional cardiovascular risk factors, inflammatory markers, adiposity, SLE disease-related factors, and depression were associated with vascular disease. In the final multivariable model, the psychological variable depression was associated with nearly 4-fold higher odds for vascular disease (OR 3.85, 95% CI 1.37, 10.87) when adjusted for other risk factors of age, lower education level, hypertensive status, waist-hip ratio, and C-reactive protein. CONCLUSION: In SLE, depression is independently associated with vascular disease, along with physical factors.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".