The Effects of 5-year Etanercept Therapy on Cardiovascular Risk Factors in Patients with Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To investigate the effects of etanercept (ETN) on lipid metabolism and other known cardiovascular disease (CVD) risk factors in patients with psoriatic arthritis (PsA). METHODS: In an observational cohort of 118 consecutive patients with PsA, CVD risk factors were assessed over 5 years. Mixed-model analyses were performed to investigate the effects of ETN therapy on CVD risk factors over time. RESULTS: Disease Activity Score in 28 joints, C-reactive protein (CRP), and erythrocyte sedimentation rate decreased during therapy with ETN. There was an increase in total cholesterol (TC), high-density lipoprotein cholesterol (HDLc), and low-density lipoprotein cholesterol. The TC/HDLc ratio remained unaltered. The apolipoprotein B to apolipoprotein A-I (apoB/apoA-I) ratio decreased significantly. An increase in CRP was associated with an increase in the apoB/apoA-1 ratio. CONCLUSION: Serum lipid concentrations showed small changes over a 5-year period of ETN therapy and were inversely associated with inflammatory markers. Other CVD risk factors remained stable. The apoB/apoA-1 ratio decreased over time and an increase in disease activity was associated with an increase in this ratio. However, this modest lipid modulation cannot explain the observed beneficial CV effects of ETN, and ETN likely exerts those effects through inflammation-related mechanisms.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".