Postoperative glaucoma in the Labrador Retriever: incidence, risk factors, and visual outcome following routine phacoemulsification
Bibliographic record
Abstract
OBJECTIVE: To evaluate the incidence and risk factors associated with development of postoperative glaucoma in the Labrador Retriever following routine phacoemulsification. METHODS: Medical records from Labradors and a randomly selected population of non-Labradors were retrospectively evaluated. Signalment, diabetic status, cataract stage, gonioscopic findings, presence of preoperative lens-induced uveitis, development of postoperative hypertension (POH), postoperative glaucoma and postoperative visual status were recorded for each patient. Survival curves were developed using the Cox proportional hazards model. RESULTS: Forty-two Labradors (66 eyes) and 199 non-Labradors (314 eyes) were included. The incidence of POH was significantly higher in Labradors (33%) than non-Labradors (18%). Labradors were at significantly increased risk of postoperative glaucoma and blindness compared to non-Labradors. Estimated probabilities of postoperative glaucoma in Labradors were 23%, 25%, 30% and 35% at weeks 4, 26, 52 and 104, respectively, compared with 5%, 6%, 7% and 9% at weeks 4, 26, 52 and 104, respectively, in non-Labradors. Estimated probabilities of postoperative blindness in Labradors were 5%, 9%, 15% and 27% at weeks 4, 26, 52 and 104, respectively, compared with 2%, 3%, 5% and 10% at weeks 4, 26, 52 and 104, respectively, in non-Labradors. Risk factors for the development of glaucoma in Labradors included increasing age and development of POH. No statistically significant risk factors for the development of glaucoma were identified in non-Labradors. CONCLUSIONS: Labradors are at increased risk of glaucoma and blindness following phacoemulsification compared with non-Labradors. POH and increasing age represent risk factors for the development of postoperative glaucoma in Labradors.
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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".