Cataracts in Labrador Retriever and Jack Russell Terrier: a two-year retrospective study
Bibliographic record
Abstract
Cataracts are among the most common ocular diseases and are a leading cause of vision loss in dogs and humans. Jack Russell Terriers (JRT) and Labrador Retrievers (LR) are among the canine breeds most affected by cataracts. This study aimed to analyse the clinical features and the surgical outcome of cataracts in JRT and LR in an ophthalmological reference Veterinary Hospital in the United Kingdom. Medical records from JRT and LR diagnosed with cataracts between January of 2015 and December of 2016 were retrospectively evaluated. Data related with identification, clinical history, pre-operative features and surgical outcome were analysed. Forty-four dogs (81 eyes), including 26 JRT and 18 LR were enrolled in the study. Mean ages were 10.2 ± 3.2 years in JRT and 8.5 ± 3.7 years in LR. Twenty-eight (63.6%) were females and 16 (36.4%) were males. Most dogs (84.1%) presented bilateral cataracts. The most prevalent type of cataracts was nuclear and cortical in JRT (42.9%), and subcapsular in LR (31.3%). Significant differences in cataract location within the lens were detected between the two breeds (P=0.013).Senile in JRT (n=7) and genetic in LR (n=7) were the most common aetiologies. Concomitant ocular lesions were more frequent in dogs presented with cataracts in advanced stages, and included lens position (n=18; JRT: n=15; LR: n=3) and retinal alterations (n=8; JRT: n=2; LR: n=6), and glaucoma (n=6; JRT: n=5; LR: n=1). Thirty-three animals (75.0%, 51 eyes) were submitted to phacoemulsification with intraocular lens placement. Of these, 28 eyes (54.9%; JRT: n=21; LR: n=7) were visual, 17 eyes (33.3%; JRT: n=11; LR: n=6) presented impaired vision and six eyes (11.8%; JRT: n=0; LR: n=6) were blind at last clinical record. Post-operative complications were detected in 11 eyes (21.6%), being more frequent in dogs presented with cataracts in advanced stages. The obtained results and the multifactorial nature of cataracts call for further studies to identify and characterize the variables in a broader assessment, including other breeds and influencing factors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".