Association between interleukin-4 C589T polymorphism and asthma in Iraq: Ameta-analysis
Bibliographic record
Abstract
Abstract Background Asthma is a common disease with a complex risk architecture involving both genetic and environmental factors. Several studies have identified an association between interleukin (IL)-4 C-589T and asthma risk; however, the results remain inconclusive. Aims to identify the effect of IL-4 C589T polymorphisms on asthma susceptibility in Iraq. Material and methods PubMed, Web of Science, Scopus, and Google Scholar databases were searched for only case-control studies published on Iraqi asthmatic. The methodological quality assessment of the included studies was performed based on the Newcastle-Ottawa Quality Scale (NOS). Based on the heterogeneity, we conducted a meta-analysis using random-effect models. Pooled odds ratios (ORs) with a 95% confidence interval (CI) were calculated using the allele (C vs. T), homozygous (CC vs. TT), heterozygous (CT vs. TT), dominant (CC þ CT vs. TT), and recessive (CC vs. CT þ TT) genetic models to assess the strength of the relationship between IL-4 C589T polymorphism and asthma risk. In addition, the stability of our analysis was evaluated by heterogeneity, sensitivity, and study design, and publication bias analysis. Result We included 5 case-control studies with a total of 359 cases and 245 controls. All genetic models showed a higher risk of asthma, the overall analyses were a highly statistically significant. There was moderate to high heterogeneity among the genetic models. However, sensitivity analysis revealed highly significant differences in the pooled odds ratios of the rs2243250 polymorphism between asthmatic patients and control groups. Conclusion The meta-analysis identified a significant association between the IL-4 C-589T polymorphism and asthma. However, the substantial result variability indicates the need for well-designed case-control studies with a large population to more accurately estimate this association.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.036 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".