Relationship between<i>HLA-DR</i>gene polymorphisms and outcomes of hepatitis B viral infections: A meta-analysis
Bibliographic record
Abstract
AIM: To assess the rigorous relationship between human leukocyte antigens (HLA)-DR alleles and outcomes of hepatitis B virus (HBV) infections by means of meta-analysis. METHODS: Medline/PubMed, EMBASE, CNKI and VIP were searched to identify relevant studies. Study quality was evaluated using the Newcastle-Ottawa Scale. Odds ratios (OR) and 95% confidence interval (95% CI) were pooled using Stata 11.0. Subgroup analyses were performed by ethnicity. Heterogeneity and publication bias analyses were performed to validate the credibility. RESULTS: A total of 2609 patients with chronic hepatitis B and 2606 controls spontaneously recovering from prior HBV infection were included. Meta-analysis showed that HLA-DR*04 (OR = 0.72, 95% CI: 0.60-0.85) and DR*13 (OR = 0.27, 95% CI: 0.19-0.37) alleles were significantly associated with HBV clearance while patients carrying HLA-DR*03 (OR = 1.47, 95% CI: 1.16-1.87) or DR*07 (OR = 1.59, 95% CI: 1.24-2.03) alleles had a significantly increased risk of chronic HBV persistence. For the HLA-DR*01 polymorphism, a significantly association with HBV clearance was found in Chinese Han group (OR = 0.48, 95% CI: 0.26-0.86), but not found in other ethnic groups (P = 0.191). For other polymorphisms, no association with the HBV infection outcome was found. CONCLUSION: HLA-DR*04 and DR*13 alleles may be the protective factors for HBV clearance and HLA-DR*03, and DR*07 alleles may be the risk factors for HBV persistence.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".