Clinical and histological characteristics of canine ocular gliovascular syndrome
Bibliographic record
Abstract
OBJECTIVE: To characterize the clinical, diagnostic, and histopathologic findings in dogs with canine ocular gliovascular syndrome (COGS). PROCEDURES: The archives at the Comparative Ocular Pathology Laboratory of Wisconsin (COPLOW) were used to identify eyes with COGS. Histopathological inclusion criteria included: a neovascular membrane extending from the optic nerve head or retina, clusters of spindle cells lacking vascularization within the vitreous, and histological signs of glaucoma. Special and immunohistochemical (IHC) staining techniques were performed. Clinical data, treatments, and outcomes were obtained from case records and information provided by submitting veterinarians. RESULTS: Thirty-seven eyes of 36 dogs were identified with COGS. The average age at diagnosis was 8.8 years (±2.2). The relative risk for a Labrador retriever affected by COGS was significantly greater (9.3 times) (P < 0.0001) when compared to all other dog breeds within the COPLOW database. Most dogs presented with hyphema and secondary glaucoma; average intraocular pressure was 39 mmHg (±19). Average time to enucleation or evisceration was 27 days. Vitreal cells stained positive with IHC for glial fibrillary acidic protein in 14 of 17 globes, and vascular endothelial growth factor was expressed in the vitreal cells in five of five globes. CONCLUSIONS: We have defined a syndrome associated with vitreal glial cell aggregates and neovascular proliferation from the optic nerve or retina, which leads to neovascular glaucoma. The inflammation and secondary glaucoma resulting from this syndrome appear poorly responsive to conventional medical therapies. The exact etiology of COGS remains undetermined, but a systemic etiology is unlikely.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".