In vivo evaluation of retinal ganglion cells degeneration in eyes with branch retinal vein occlusion
Bibliographic record
Abstract
PURPOSE: To analyse the topographic changes in retinal ganglion cells (RGCs) in eyes with unilateral naive branch retinal vein occlusion (BRVO) in comparison to normal fellow eyes and to healthy control eyes. METHODS: We performed a retrospective analysis of 66 eyes (33 subjects) with naive unilateral BRVO who underwent spectral-domain optical coherence tomography using Cirrus HD-OCT. We also included 67 eyes of 48 age-matched healthy volunteers as control group. Average, minimum and sectoral macular ganglion cell-inner plexiform layer (GCIPL) thickness, macular retinal nerve fibre layer (RNFL) thickness and outer retinal thickness were collected. Comparison of the GCIPL, RNFL and outer retinal thicknesses among study eyes, normal fellow eyes and control groups was performed. RESULTS: The average and minimum macular GCIPL thicknesses were constantly and diffusely reduced in BRVO compared with normal fellow eyes and healthy controls (p<0.001 for each GCIPL sector). The average macular RNFL thickness was reduced in BRVO eyes compared with normal fellow eyes (p=0.01) and tended to be lower than controls (p=0.07). The minimum RNFL thickness in eyes with BRVO was significantly reduced when compared with fellow eyes (p<0.001) and control eyes (p<0.001). The average outer retina thickness was thicker in BRVO eyes compared with both fellow eyes (p<0.001) and controls (p<0.001). CONCLUSIONS: A significant reduction of the macular GCIPL and RNFL thicknesses was observed in eyes with BRVO. This finding is suggestive of RGCs degeneration; the neuroprotective effect of current therapeutic options might be an important consideration when evaluating treatment strategies and prognosticating visual outcome in BRVO eyes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".