Epstein-Barr virus infection and its association with systemic lupus erythematosus: Systematic review and meta-analysis
Bibliographic record
Abstract
Background Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder characterized by the production of autoantibodies that target most of the organ systems and lead to their dysfunction. The exact etiology of SLE remains unclear; however, genetic and environmental factors are believed to play significant roles. Viral infections, particularly Epstein-Barr virus (EBV), have been implicated as environmental triggers in SLE pathogenesis however, the observations remained inconsistent among studies and populations. The present study uses a meta-analysis approach to explore the prevalence of EBV infection in the general population and their role in the pathogenesis of SLE. Materials and Methods Various databases such as PubMed, Scopus, and ScienceDirect were searched to obtain eligible studies based on predetermined inclusion and exclusion criteria. The Newcastle-Ottawa Scale (NOS) was used for quality assessment of the eligible studies, and Comprehensive Meta-Analysis (CMA) v4 software was used for the analysis. Publication bias was assessed with funnel plots and Egger’s regression, while heterogeneity was evaluated with Cochrane Q and I 2 statistics. Results In the present investigation, a total of 28 studies comprising of 3926 healthy controls and 2968 SLE patients were included. EBV infections were prevalent in the healthy controls. While comparing the frequency of EBV DNA or antibodies positivity, the SLE patients had a higher positivity rate than the healthy controls, indicating that EBV infection is a risk factor for developing SLE. Furthermore, the sensitivity analysis also revealed that the meta-analysis was robust. Conclusion The majority of healthy subjects were previously exposed to EBV, and the infection could be a potential risk factor in SLE pathogenesis. However, future research is required to elucidate the possible mechanisms of EBV reactivation in SLE patients and examine potential preventive measures, such as antiviral therapies, in mitigating SLE risk.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".