Association between Aldose Reductase Gene C(-106)T Polymorphism and Diabetic Retinopathy: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Controversial results regarding the associations between aldose reductase (AR) genetic polymorphisms and diabetic retinopathy (DR) have been reported for many years. The present meta-analysis was performed to clarify the effects of the AR gene C(-106)T polymorphism on DR risk. The PubMed, Web of Sciences, Cochrane library, EMBASE, Chinese National Knowledge Infrastructure, and Wan Fang databases were extensively searched in Chinese to select relevant studies with an updated date of April 25, 2018. The Newcastle-Ottawa Scale (NOS) was applied to assess quality. The random-effects model was applied to calculate the pooled OR and 95% CI. This meta-analysis identified 23 studies with an average score of 7.52 for NOS analysis, including 4,313 DR cases and 5,128 diabetes mellitus (DM) control cases. In the overall analysis, a significant association between the AR gene C(-106)T polymorphism and DR susceptibility was found. In subgroups stratified by DM type and ethnicity, significantly increased risks for DR were found in DM type 1, East Asian populations, and Middle Eastern populations. Compared with DR control cases, the following associations were found: T vs. C: OR 0.91, 95% CI 0.85-0.97, I2 = 72.9%; CT + TT vs. CC: OR 0.75, 95% CI 0.68-0.81, I2 = 86.7%; and CT vs. CC: OR 0.86, 95% CI 0.78-0.94, I2 = 70.5%. The results of this meta-analysis showed a significant association between the AR gene C(-106)T polymorphism and susceptibility to DR in DM patients. DM patients with allele T and CT+TT genotype of the AR gene may have a lower risk of DR.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".