Elevated intravitreal interleukin-6 levels in patients with proliferative diabetic retinopathy
Bibliographic record
Abstract
Background: We conducted this study to elucidate the possible role of interleukin-6 (IL-6) in the pathogenesis of proliferative diabetic retinopathy (PDR). Methods: Together with pertinent clinical and laboratory data, intravitreal and serum concentrations of IL-6 were determined in 8 patients with PDR by means of enzyme-linked immunosorbent assay (ELISA). The results were compared with data from 8 nondiabetic control subjects undergoing vitrectomy. Results: Significantly higher intravitreal IL-6 concentrations were found in patients with PDR (mean [SD], 755 [177] pg/mL) compared with control subjects (93 [151] pg/mL) ( p = 0.001). The serum IL-6 levels in the PDR group were lower than the measurable threshold of the ELISA kit (<0.16 pg/mL). Diabetic patients with macular edema had a higher mean (SD) level of intravitreal IL-6 (896 [73] pg/mL) compared with patients without macular edema (613 [119] pg/mL) (Mann-Whitney U test, p = 0.03). Correlation analysis did not reveal any significant association between intravitreal IL-6 levels and patient age, duration of either diabetes mellitus or vitreous hemorrhage, panretinal photocoagulation, type of current medical therapy, hyperglycemia, or the biochemical indicators of renal function. Interpretation: IL-6, a proinflammatory cytokine, may have a role in PDR. Intraocular production of IL-6 appears to be responsible for the elevated intravitreal levels observed.
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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 | 0.002 |
| 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) | 0.001 | 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".