Metabolic Syndrome Is Associated with Increased Arterial Stiffness and Biomarkers of Subclinical Atherosclerosis in Patients with Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Aortic pulse wave velocity (PWV) is an independent predictor of risk for atherosclerotic cardiovascular disease. Metabolic syndrome (MetS) is more prevalent in patients with systemic lupus erythematosus (SLE) compared with matched healthy subjects. Aortic PWV is increased in MetS. The purpose of this cross-sectional study was to determine the association between MetS and aortic PWV and other surrogate biomarkers of subclinical atherosclerosis in SLE. METHODS: One hundred twenty-eight patients with SLE were studied. We established the presence of MetS according to the National Cholesterol Education Program Adult Treatment Panel III definition and we measured PWV, glucose, insulin, glycosylated hemoglobin (HbA(1c)), insulin sensitivity (HOMA index), lipid levels, uric acid, homocysteine, fibrinogen, D-dimer, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), interleukin 6 (IL-6), IL-8, IL-10, C3, C4, autoantibodies, SLE Disease Activity Index (SLEDAI), and Systemic Lupus International Collaborating Clinics/ACR Damage Index. Duration of SLE and treatment was also recorded. Multivariate logistic regression analysis was used to identify independent determinants of increased PWV. RESULTS: SLE patients with MetS had higher aortic PWV (9.8 +/- 2.4 vs 8.5 +/- 1.7 m/s; p = 0.002) and increased biomarkers of subclinical atherosclerosis such as CRP, IL-6, C3, uric acid, homocysteine, fibrinogen and D-dimer, compared to those without MetS. HOMA index and insulin and HbA(1c) levels were also higher in this group. No differences were found in variables related to lupus activity (ESR, C4, SLEDAI, IL-8, IL-10, and treatment for SLE). In the multivariate model, increased PWV was associated with age, male sex, MetS, duration of SLE, and CRP. CONCLUSION: MetS may contribute to the development of accelerated atherosclerosis in SLE.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".