Table_1_Extended analysis on peripheral blood cytokines correlated with hepatitis B virus viral load in chronically infected patients – a systematic review and meta-analysis.docx
Bibliographic record
Abstract
Background Hepatitis B Virus (HBV) can affect life quality. Monitoring and understanding the fluctuations of the HBV level of viremia related to the intricate immune activity of the host helps in the development of new treatment strategies and evaluation patterns. This meta-analysis presents the correlations between cytokines and the level of viremia in chronic HBV patients for a better comprehension of the immune mechanisms behind this infection. Methods We used PRISMA guidelines for this meta-analysis. The databases assessed were PUBMED, WEB OF SCIENCE, SCOPUS, and Cochrane Library. ZOTERO and PlotDigitizer helped the systematic research process. We extracted information related to the correlations between cytokines and the HBV-DNA level. Effect measures included comparisons between standardized mean differences and correlation coefficients. We evaluated retrieved articles with the Newcastle-Ottawa Quality Assessment Scale (NOS). The R 4.2.2 software displayed the statistical calculation and graphical representations. Results From 58,169 records, we extracted 16 articles with 32 different cytokine determinations. The main interleukins included in detection panels were IL-10 and IL-21. The meta-correlation analysis comprised 1,199 chronic HBV patients. The standardized mean difference between cytokine levels in HBV patients and healthy controls was 0.82 (95% CI = [−0.19, 1.84], p = 0.11). We observed a significant, fair, pooled correlation coefficient between IL-10, IL-9, and the viral load (r = 0.52, 95% CI = [0.19, 0.85]). Conclusion This meta-analysis brings novelty because it gives a first rigorous systematic look at multiple studies with many cytokines. Our research approaches a debatable issue and gives a possible solution for settling controversies. Future studies can arise towards understanding the immune disruption in HBV and the development of new, improved assays for prognosis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.347 | 0.002 |
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; both teacher heads agree on what is shown here.
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".