Prevalence of antiphospholipid antibodies in Behçet's disease: A systematic review and meta-analysis
Bibliographic record
Abstract
Behçet's disease (BD) is a multifactorial systemic inflammatory disease of unknown aetiology characterised by several clinical manifestations including vascular involvements (i.e., both arterial and venous thrombosis). Antiphospholipid antibodies (aPLs)-including anticardiolipin (aCL), anti-β2-glycoprotein I (β2-GPI) antibodies and lupus anticoagulant (LA) are detected in systemic autoimmune diseases which contribute to thrombosis. The aim of this systematic review and meta-analysis was to evaluate the prevalence of aPLs in patients with BD as compared to controls. A protocol was registered in PROSPERO (Registration No. CRD42018088125) and a systematic literature search was conducted through PubMed, Web of Science, Embase, Scopus and ScienceDirect databases. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using random-effects model. Quality assessment was carried out by using the modified 9-star Newcastle-Ottawa Scale (NOS). Publication bias was evaluated via visualisation of contour- enhanced and trim and fill funnel plots along with Begg's and Egger's tests. We included ten case-control studies (a total of 999 participants from 380 BD patients and 619 controls) based on the inclusion criteria. The prevalence of aCL (OR: 12.10, 95% CI: 5.15-28.41, p<0.00001) and anti-β2-GPI antibodies (OR: 23.57, 95% CI: 1.31-423.63, p = 0.03) were statistically significant, however, the prevalence of LA was not significant (OR: 13.77, 95% CI: 0.65-293.59, p = 0.09). The results remained statistically significant from different sensitivity analyses which represented the robustness of this meta-analysis. According to the NOS, 50.0% of the studies were considered as of high methodological quality (low risk of bias). No significant publication bias was detected from contour-enhanced and trim and fill funnel plots or Begg's and Egger's tests. This meta-analysis established that there is a significantly high prevalence of aPLs (i.e., aCL and anti-β2-GPI antibodies) in patients with BD when compared to controls.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".