The association of serum anti-ribosomal P antibody with clinical and serological disorders in systemic lupus erythematosus: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Anti-ribosomal P (anti-P) antibody is a serological specific marker of systemic lupus erythematosus (SLE). The aim of this study is to investigate the association of this antibody with clinical and serological disorders in SLE. METHODS: All relevant literature was retrieved from PubMed, EMBASE, Web of Science and CNKI databases. The qualities of these studies were evaluated using a modified version of the Newcastle-Ottawa scale. The associations of anti-P antibody with clinical and serological disorders were determined by the pooled odds ratio (OR) and the confidence interval (CI) calculated using meta-analysis with the Mantel-Haenszel method. RESULTS: Sixteen cohort studies with 2355 patients were included in this study. Malar rash, oral ulcer and photosensitivity were strongly associated with serum anti-P antibody, with OR (95% CI) values of 2.05 (1.42-2.92), 1.49 (1.05-2.13) and 1.44 (1.08-1.91), respectively. Arthritis and renal involvement were not associated with anti-P antibody, whereas a high heterogeneity was observed due to ethnicity and publication bias, respectively. Neuropsychiatric SLE (NPSLE), hepatic involvement, anti-dsDNA, anti-Sm and anti-cardiolipin antibodies (aCL) were observed more frequently in anti-P positive patients than in negative patients. Studies on hepatic involvement showed a low precision with substantially broad CI (2.56-11.2). A high heterogeneity presented among studies on NPSLE, anti-Sm and aCL. CONCLUSIONS: Anti-P antibody is significantly associated with malar rash, oral ulcer, photosensitivity and serum anti-dsDNA antibody, and potentially associated with NPSLE, hepatic damage, serum anti-Sm and aCL.
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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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.020 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".