The association between the rs11196218A/G polymorphism of the TCF7L2 gene and type 2 diabetes in the Chinese Han population: a meta-analysis
Bibliographic record
Abstract
Transcription factor 7-like 2 has been shown to be associated with type 2 diabetes mellitus in multiple ethnic groups in recent years. In the Chinese Han population in particular, numerous studies have evaluated the association between the rs11196218A/G polymorphism of the transcription factor 7-like 2 gene and type 2 diabetes mellitus. However, the results have been inconsistent, so we performed a meta-analysis to assess the association. Odds ratio and 95% confidence interval values were calculated using a random-effects model or a fixed-effects model based on heterogeneity analysis. The quality of the included studies was evaluated using the Newcastle-Ottawa Scale. Subgroup analyses were conducted based on conformity with Hardy-Weinberg equilibrium in the control group as well as on other variables, such as age, sex and body mass index. Sensitivity analysis was also performed to detect heterogeneity and to assess the stability of the results. In total, 10 case-control studies comprising 7,491 cases and 12,968 controls were included in this meta-analysis. The combined analysis indicated that the rs11196218A/G polymorphism was not associated with type 2 diabetes mellitus (G vs. A, OR=1.04, 95% CI=0.97-1.13, p=0.28). The subgroup analyses also did not show any association between the rs11196218A/G polymorphism and the risk of type 2 diabetes mellitus. Furthermore, the results of the subgroup analyses indicated that the absence of an association was not influenced by age, sex or body mass index. The results of the sensitivity analysis verified the reliability and stability of this meta-analysis. In conclusion, this study indicated that there is no significant association between the rs11196218A/G polymorphism and the risk of type 2 diabetes mellitus in the Chinese Han population.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.045 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".