A prospective study of the prevalence of corneal surface disease in dogs receiving prophylactic topical lubrication under general anesthesia
Bibliographic record
Abstract
OBJECTIVE: To identify the prevalence of corneal ulceration in dogs receiving prophylactic gel lubrication under general anesthesia (GA). MATERIALS AND METHODS: An ophthalmic examination was performed before premedication and 24 h after GA in 100 dogs (199 eyes) undergoing nonophthalmic procedures. Individuals with known pre-existing ocular surface conditions were excluded. An ocular lubricating gel containing carmellose sodium was applied by the anesthetist at induction and every 2-4 h until extubation. Logistic regression analysis was used to calculate risk factors for ulcerative disease, including signalment, length of GA, patient position, procedure performed, pre-, and post-GA ophthalmic examination findings and admitting service. A Wilcoxon rank sum test compared pre- and post-GA Schirmer tear test-1 (STT-1) values. RESULTS: One dog (0.5% of total eyes) developed fluorescein stain uptake consistent with superficial corneal ulceration that resolved within 48 h with supportive treatment. Twenty-five (18.6% of total eyes) developed a faint, patchy corneal uptake of stain in the axial cornea that was consistent with epithelial erosion. All erosions resolved with lubrication 24 h later. The decrease in STT-1 readings at 24 h post-GA was statistically significant from those pre-GA (P < 0.001). No significant risk factors for corneal erosion/ulceration were identified. CONCLUSIONS: The results of this study show that a basic protocol of prophylactic lubrication during GA was associated with a low prevalence of corneal ulceration but a higher prevalence of epithelial erosion. In addition, the study supports the need for post-GA corneal examination.
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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 | 0.000 |
| 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".