Golden retriever cystic uveal disease: a longitudinal study of iridociliary cysts, pigmentary uveitis, and pigmentary/cystic glaucoma over a decade in western Canada
Bibliographic record
Abstract
OBJECTIVES: To determine the incidence of iridociliary cysts, pigmentary uveitis (PU)/pigmentary cystic glaucoma (PCG) in golden retriever dogs in western Canada, the progression of iridociliary cysts to PU/PCG, and a mode of inheritance for this disorder. ANIMAL STUDIED: A total of 830 golden retriever dogs from Alberta, Saskatchewan, and Manitoba from 2004 to 2014 were studied. PROCEDURE: Data were compiled from Canine Eye Registry Foundation (CERF) or Orthopedic Foundation for Animals (OFA) records (n = 630) and clinical consultations (n = 200) for a retrospective assessment of iridociliary cysts, PU, and PCG. RESULTS: Total incidence of iridociliary cysts and PU from CERF/OFA data were 4.8% (n = 30/630) and 5.9% (n = 37/630), respectively. Incidence of PU increased with ages >4 years (12.7%, n = 32/251). Dogs diagnosed with thin-walled, attached iridociliary cysts had a high risk of being diagnosed with PU or PCG upon re-examination (56.5%, n = 13/23). No dogs diagnosed with thick-walled, anterior chamber cysts (n = 7) developed PU or PCG within the time frame of the study. Data from clinical consultations confirmed that PU carried a poor prognosis for the affected eyes as 44.9% (n = 22/49) of dogs progressed to PCG. PU- and PCG-affected dogs followed a familial pattern and there was an association with thin-walled iridociliary cysts. Pedigree analysis suggested an autosomal dominant mode of inheritance with partial penetrance. CONCLUSIONS: Thin-walled iridociliary cysts are associated with PU and PCG. All breeding golden retriever dogs should be examined annually by an ophthalmologist. The incidence of this disorder is higher in western Canada than previous reports in North America.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".