Serum Adiponectin Levels in Patients With Systemic Lupus Erythematosus
Bibliographic record
Abstract
BACKGROUND: Higher serum adiponectin in systemic lupus erythematosus (SLE) patients mitigates the inflammatory response. Previous studies investigated serum adiponectin level in SLE patients compared with control subjects, yielding inconsistent results. OBJECTIVE: The aim of this meta-analysis was to assess the difference between serum adiponectin levels in SLE patients compared with control subjects. METHODS: MEDLINE, PubMed, EMBASE, and Web of Science were searched from inception to August 31, 2016, to identify all observational studies that examined the relationship between serum adiponectin levels and SLE. The study quality was assessed by the Newcastle-Ottawa Scale. Standard mean difference values and 95% confidence intervals were estimated and pooled using the meta-analysis methodology. The Cochrane Q test and I statistics were used to test heterogeneity. To assess publication bias, visual observations of a funnel plot were used. The Stata software (version 11.0) was used for statistical analysis. RESULTS: A total of 8 studies including 782 SLE patients and 550 control subjects were eligible for the meta-analysis. In overall random-effects model including all the studies, we found that patients with SLE had higher serum adiponectin levels than control subjects (eight studies; pooled standardized mean difference, 0.502 μg/mL; 95% confidence interval, 0.021-0.984; I = 94.0%; P < 0.001). In subgroup analyses, SLE patients with body mass index of 25 kg/m or greater had higher serum adiponectin levels compared with control subjects. CONCLUSIONS: Collectively, our results demonstrate that higher serum adiponectin level is significantly associated with SLE. Furthermore, they suggest that serum adiponectin levels in SLE patients are not correlated with Systemic Lupus Erythematosus Disease Activity Index scores. Imbalanced adiponectin levels might be associated with onset of other chronic diseases.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".