Glutathione S-Transferase Genotype polymorphism and Primary Open-Angle Glaucoma in an Italian population
Bibliographic record
Abstract
Abstract Purpose Oxidative damage to the trabecular meshwork (TM) represents one of the pathogenic mechanisms leading to primary open angle glaucoma (POAG). Glutathione S-transferase mu 1 (GSTM1) may neutralizes reactive oxygen species protecting the TM. The present paper investigates the prevalence of GSTM1 null genotype in an Italian population, and its association with POAG treated either medically or surgically. Methods In a case-control study, the GSTM1 genotype was identified in POAGs and controls. The POAGs patients were divided in two groups: medical POAGs and surgical POAGS. Medical POAGs consisted of patients with a well-controlled intraocular pressure (IOP) by IOP-lowering medications and a stable visual field (VF). Patients with an uncontrolled IOP and a progressing VF that were submitted to incisional surgery formed the surgical POAGs’ group. Results We enrolled 104 medical POAGs, 158 surgical POAGs and 263 Controls. No significative differences between the groups existed regarding age and gender (p=0.275 and p=0.950, respectively). All the enrolled subjects were Caucasian of Italian descents. The GSTM1 null genotype was identified in 57 (45.2%) medical POAGs, 91 (57.6%) surgical POAGs and, 119 (45.3%) controls (p=0.033). The association between medical POAG and GSTM1 null status was non-significant (OR= 1.44, 95% IC = 0.86 to 2.39) whereas the association was significant for surgical POAGs (OR= 2.01, 95% IC= 1.26 to 3.21) Conclusions Our results showed an association between the GSTM1 null genotype and glaucoma that require surgery in an Italian population. GSTM1 null genotype detection may help to identify high-risk glaucoma patients that require a closer follow-up and a more aggressive treatments.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".