Changes in Lipid Profile Between Flare and Remission of Patients with Systemic Lupus Erythematosus: A Prospective Study
Bibliographic record
Abstract
OBJECTIVE: To determine the lipid profile of patients with systemic lupus erythematosus (SLE) according to the disease activity, and to calculate the percentage of patients that diverged from optimal values. METHODS: Serum was collected from 52 patients with SLE at flare and at remission. SLE disease activity was measured by using the SLE Disease Activity Index (SLEDAI). Clinical and biological measures were evaluated in both situations. Total cholesterol (TC), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), and triglyceride (TG) levels were analyzed after overnight fasting. We also calculated the atherogenic ratios of TC/HDLC and LDLC/HDLC. RESULTS: SLE patients had significantly higher median TC/HDLC and LDLC/HDLC ratios at flare than during remission: 4.5 +/- 1.5 versus 3.9 +/- 1.0 (p = 0.007) and 2.7 +/- 1.1 versus 2.4 +/- 0.8 (p = 0.015), respectively. The differences persisted after adjustments based on kidney disease and treatment but not after adjusting by creatinine clearance < 60 ml/min/1.73 m(2) in remission. The variation between flare and remission of the percentage of SLE patients with high-risk levels of lipid profile to desirable values, and vice versa, was statistically significant for the LDLC/HDLC ratio (9 vs 1; p = 0.021). CONCLUSION: Our results reflect a higher risk of atherosclerosis phenomena in SLE patients during flare than during clinical remission. This might explain the propensity to develop coronary heart disease in patients with SLE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".